diff --git "a/vae_encoder.xml" "b/vae_encoder.xml"
--- "a/vae_encoder.xml"
+++ "b/vae_encoder.xml"
@@ -1,10 +1,10 @@
-<?xml version="1.0" ?>
+<?xml version="1.0"?>
<net name="torch_jit" version="11">
<layers>
<layer id="0" name="init_image" type="Parameter" version="opset1">
- <data shape="1,3,512,512" element_type="f32"/>
+ <data shape="1,3,512,512" element_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="init_image"/>
+ <attribute name="old_api_map_element_type" version="0" value="f16" />
</rt_info>
<output>
<port id="0" precision="FP32" names="init_image">
@@ -15,33 +15,70 @@
</port>
</output>
</layer>
- <layer id="1" name="Constant_13488" type="Const" version="opset1">
- <data element_type="f32" shape="1, 1, 512" offset="0" size="2048"/>
+ <layer id="1" name="Constant_155099_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 1, 512" offset="0" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>1</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="2" name="Constant_13483" type="Const" version="opset1">
- <data element_type="f32" shape="1, 1, 512" offset="2048" size="2048"/>
+ <layer id="2" name="Constant_155099" type="Convert" version="opset1">
+ <data destination_type="f32" />
+ <rt_info>
+ <attribute name="decompression" version="0" />
+ </rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </input>
<output>
- <port id="0" precision="FP32">
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="3" name="Constant_155094_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 1, 512" offset="1024" size="1024" />
+ <output>
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>1</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="3" name="m.encoder.conv_in.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 3, 3, 3" offset="4096" size="13824"/>
+ <layer id="4" name="Constant_155094" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.conv_in.weight"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="5" name="vae.encoder.conv_in.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 3, 3, 3" offset="2048" size="6912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.conv_in.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>3</dim>
<dim>3</dim>
@@ -49,11 +86,30 @@
</port>
</output>
</layer>
- <layer id="4" name="Convolution_114" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="6" name="vae.encoder.conv_in.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_114"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.conv_in.weight">
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="7" name="/encoder/conv_in/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -77,10 +133,10 @@
</port>
</output>
</layer>
- <layer id="5" name="Reshape_134" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="17920" size="512"/>
+ <layer id="8" name="Reshape_117418_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="8960" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -88,11 +144,30 @@
</port>
</output>
</layer>
- <layer id="6" name="onnx::Cast_249" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="9" name="Reshape_117418" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_133, Reshape_134, input, onnx::Cast_249"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="10" name="/encoder/conv_in/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -108,7 +183,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input,onnx::Cast_249">
+ <port id="2" precision="FP32" names="/encoder/conv_in/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -116,22 +191,16 @@
</port>
</output>
</layer>
- <layer id="7" name="onnx::Reshape_251" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_251"/>
- </rt_info>
+ <layer id="11" name="/encoder/down_blocks.0/resnets.0/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_251">
+ <port id="0" precision="I64" names="/encoder/down_blocks.0/resnets.0/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="8" name="onnx::InstanceNormalization_252" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_252"/>
- </rt_info>
+ <layer id="12" name="/encoder/down_blocks.0/resnets.0/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -144,29 +213,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_252">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="9" name="Constant_172" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_172"/>
- </rt_info>
+ <layer id="13" name="Constant_117455" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="10" name="MVN_173" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_192, Concat_237, MVN_173, Multiply_220, Reshape_193, Reshape_238, onnx::Reshape_255"/>
- </rt_info>
+ <layer id="14" name="MVN_117456" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -178,18 +241,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_255">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="11" name="onnx::Reshape_256" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_256"/>
- </rt_info>
+ <layer id="15" name="/encoder/down_blocks.0/resnets.0/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -199,16 +259,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_256">
+ <port id="1" precision="I64" names="/encoder/down_blocks.0/resnets.0/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="12" name="onnx::Mul_257" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_257"/>
- </rt_info>
+ <layer id="16" name="/encoder/down_blocks.0/resnets.0/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -220,7 +277,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_257">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -228,10 +285,10 @@
</port>
</output>
</layer>
- <layer id="13" name="Constant_13445" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="18464" size="512"/>
+ <layer id="17" name="Constant_155056_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="9248" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -239,11 +296,30 @@
</port>
</output>
</layer>
- <layer id="14" name="onnx::Add_260" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="18" name="Constant_155056" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_260"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="19" name="/encoder/down_blocks.0/resnets.0/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -259,7 +335,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_260">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm1/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -267,10 +343,10 @@
</port>
</output>
</layer>
- <layer id="15" name="Constant_13446" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="18976" size="512"/>
+ <layer id="20" name="Constant_155057_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="9504" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -278,11 +354,30 @@
</port>
</output>
</layer>
- <layer id="16" name="onnx::Cast_263" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="21" name="Constant_155057" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.4, onnx::Cast_263"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="22" name="/encoder/down_blocks.0/resnets.0/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -298,7 +393,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.4,onnx::Cast_263">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm1/Add_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -306,10 +401,7 @@
</port>
</output>
</layer>
- <layer id="17" name="input.8" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.8, onnx::Mul_265"/>
- </rt_info>
+ <layer id="23" name="/encoder/down_blocks.0/resnets.0/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -319,7 +411,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.8">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.0/resnets.0/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -327,13 +419,10 @@
</port>
</output>
</layer>
- <layer id="18" name="m.encoder.down_blocks.0.resnets.0.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 128, 3, 3" offset="19488" size="589824"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.resnets.0.conv1.weight"/>
- </rt_info>
+ <layer id="24" name="vae.encoder.down_blocks.0.resnets.0.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 128, 3, 3" offset="9760" size="294912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.0.resnets.0.conv1.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>128</dim>
<dim>3</dim>
@@ -341,11 +430,30 @@
</port>
</output>
</layer>
- <layer id="19" name="Convolution_278" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="25" name="vae.encoder.down_blocks.0.resnets.0.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_278"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.0.resnets.0.conv1.weight">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="26" name="/encoder/down_blocks.0/resnets.0/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -369,10 +477,10 @@
</port>
</output>
</layer>
- <layer id="20" name="Reshape_298" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="609312" size="512"/>
+ <layer id="27" name="Reshape_117580_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="304672" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -380,11 +488,30 @@
</port>
</output>
</layer>
- <layer id="21" name="onnx::Cast_267" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="28" name="Reshape_117580" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_297, Reshape_298, input.12, onnx::Cast_267"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="29" name="/encoder/down_blocks.0/resnets.0/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -400,7 +527,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.12,onnx::Cast_267">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/conv1/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -408,22 +535,16 @@
</port>
</output>
</layer>
- <layer id="22" name="onnx::Reshape_269" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_269"/>
- </rt_info>
+ <layer id="30" name="/encoder/down_blocks.0/resnets.0/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_269">
+ <port id="0" precision="I64" names="/encoder/down_blocks.0/resnets.0/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="23" name="onnx::InstanceNormalization_270" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_270"/>
- </rt_info>
+ <layer id="31" name="/encoder/down_blocks.0/resnets.0/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -436,29 +557,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_270">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="24" name="Constant_336" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_336"/>
- </rt_info>
+ <layer id="32" name="Constant_117617" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="25" name="MVN_337" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_356, Concat_401, MVN_337, Multiply_384, Reshape_357, Reshape_402, onnx::Reshape_273"/>
- </rt_info>
+ <layer id="33" name="MVN_117618" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -470,18 +585,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_273">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="26" name="onnx::Reshape_274" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_274"/>
- </rt_info>
+ <layer id="34" name="/encoder/down_blocks.0/resnets.0/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -491,16 +603,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_274">
+ <port id="1" precision="I64" names="/encoder/down_blocks.0/resnets.0/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="27" name="onnx::Mul_275" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_275"/>
- </rt_info>
+ <layer id="35" name="/encoder/down_blocks.0/resnets.0/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -512,7 +621,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_275">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -520,10 +629,10 @@
</port>
</output>
</layer>
- <layer id="28" name="Constant_13447" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="609824" size="512"/>
+ <layer id="36" name="Constant_155058_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="304928" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -531,11 +640,30 @@
</port>
</output>
</layer>
- <layer id="29" name="onnx::Add_278" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="37" name="Constant_155058" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_278"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="38" name="/encoder/down_blocks.0/resnets.0/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -551,7 +679,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_278">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm2/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -559,10 +687,10 @@
</port>
</output>
</layer>
- <layer id="30" name="Constant_13448" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="610336" size="512"/>
+ <layer id="39" name="Constant_155059_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="305184" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -570,11 +698,30 @@
</port>
</output>
</layer>
- <layer id="31" name="onnx::Cast_281" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="40" name="Constant_155059" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.16, onnx::Cast_281"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="41" name="/encoder/down_blocks.0/resnets.0/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -590,7 +737,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.16,onnx::Cast_281">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/norm2/Add_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -598,10 +745,7 @@
</port>
</output>
</layer>
- <layer id="32" name="input.20" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.20, onnx::Mul_283"/>
- </rt_info>
+ <layer id="42" name="/encoder/down_blocks.0/resnets.0/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -611,7 +755,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.20">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.0/resnets.0/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -619,13 +763,10 @@
</port>
</output>
</layer>
- <layer id="33" name="m.encoder.down_blocks.0.resnets.0.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 128, 3, 3" offset="610848" size="589824"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.resnets.0.conv2.weight"/>
- </rt_info>
+ <layer id="43" name="vae.encoder.down_blocks.0.resnets.0.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 128, 3, 3" offset="305440" size="294912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.0.resnets.0.conv2.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>128</dim>
<dim>3</dim>
@@ -633,11 +774,30 @@
</port>
</output>
</layer>
- <layer id="34" name="Convolution_442" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="44" name="vae.encoder.down_blocks.0.resnets.0.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_442"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.0.resnets.0.conv2.weight">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="45" name="/encoder/down_blocks.0/resnets.0/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -661,10 +821,10 @@
</port>
</output>
</layer>
- <layer id="35" name="Reshape_462" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1200672" size="512"/>
+ <layer id="46" name="Reshape_117742_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="600352" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -672,11 +832,30 @@
</port>
</output>
</layer>
- <layer id="36" name="onnx::Add_285" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="47" name="Reshape_117742" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_461, Reshape_462, onnx::Add_285"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="48" name="/encoder/down_blocks.0/resnets.0/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -692,7 +871,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_285">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/conv2/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -700,11 +879,8 @@
</port>
</output>
</layer>
- <layer id="37" name="onnx::Div_286" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.24, onnx::Cast_288, onnx::Div_286"/>
- </rt_info>
+ <layer id="49" name="/encoder/down_blocks.0/resnets.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -720,7 +896,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.24,onnx::Cast_288,onnx::Div_286">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.0/Add_output_0,/encoder/down_blocks.0/resnets.0/Div_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -728,22 +904,16 @@
</port>
</output>
</layer>
- <layer id="38" name="onnx::Reshape_290" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_290"/>
- </rt_info>
+ <layer id="50" name="/encoder/down_blocks.0/resnets.1/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_290">
+ <port id="0" precision="I64" names="/encoder/down_blocks.0/resnets.1/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="39" name="onnx::InstanceNormalization_291" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_291"/>
- </rt_info>
+ <layer id="51" name="/encoder/down_blocks.0/resnets.1/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -756,29 +926,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_291">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="40" name="Constant_503" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_503"/>
- </rt_info>
+ <layer id="52" name="Constant_117782" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="41" name="MVN_504" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_523, Concat_568, MVN_504, Multiply_551, Reshape_524, Reshape_569, onnx::Reshape_294"/>
- </rt_info>
+ <layer id="53" name="MVN_117783" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -790,18 +954,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_294">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="42" name="onnx::Reshape_295" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_295"/>
- </rt_info>
+ <layer id="54" name="/encoder/down_blocks.0/resnets.1/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -811,16 +972,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_295">
+ <port id="1" precision="I64" names="/encoder/down_blocks.0/resnets.1/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="43" name="onnx::Mul_296" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_296"/>
- </rt_info>
+ <layer id="55" name="/encoder/down_blocks.0/resnets.1/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -832,7 +990,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_296">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -840,10 +998,10 @@
</port>
</output>
</layer>
- <layer id="44" name="Constant_13449" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1201184" size="512"/>
+ <layer id="56" name="Constant_155060_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="600608" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -851,27 +1009,46 @@
</port>
</output>
</layer>
- <layer id="45" name="onnx::Add_299" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="57" name="Constant_155060" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_299"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
- <dim>512</dim>
- <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
</port>
+ </input>
+ <output>
<port id="1" precision="FP32">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
<dim>1</dim>
</port>
- </input>
- <output>
- <port id="2" precision="FP32" names="onnx::Add_299">
+ </output>
+ </layer>
+ <layer id="58" name="/encoder/down_blocks.0/resnets.1/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm1/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -879,10 +1056,10 @@
</port>
</output>
</layer>
- <layer id="46" name="Constant_13450" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1201696" size="512"/>
+ <layer id="59" name="Constant_155061_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="600864" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -890,11 +1067,30 @@
</port>
</output>
</layer>
- <layer id="47" name="onnx::Cast_302" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="60" name="Constant_155061" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.28, onnx::Cast_302"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="61" name="/encoder/down_blocks.0/resnets.1/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -910,7 +1106,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.28,onnx::Cast_302">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm1/Add_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -918,10 +1114,7 @@
</port>
</output>
</layer>
- <layer id="48" name="input.32" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.32, onnx::Mul_304"/>
- </rt_info>
+ <layer id="62" name="/encoder/down_blocks.0/resnets.1/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -931,7 +1124,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.32">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.0/resnets.1/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -939,13 +1132,10 @@
</port>
</output>
</layer>
- <layer id="49" name="m.encoder.down_blocks.0.resnets.1.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 128, 3, 3" offset="1202208" size="589824"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.resnets.1.conv1.weight"/>
- </rt_info>
+ <layer id="63" name="vae.encoder.down_blocks.0.resnets.1.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 128, 3, 3" offset="601120" size="294912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.0.resnets.1.conv1.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>128</dim>
<dim>3</dim>
@@ -953,11 +1143,30 @@
</port>
</output>
</layer>
- <layer id="50" name="Convolution_609" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="64" name="vae.encoder.down_blocks.0.resnets.1.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_609"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.0.resnets.1.conv1.weight">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="65" name="/encoder/down_blocks.0/resnets.1/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -981,10 +1190,10 @@
</port>
</output>
</layer>
- <layer id="51" name="Reshape_629" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1792032" size="512"/>
+ <layer id="66" name="Reshape_117907_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="896032" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -992,11 +1201,30 @@
</port>
</output>
</layer>
- <layer id="52" name="onnx::Cast_306" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="67" name="Reshape_117907" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_628, Reshape_629, input.36, onnx::Cast_306"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="68" name="/encoder/down_blocks.0/resnets.1/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1012,7 +1240,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.36,onnx::Cast_306">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/conv1/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1020,22 +1248,16 @@
</port>
</output>
</layer>
- <layer id="53" name="onnx::Reshape_308" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_308"/>
- </rt_info>
+ <layer id="69" name="/encoder/down_blocks.0/resnets.1/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_308">
+ <port id="0" precision="I64" names="/encoder/down_blocks.0/resnets.1/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="54" name="onnx::InstanceNormalization_309" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_309"/>
- </rt_info>
+ <layer id="70" name="/encoder/down_blocks.0/resnets.1/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1048,29 +1270,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_309">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="55" name="Constant_667" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_667"/>
- </rt_info>
+ <layer id="71" name="Constant_117944" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="56" name="MVN_668" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_687, Concat_732, MVN_668, Multiply_715, Reshape_688, Reshape_733, onnx::Reshape_312"/>
- </rt_info>
+ <layer id="72" name="MVN_117945" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1082,18 +1298,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_312">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>1048576</dim>
</port>
</output>
</layer>
- <layer id="57" name="onnx::Reshape_313" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_313"/>
- </rt_info>
+ <layer id="73" name="/encoder/down_blocks.0/resnets.1/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1103,16 +1316,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_313">
+ <port id="1" precision="I64" names="/encoder/down_blocks.0/resnets.1/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="58" name="onnx::Mul_314" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_314"/>
- </rt_info>
+ <layer id="74" name="/encoder/down_blocks.0/resnets.1/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1124,7 +1334,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_314">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1132,10 +1342,10 @@
</port>
</output>
</layer>
- <layer id="59" name="Constant_13451" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1792544" size="512"/>
+ <layer id="75" name="Constant_155062_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="896288" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1143,11 +1353,30 @@
</port>
</output>
</layer>
- <layer id="60" name="onnx::Add_317" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="76" name="Constant_155062" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_317"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="77" name="/encoder/down_blocks.0/resnets.1/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1163,7 +1392,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_317">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm2/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1171,10 +1400,10 @@
</port>
</output>
</layer>
- <layer id="61" name="Constant_13452" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="1793056" size="512"/>
+ <layer id="78" name="Constant_155063_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="896544" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1182,11 +1411,30 @@
</port>
</output>
</layer>
- <layer id="62" name="onnx::Cast_320" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="79" name="Constant_155063" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.40, onnx::Cast_320"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="80" name="/encoder/down_blocks.0/resnets.1/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1202,7 +1450,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.40,onnx::Cast_320">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/norm2/Add_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1210,10 +1458,7 @@
</port>
</output>
</layer>
- <layer id="63" name="input.44" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.44, onnx::Mul_322"/>
- </rt_info>
+ <layer id="81" name="/encoder/down_blocks.0/resnets.1/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1223,7 +1468,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.44">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.0/resnets.1/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1231,13 +1476,10 @@
</port>
</output>
</layer>
- <layer id="64" name="m.encoder.down_blocks.0.resnets.1.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 128, 3, 3" offset="1793568" size="589824"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.resnets.1.conv2.weight"/>
- </rt_info>
+ <layer id="82" name="vae.encoder.down_blocks.0.resnets.1.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 128, 3, 3" offset="896800" size="294912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.0.resnets.1.conv2.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>128</dim>
<dim>3</dim>
@@ -1245,11 +1487,30 @@
</port>
</output>
</layer>
- <layer id="65" name="Convolution_773" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="83" name="vae.encoder.down_blocks.0.resnets.1.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_773"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.0.resnets.1.conv2.weight">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="84" name="/encoder/down_blocks.0/resnets.1/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1273,10 +1534,10 @@
</port>
</output>
</layer>
- <layer id="66" name="Reshape_793" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="2383392" size="512"/>
+ <layer id="85" name="Reshape_118069_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="1191712" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1284,11 +1545,30 @@
</port>
</output>
</layer>
- <layer id="67" name="onnx::Add_324" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="86" name="Reshape_118069" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_792, Reshape_793, onnx::Add_324"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="87" name="/encoder/down_blocks.0/resnets.1/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1304,7 +1584,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_324">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/conv2/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1312,11 +1592,8 @@
</port>
</output>
</layer>
- <layer id="68" name="onnx::Div_325" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Div_325, onnx::Pad_327"/>
- </rt_info>
+ <layer id="88" name="/encoder/down_blocks.0/resnets.1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1332,7 +1609,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Div_325,onnx::Pad_327">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/resnets.1/Add_output_0,/encoder/down_blocks.0/resnets.1/Div_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>512</dim>
@@ -1340,13 +1617,10 @@
</port>
</output>
</layer>
- <layer id="69" name="m.encoder.down_blocks.0.downsamplers.0.conv.weight" type="Const" version="opset1">
- <data element_type="f32" shape="128, 128, 3, 3" offset="2383904" size="589824"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.0.downsamplers.0.conv.weight"/>
- </rt_info>
+ <layer id="89" name="vae.encoder.down_blocks.0.downsamplers.0.conv.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="128, 128, 3, 3" offset="1191968" size="294912" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.0.downsamplers.0.conv.weight">
+ <port id="0" precision="FP16">
<dim>128</dim>
<dim>128</dim>
<dim>3</dim>
@@ -1354,11 +1628,30 @@
</port>
</output>
</layer>
- <layer id="70" name="Convolution_925" type="Convolution" version="opset1">
- <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="90" name="vae.encoder.down_blocks.0.downsamplers.0.conv.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_925, Split_857, input.48"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.0.downsamplers.0.conv.weight">
+ <dim>128</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="91" name="/encoder/down_blocks.0/downsamplers.0/conv/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1382,10 +1675,10 @@
</port>
</output>
</layer>
- <layer id="71" name="Reshape_945" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="2973728" size="512"/>
+ <layer id="92" name="Reshape_118224_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="1486880" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1393,11 +1686,30 @@
</port>
</output>
</layer>
- <layer id="72" name="onnx::Cast_352" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="93" name="Reshape_118224" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_944, Reshape_945, input.52, onnx::Cast_352"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="94" name="/encoder/down_blocks.0/downsamplers.0/conv/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1413,7 +1725,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.52,onnx::Cast_352">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.0/downsamplers.0/conv/Conv_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>256</dim>
@@ -1421,13 +1733,10 @@
</port>
</output>
</layer>
- <layer id="73" name="m.encoder.down_blocks.1.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 128, 1, 1" offset="2974240" size="131072"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.resnets.0.conv_shortcut.weight"/>
- </rt_info>
+ <layer id="95" name="vae.encoder.down_blocks.1.resnets.0.conv_shortcut.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 128, 1, 1" offset="1487136" size="65536" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.resnets.0.conv_shortcut.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1435,11 +1744,30 @@
</port>
</output>
</layer>
- <layer id="74" name="Convolution_1301" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+ <layer id="96" name="vae.encoder.down_blocks.1.resnets.0.conv_shortcut.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1301"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.resnets.0.conv_shortcut.weight">
+ <dim>256</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="97" name="/encoder/down_blocks.1/resnets.0/conv_shortcut/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1463,10 +1791,10 @@
</port>
</output>
</layer>
- <layer id="75" name="Reshape_1321" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="3105312" size="1024"/>
+ <layer id="98" name="Reshape_118596_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="1552672" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -1474,11 +1802,30 @@
</port>
</output>
</layer>
- <layer id="76" name="onnx::Add_389" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="99" name="Reshape_118596" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1320, Reshape_1321, onnx::Add_389"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="100" name="/encoder/down_blocks.1/resnets.0/conv_shortcut/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1494,7 +1841,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_389">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/conv_shortcut/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -1502,22 +1849,16 @@
</port>
</output>
</layer>
- <layer id="77" name="onnx::Reshape_354" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_354"/>
- </rt_info>
+ <layer id="101" name="/encoder/down_blocks.1/resnets.0/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_354">
+ <port id="0" precision="I64" names="/encoder/down_blocks.1/resnets.0/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="78" name="onnx::InstanceNormalization_355" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_355"/>
- </rt_info>
+ <layer id="102" name="/encoder/down_blocks.1/resnets.0/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1530,29 +1871,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_355">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="79" name="Constant_983" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_983"/>
- </rt_info>
+ <layer id="103" name="Constant_118261" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="80" name="MVN_984" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_1003, Concat_1048, MVN_984, Multiply_1031, Reshape_1004, Reshape_1049, onnx::Reshape_358"/>
- </rt_info>
+ <layer id="104" name="MVN_118262" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1564,18 +1899,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_358">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="81" name="onnx::Reshape_359" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_359"/>
- </rt_info>
+ <layer id="105" name="/encoder/down_blocks.1/resnets.0/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1585,16 +1917,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_359">
+ <port id="1" precision="I64" names="/encoder/down_blocks.1/resnets.0/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="82" name="onnx::Mul_360" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_360"/>
- </rt_info>
+ <layer id="106" name="/encoder/down_blocks.1/resnets.0/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1606,7 +1935,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_360">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>256</dim>
@@ -1614,10 +1943,10 @@
</port>
</output>
</layer>
- <layer id="83" name="Constant_13453" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="3106336" size="512"/>
+ <layer id="107" name="Constant_155064_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="1553184" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1625,11 +1954,30 @@
</port>
</output>
</layer>
- <layer id="84" name="onnx::Add_363" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="108" name="Constant_155064" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_363"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="109" name="/encoder/down_blocks.1/resnets.0/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1645,7 +1993,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_363">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm1/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>256</dim>
@@ -1653,10 +2001,10 @@
</port>
</output>
</layer>
- <layer id="85" name="Constant_13454" type="Const" version="opset1">
- <data element_type="f32" shape="1, 128, 1, 1" offset="3106848" size="512"/>
+ <layer id="110" name="Constant_155065_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 128, 1, 1" offset="1553440" size="256" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1664,19 +2012,13 @@
</port>
</output>
</layer>
- <layer id="86" name="onnx::Cast_366" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="111" name="Constant_155065" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.56, onnx::Cast_366"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>128</dim>
- <dim>256</dim>
- <dim>256</dim>
- </port>
- <port id="1" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>128</dim>
<dim>1</dim>
@@ -1684,7 +2026,32 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.56,onnx::Cast_366">
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="112" name="/encoder/down_blocks.1/resnets.0/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>256</dim>
+ <dim>256</dim>
+ </port>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>128</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm1/Add_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>256</dim>
@@ -1692,10 +2059,7 @@
</port>
</output>
</layer>
- <layer id="87" name="input.60" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.60, onnx::Mul_368"/>
- </rt_info>
+ <layer id="113" name="/encoder/down_blocks.1/resnets.0/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1705,7 +2069,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.60">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.1/resnets.0/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>128</dim>
<dim>256</dim>
@@ -1713,13 +2077,10 @@
</port>
</output>
</layer>
- <layer id="88" name="m.encoder.down_blocks.1.resnets.0.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 128, 3, 3" offset="3107360" size="1179648"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.resnets.0.conv1.weight"/>
- </rt_info>
+ <layer id="114" name="vae.encoder.down_blocks.1.resnets.0.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 128, 3, 3" offset="1553696" size="589824" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.resnets.0.conv1.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>128</dim>
<dim>3</dim>
@@ -1727,11 +2088,30 @@
</port>
</output>
</layer>
- <layer id="89" name="Convolution_1089" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="115" name="vae.encoder.down_blocks.1.resnets.0.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1089"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.resnets.0.conv1.weight">
+ <dim>256</dim>
+ <dim>128</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="116" name="/encoder/down_blocks.1/resnets.0/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1755,10 +2135,10 @@
</port>
</output>
</layer>
- <layer id="90" name="Reshape_1109" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="4287008" size="1024"/>
+ <layer id="117" name="Reshape_118386_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="2143520" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -1766,11 +2146,30 @@
</port>
</output>
</layer>
- <layer id="91" name="onnx::Cast_370" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="118" name="Reshape_118386" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1108, Reshape_1109, input.64, onnx::Cast_370"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="119" name="/encoder/down_blocks.1/resnets.0/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1786,7 +2185,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.64,onnx::Cast_370">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/conv1/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -1794,22 +2193,16 @@
</port>
</output>
</layer>
- <layer id="92" name="onnx::Reshape_372" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_372"/>
- </rt_info>
+ <layer id="120" name="/encoder/down_blocks.1/resnets.0/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_372">
+ <port id="0" precision="I64" names="/encoder/down_blocks.1/resnets.0/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="93" name="onnx::InstanceNormalization_373" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_373"/>
- </rt_info>
+ <layer id="121" name="/encoder/down_blocks.1/resnets.0/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1822,29 +2215,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_373">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="94" name="Constant_1147" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_1147"/>
- </rt_info>
+ <layer id="122" name="Constant_118423" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="95" name="MVN_1148" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_1167, Concat_1212, MVN_1148, Multiply_1195, Reshape_1168, Reshape_1213, onnx::Reshape_376"/>
- </rt_info>
+ <layer id="123" name="MVN_118424" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1856,18 +2243,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_376">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="96" name="onnx::Reshape_377" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_377"/>
- </rt_info>
+ <layer id="124" name="/encoder/down_blocks.1/resnets.0/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1877,16 +2261,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_377">
+ <port id="1" precision="I64" names="/encoder/down_blocks.1/resnets.0/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="97" name="onnx::Mul_378" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_378"/>
- </rt_info>
+ <layer id="125" name="/encoder/down_blocks.1/resnets.0/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1898,7 +2279,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_378">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -1906,10 +2287,10 @@
</port>
</output>
</layer>
- <layer id="98" name="Constant_13455" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="4288032" size="1024"/>
+ <layer id="126" name="Constant_155066_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="2144032" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -1917,11 +2298,30 @@
</port>
</output>
</layer>
- <layer id="99" name="onnx::Add_381" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="127" name="Constant_155066" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_381"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="128" name="/encoder/down_blocks.1/resnets.0/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1937,7 +2337,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_381">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm2/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -1945,10 +2345,10 @@
</port>
</output>
</layer>
- <layer id="100" name="Constant_13456" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="4289056" size="1024"/>
+ <layer id="129" name="Constant_155067_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="2144544" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -1956,11 +2356,30 @@
</port>
</output>
</layer>
- <layer id="101" name="onnx::Cast_384" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="130" name="Constant_155067" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.68, onnx::Cast_384"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="131" name="/encoder/down_blocks.1/resnets.0/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1976,7 +2395,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.68,onnx::Cast_384">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/norm2/Add_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -1984,10 +2403,7 @@
</port>
</output>
</layer>
- <layer id="102" name="input.72" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.72, onnx::Mul_386"/>
- </rt_info>
+ <layer id="132" name="/encoder/down_blocks.1/resnets.0/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -1997,7 +2413,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.72">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.1/resnets.0/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2005,13 +2421,10 @@
</port>
</output>
</layer>
- <layer id="103" name="m.encoder.down_blocks.1.resnets.0.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 256, 3, 3" offset="4290080" size="2359296"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.resnets.0.conv2.weight"/>
- </rt_info>
+ <layer id="133" name="vae.encoder.down_blocks.1.resnets.0.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 256, 3, 3" offset="2145056" size="1179648" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.resnets.0.conv2.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>256</dim>
<dim>3</dim>
@@ -2019,11 +2432,30 @@
</port>
</output>
</layer>
- <layer id="104" name="Convolution_1253" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="134" name="vae.encoder.down_blocks.1.resnets.0.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1253"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.resnets.0.conv2.weight">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="135" name="/encoder/down_blocks.1/resnets.0/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2047,10 +2479,10 @@
</port>
</output>
</layer>
- <layer id="105" name="Reshape_1273" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="6649376" size="1024"/>
+ <layer id="136" name="Reshape_118548_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="3324704" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2058,11 +2490,30 @@
</port>
</output>
</layer>
- <layer id="106" name="onnx::Add_388" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="137" name="Reshape_118548" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1272, Reshape_1273, onnx::Add_388"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="138" name="/encoder/down_blocks.1/resnets.0/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2078,7 +2529,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_388">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/conv2/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2086,11 +2537,8 @@
</port>
</output>
</layer>
- <layer id="107" name="onnx::Div_390" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.76, onnx::Cast_392, onnx::Div_390"/>
- </rt_info>
+ <layer id="139" name="/encoder/down_blocks.1/resnets.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2106,7 +2554,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.76,onnx::Cast_392,onnx::Div_390">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.0/Add_output_0,/encoder/down_blocks.1/resnets.0/Div_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2114,22 +2562,16 @@
</port>
</output>
</layer>
- <layer id="108" name="onnx::Reshape_394" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_394"/>
- </rt_info>
+ <layer id="140" name="/encoder/down_blocks.1/resnets.1/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_394">
+ <port id="0" precision="I64" names="/encoder/down_blocks.1/resnets.1/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="109" name="onnx::InstanceNormalization_395" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_395"/>
- </rt_info>
+ <layer id="141" name="/encoder/down_blocks.1/resnets.1/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2142,29 +2584,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_395">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="110" name="Constant_1362" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_1362"/>
- </rt_info>
+ <layer id="142" name="Constant_118636" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="111" name="MVN_1363" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_1382, Concat_1427, MVN_1363, Multiply_1410, Reshape_1383, Reshape_1428, onnx::Reshape_398"/>
- </rt_info>
+ <layer id="143" name="MVN_118637" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2176,18 +2612,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_398">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="112" name="onnx::Reshape_399" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_399"/>
- </rt_info>
+ <layer id="144" name="/encoder/down_blocks.1/resnets.1/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2197,16 +2630,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_399">
+ <port id="1" precision="I64" names="/encoder/down_blocks.1/resnets.1/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="113" name="onnx::Mul_400" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_400"/>
- </rt_info>
+ <layer id="145" name="/encoder/down_blocks.1/resnets.1/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2218,7 +2648,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_400">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2226,10 +2656,10 @@
</port>
</output>
</layer>
- <layer id="114" name="Constant_13457" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="6650400" size="1024"/>
+ <layer id="146" name="Constant_155068_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="3325216" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2237,11 +2667,30 @@
</port>
</output>
</layer>
- <layer id="115" name="onnx::Add_403" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="147" name="Constant_155068" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_403"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="148" name="/encoder/down_blocks.1/resnets.1/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2257,7 +2706,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_403">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm1/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2265,10 +2714,10 @@
</port>
</output>
</layer>
- <layer id="116" name="Constant_13458" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="6651424" size="1024"/>
+ <layer id="149" name="Constant_155069_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="3325728" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2276,11 +2725,30 @@
</port>
</output>
</layer>
- <layer id="117" name="onnx::Cast_406" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="150" name="Constant_155069" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.80, onnx::Cast_406"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="151" name="/encoder/down_blocks.1/resnets.1/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2296,7 +2764,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.80,onnx::Cast_406">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm1/Add_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2304,10 +2772,7 @@
</port>
</output>
</layer>
- <layer id="118" name="input.84" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.84, onnx::Mul_408"/>
- </rt_info>
+ <layer id="152" name="/encoder/down_blocks.1/resnets.1/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2317,7 +2782,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.84">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.1/resnets.1/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2325,13 +2790,10 @@
</port>
</output>
</layer>
- <layer id="119" name="m.encoder.down_blocks.1.resnets.1.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 256, 3, 3" offset="6652448" size="2359296"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.resnets.1.conv1.weight"/>
- </rt_info>
+ <layer id="153" name="vae.encoder.down_blocks.1.resnets.1.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 256, 3, 3" offset="3326240" size="1179648" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.resnets.1.conv1.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>256</dim>
<dim>3</dim>
@@ -2339,11 +2801,30 @@
</port>
</output>
</layer>
- <layer id="120" name="Convolution_1468" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="154" name="vae.encoder.down_blocks.1.resnets.1.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1468"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.resnets.1.conv1.weight">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="155" name="/encoder/down_blocks.1/resnets.1/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2367,10 +2848,10 @@
</port>
</output>
</layer>
- <layer id="121" name="Reshape_1488" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="9011744" size="1024"/>
+ <layer id="156" name="Reshape_118761_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="4505888" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2378,11 +2859,30 @@
</port>
</output>
</layer>
- <layer id="122" name="onnx::Cast_410" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="157" name="Reshape_118761" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1487, Reshape_1488, input.88, onnx::Cast_410"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="158" name="/encoder/down_blocks.1/resnets.1/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2398,7 +2898,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.88,onnx::Cast_410">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/conv1/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2406,22 +2906,16 @@
</port>
</output>
</layer>
- <layer id="123" name="onnx::Reshape_412" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_412"/>
- </rt_info>
+ <layer id="159" name="/encoder/down_blocks.1/resnets.1/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_412">
+ <port id="0" precision="I64" names="/encoder/down_blocks.1/resnets.1/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="124" name="onnx::InstanceNormalization_413" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_413"/>
- </rt_info>
+ <layer id="160" name="/encoder/down_blocks.1/resnets.1/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2434,29 +2928,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_413">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="125" name="Constant_1526" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_1526"/>
- </rt_info>
+ <layer id="161" name="Constant_118798" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="126" name="MVN_1527" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_1546, Concat_1591, MVN_1527, Multiply_1574, Reshape_1547, Reshape_1592, onnx::Reshape_416"/>
- </rt_info>
+ <layer id="162" name="MVN_118799" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2468,18 +2956,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_416">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>524288</dim>
</port>
</output>
</layer>
- <layer id="127" name="onnx::Reshape_417" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_417"/>
- </rt_info>
+ <layer id="163" name="/encoder/down_blocks.1/resnets.1/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2489,16 +2974,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_417">
+ <port id="1" precision="I64" names="/encoder/down_blocks.1/resnets.1/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="128" name="onnx::Mul_418" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_418"/>
- </rt_info>
+ <layer id="164" name="/encoder/down_blocks.1/resnets.1/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2510,7 +2992,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_418">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2518,10 +3000,10 @@
</port>
</output>
</layer>
- <layer id="129" name="Constant_13459" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="9012768" size="1024"/>
+ <layer id="165" name="Constant_155070_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="4506400" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2529,19 +3011,13 @@
</port>
</output>
</layer>
- <layer id="130" name="onnx::Add_421" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="166" name="Constant_155070" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_421"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>256</dim>
- <dim>256</dim>
- <dim>256</dim>
- </port>
- <port id="1" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2549,18 +3025,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_421">
- <dim>1</dim>
- <dim>256</dim>
- <dim>256</dim>
- <dim>256</dim>
- </port>
- </output>
- </layer>
- <layer id="131" name="Constant_13460" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="9013792" size="1024"/>
- <output>
- <port id="0" precision="FP32">
+ <port id="1" precision="FP32">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2568,11 +3033,8 @@
</port>
</output>
</layer>
- <layer id="132" name="onnx::Cast_424" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.92, onnx::Cast_424"/>
- </rt_info>
+ <layer id="167" name="/encoder/down_blocks.1/resnets.1/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2588,7 +3050,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.92,onnx::Cast_424">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm2/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2596,10 +3058,41 @@
</port>
</output>
</layer>
- <layer id="133" name="input.96" type="Swish" version="opset4">
+ <layer id="168" name="Constant_155071_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="4506912" size="512" />
+ <output>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="169" name="Constant_155071" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.96, onnx::Mul_426"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="170" name="/encoder/down_blocks.1/resnets.1/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2607,9 +3100,15 @@
<dim>256</dim>
<dim>256</dim>
</port>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
</input>
<output>
- <port id="1" precision="FP32" names="input.96">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/norm2/Add_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2617,13 +3116,28 @@
</port>
</output>
</layer>
- <layer id="134" name="m.encoder.down_blocks.1.resnets.1.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 256, 3, 3" offset="9014816" size="2359296"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.resnets.1.conv2.weight"/>
- </rt_info>
+ <layer id="171" name="/encoder/down_blocks.1/resnets.1/nonlinearity_1/Mul" type="Swish" version="opset4">
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>256</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="/encoder/down_blocks.1/resnets.1/nonlinearity_1/Mul_output_0">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>256</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="172" name="vae.encoder.down_blocks.1.resnets.1.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 256, 3, 3" offset="4507424" size="1179648" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.resnets.1.conv2.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>256</dim>
<dim>3</dim>
@@ -2631,11 +3145,30 @@
</port>
</output>
</layer>
- <layer id="135" name="Convolution_1632" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="173" name="vae.encoder.down_blocks.1.resnets.1.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1632"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.resnets.1.conv2.weight">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="174" name="/encoder/down_blocks.1/resnets.1/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2659,10 +3192,10 @@
</port>
</output>
</layer>
- <layer id="136" name="Reshape_1652" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="11374112" size="1024"/>
+ <layer id="175" name="Reshape_118923_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="5687072" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2670,11 +3203,30 @@
</port>
</output>
</layer>
- <layer id="137" name="onnx::Add_428" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="176" name="Reshape_118923" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1651, Reshape_1652, onnx::Add_428"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="177" name="/encoder/down_blocks.1/resnets.1/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2690,7 +3242,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_428">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/conv2/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2698,11 +3250,8 @@
</port>
</output>
</layer>
- <layer id="138" name="onnx::Div_429" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Div_429, onnx::Pad_431"/>
- </rt_info>
+ <layer id="178" name="/encoder/down_blocks.1/resnets.1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2718,7 +3267,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Div_429,onnx::Pad_431">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/resnets.1/Add_output_0,/encoder/down_blocks.1/resnets.1/Div_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>256</dim>
@@ -2726,13 +3275,10 @@
</port>
</output>
</layer>
- <layer id="139" name="m.encoder.down_blocks.1.downsamplers.0.conv.weight" type="Const" version="opset1">
- <data element_type="f32" shape="256, 256, 3, 3" offset="11375136" size="2359296"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.1.downsamplers.0.conv.weight"/>
- </rt_info>
+ <layer id="179" name="vae.encoder.down_blocks.1.downsamplers.0.conv.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="256, 256, 3, 3" offset="5687584" size="1179648" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.1.downsamplers.0.conv.weight">
+ <port id="0" precision="FP16">
<dim>256</dim>
<dim>256</dim>
<dim>3</dim>
@@ -2740,11 +3286,30 @@
</port>
</output>
</layer>
- <layer id="140" name="Convolution_1781" type="Convolution" version="opset1">
- <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="180" name="vae.encoder.down_blocks.1.downsamplers.0.conv.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1781, Split_1713, input.100"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.1.downsamplers.0.conv.weight">
+ <dim>256</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="181" name="/encoder/down_blocks.1/downsamplers.0/conv/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2768,10 +3333,10 @@
</port>
</output>
</layer>
- <layer id="141" name="Reshape_1801" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="13734432" size="1024"/>
+ <layer id="182" name="Reshape_119078_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="6867232" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2779,11 +3344,30 @@
</port>
</output>
</layer>
- <layer id="142" name="onnx::Cast_456" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="183" name="Reshape_119078" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1800, Reshape_1801, input.104, onnx::Cast_456"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="184" name="/encoder/down_blocks.1/downsamplers.0/conv/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2799,7 +3383,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.104,onnx::Cast_456">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.1/downsamplers.0/conv/Conv_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>128</dim>
@@ -2807,13 +3391,10 @@
</port>
</output>
</layer>
- <layer id="143" name="m.encoder.down_blocks.2.resnets.0.conv_shortcut.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 256, 1, 1" offset="13735456" size="524288"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.resnets.0.conv_shortcut.weight"/>
- </rt_info>
+ <layer id="185" name="vae.encoder.down_blocks.2.resnets.0.conv_shortcut.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 256, 1, 1" offset="6867744" size="262144" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.resnets.0.conv_shortcut.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>256</dim>
<dim>1</dim>
@@ -2821,11 +3402,30 @@
</port>
</output>
</layer>
- <layer id="144" name="Convolution_2157" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+ <layer id="186" name="vae.encoder.down_blocks.2.resnets.0.conv_shortcut.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2157"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.resnets.0.conv_shortcut.weight">
+ <dim>512</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="187" name="/encoder/down_blocks.2/resnets.0/conv_shortcut/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2849,10 +3449,10 @@
</port>
</output>
</layer>
- <layer id="145" name="Reshape_2177" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="14259744" size="2048"/>
+ <layer id="188" name="Reshape_119450_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="7129888" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -2860,11 +3460,30 @@
</port>
</output>
</layer>
- <layer id="146" name="onnx::Add_493" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="189" name="Reshape_119450" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2176, Reshape_2177, onnx::Add_493"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="190" name="/encoder/down_blocks.2/resnets.0/conv_shortcut/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2880,7 +3499,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_493">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/conv_shortcut/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -2888,22 +3507,16 @@
</port>
</output>
</layer>
- <layer id="147" name="onnx::Reshape_458" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_458"/>
- </rt_info>
+ <layer id="191" name="/encoder/down_blocks.2/resnets.0/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_458">
+ <port id="0" precision="I64" names="/encoder/down_blocks.2/resnets.0/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="148" name="onnx::InstanceNormalization_459" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_459"/>
- </rt_info>
+ <layer id="192" name="/encoder/down_blocks.2/resnets.0/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2916,29 +3529,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_459">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>131072</dim>
</port>
</output>
</layer>
- <layer id="149" name="Constant_1839" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_1839"/>
- </rt_info>
+ <layer id="193" name="Constant_119115" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="150" name="MVN_1840" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_1859, Concat_1904, MVN_1840, Multiply_1887, Reshape_1860, Reshape_1905, onnx::Reshape_462"/>
- </rt_info>
+ <layer id="194" name="MVN_119116" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2950,18 +3557,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_462">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>131072</dim>
</port>
</output>
</layer>
- <layer id="151" name="onnx::Reshape_463" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_463"/>
- </rt_info>
+ <layer id="195" name="/encoder/down_blocks.2/resnets.0/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2971,16 +3575,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_463">
+ <port id="1" precision="I64" names="/encoder/down_blocks.2/resnets.0/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="152" name="onnx::Mul_464" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_464"/>
- </rt_info>
+ <layer id="196" name="/encoder/down_blocks.2/resnets.0/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -2992,7 +3593,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_464">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>128</dim>
@@ -3000,10 +3601,10 @@
</port>
</output>
</layer>
- <layer id="153" name="Constant_13461" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="14261792" size="1024"/>
+ <layer id="197" name="Constant_155072_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="7130912" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -3011,11 +3612,30 @@
</port>
</output>
</layer>
- <layer id="154" name="onnx::Add_467" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="198" name="Constant_155072" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_467"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="199" name="/encoder/down_blocks.2/resnets.0/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3031,7 +3651,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_467">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm1/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>128</dim>
@@ -3039,10 +3659,10 @@
</port>
</output>
</layer>
- <layer id="155" name="Constant_13462" type="Const" version="opset1">
- <data element_type="f32" shape="1, 256, 1, 1" offset="14262816" size="1024"/>
+ <layer id="200" name="Constant_155073_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 256, 1, 1" offset="7131424" size="512" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>256</dim>
<dim>1</dim>
@@ -3050,11 +3670,30 @@
</port>
</output>
</layer>
- <layer id="156" name="onnx::Cast_470" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="201" name="Constant_155073" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.108, onnx::Cast_470"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>256</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="202" name="/encoder/down_blocks.2/resnets.0/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3070,7 +3709,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.108,onnx::Cast_470">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm1/Add_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>128</dim>
@@ -3078,10 +3717,7 @@
</port>
</output>
</layer>
- <layer id="157" name="input.112" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.112, onnx::Mul_472"/>
- </rt_info>
+ <layer id="203" name="/encoder/down_blocks.2/resnets.0/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3091,7 +3727,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.112">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.2/resnets.0/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>256</dim>
<dim>128</dim>
@@ -3099,13 +3735,10 @@
</port>
</output>
</layer>
- <layer id="158" name="m.encoder.down_blocks.2.resnets.0.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 256, 3, 3" offset="14263840" size="4718592"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.resnets.0.conv1.weight"/>
- </rt_info>
+ <layer id="204" name="vae.encoder.down_blocks.2.resnets.0.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 256, 3, 3" offset="7131936" size="2359296" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.resnets.0.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>256</dim>
<dim>3</dim>
@@ -3113,11 +3746,30 @@
</port>
</output>
</layer>
- <layer id="159" name="Convolution_1945" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="205" name="vae.encoder.down_blocks.2.resnets.0.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_1945"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.resnets.0.conv1.weight">
+ <dim>512</dim>
+ <dim>256</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="206" name="/encoder/down_blocks.2/resnets.0/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3141,10 +3793,10 @@
</port>
</output>
</layer>
- <layer id="160" name="Reshape_1965" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="18982432" size="2048"/>
+ <layer id="207" name="Reshape_119240_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="9491232" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3152,11 +3804,30 @@
</port>
</output>
</layer>
- <layer id="161" name="onnx::Cast_474" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="208" name="Reshape_119240" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_1964, Reshape_1965, input.116, onnx::Cast_474"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="209" name="/encoder/down_blocks.2/resnets.0/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3172,7 +3843,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.116,onnx::Cast_474">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3180,22 +3851,16 @@
</port>
</output>
</layer>
- <layer id="162" name="onnx::Reshape_476" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_476"/>
- </rt_info>
+ <layer id="210" name="/encoder/down_blocks.2/resnets.0/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_476">
+ <port id="0" precision="I64" names="/encoder/down_blocks.2/resnets.0/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="163" name="onnx::InstanceNormalization_477" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_477"/>
- </rt_info>
+ <layer id="211" name="/encoder/down_blocks.2/resnets.0/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3208,29 +3873,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_477">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="164" name="Constant_2003" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_2003"/>
- </rt_info>
+ <layer id="212" name="Constant_119277" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="165" name="MVN_2004" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_2023, Concat_2068, MVN_2004, Multiply_2051, Reshape_2024, Reshape_2069, onnx::Reshape_480"/>
- </rt_info>
+ <layer id="213" name="MVN_119278" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3242,18 +3901,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_480">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="166" name="onnx::Reshape_481" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_481"/>
- </rt_info>
+ <layer id="214" name="/encoder/down_blocks.2/resnets.0/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3263,16 +3919,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_481">
+ <port id="1" precision="I64" names="/encoder/down_blocks.2/resnets.0/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="167" name="onnx::Mul_482" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_482"/>
- </rt_info>
+ <layer id="215" name="/encoder/down_blocks.2/resnets.0/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3284,7 +3937,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_482">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3292,10 +3945,10 @@
</port>
</output>
</layer>
- <layer id="168" name="Constant_13463" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="18984480" size="2048"/>
+ <layer id="216" name="Constant_155074_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="9492256" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3303,19 +3956,13 @@
</port>
</output>
</layer>
- <layer id="169" name="onnx::Add_485" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="217" name="Constant_155074" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_485"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>512</dim>
- <dim>128</dim>
- <dim>128</dim>
- </port>
- <port id="1" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3323,18 +3970,43 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_485">
+ <port id="1" precision="FP32">
<dim>1</dim>
<dim>512</dim>
- <dim>128</dim>
- <dim>128</dim>
- </port>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
</output>
</layer>
- <layer id="170" name="Constant_13464" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="18986528" size="2048"/>
- <output>
+ <layer id="218" name="/encoder/down_blocks.2/resnets.0/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
+ <input>
<port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>128</dim>
+ <dim>128</dim>
+ </port>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm2/Mul_output_0">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>128</dim>
+ <dim>128</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="219" name="Constant_155075_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="9493280" size="1024" />
+ <output>
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3342,11 +4014,30 @@
</port>
</output>
</layer>
- <layer id="171" name="onnx::Cast_488" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="220" name="Constant_155075" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.120, onnx::Cast_488"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="221" name="/encoder/down_blocks.2/resnets.0/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3362,7 +4053,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.120,onnx::Cast_488">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3370,10 +4061,7 @@
</port>
</output>
</layer>
- <layer id="172" name="input.124" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.124, onnx::Mul_490"/>
- </rt_info>
+ <layer id="222" name="/encoder/down_blocks.2/resnets.0/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3383,7 +4071,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.124">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.2/resnets.0/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3391,13 +4079,10 @@
</port>
</output>
</layer>
- <layer id="173" name="m.encoder.down_blocks.2.resnets.0.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="18988576" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.resnets.0.conv2.weight"/>
- </rt_info>
+ <layer id="223" name="vae.encoder.down_blocks.2.resnets.0.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="9494304" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.resnets.0.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -3405,11 +4090,30 @@
</port>
</output>
</layer>
- <layer id="174" name="Convolution_2109" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="224" name="vae.encoder.down_blocks.2.resnets.0.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2109"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.resnets.0.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="225" name="/encoder/down_blocks.2/resnets.0/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3433,10 +4137,10 @@
</port>
</output>
</layer>
- <layer id="175" name="Reshape_2129" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="28425760" size="2048"/>
+ <layer id="226" name="Reshape_119402_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="14212896" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3444,11 +4148,30 @@
</port>
</output>
</layer>
- <layer id="176" name="onnx::Add_492" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="227" name="Reshape_119402" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2128, Reshape_2129, onnx::Add_492"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="228" name="/encoder/down_blocks.2/resnets.0/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3464,7 +4187,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_492">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3472,11 +4195,8 @@
</port>
</output>
</layer>
- <layer id="177" name="onnx::Div_494" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.128, onnx::Cast_496, onnx::Div_494"/>
- </rt_info>
+ <layer id="229" name="/encoder/down_blocks.2/resnets.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3492,7 +4212,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.128,onnx::Cast_496,onnx::Div_494">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.0/Add_output_0,/encoder/down_blocks.2/resnets.0/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3500,22 +4220,16 @@
</port>
</output>
</layer>
- <layer id="178" name="onnx::Reshape_498" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_498"/>
- </rt_info>
+ <layer id="230" name="/encoder/down_blocks.2/resnets.1/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_498">
+ <port id="0" precision="I64" names="/encoder/down_blocks.2/resnets.1/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="179" name="onnx::InstanceNormalization_499" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_499"/>
- </rt_info>
+ <layer id="231" name="/encoder/down_blocks.2/resnets.1/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3528,29 +4242,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_499">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="180" name="Constant_2218" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_2218"/>
- </rt_info>
+ <layer id="232" name="Constant_119490" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="181" name="MVN_2219" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_2238, Concat_2283, MVN_2219, Multiply_2266, Reshape_2239, Reshape_2284, onnx::Reshape_502"/>
- </rt_info>
+ <layer id="233" name="MVN_119491" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3562,18 +4270,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_502">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="182" name="onnx::Reshape_503" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_503"/>
- </rt_info>
+ <layer id="234" name="/encoder/down_blocks.2/resnets.1/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3583,16 +4288,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_503">
+ <port id="1" precision="I64" names="/encoder/down_blocks.2/resnets.1/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="183" name="onnx::Mul_504" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_504"/>
- </rt_info>
+ <layer id="235" name="/encoder/down_blocks.2/resnets.1/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3604,7 +4306,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_504">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3612,10 +4314,10 @@
</port>
</output>
</layer>
- <layer id="184" name="Constant_13465" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="28427808" size="2048"/>
+ <layer id="236" name="Constant_155076_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="14213920" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3623,11 +4325,30 @@
</port>
</output>
</layer>
- <layer id="185" name="onnx::Add_507" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="237" name="Constant_155076" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_507"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="238" name="/encoder/down_blocks.2/resnets.1/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3643,7 +4364,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_507">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3651,10 +4372,10 @@
</port>
</output>
</layer>
- <layer id="186" name="Constant_13466" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="28429856" size="2048"/>
+ <layer id="239" name="Constant_155077_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="14214944" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3662,11 +4383,30 @@
</port>
</output>
</layer>
- <layer id="187" name="onnx::Cast_510" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="240" name="Constant_155077" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.132, onnx::Cast_510"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="241" name="/encoder/down_blocks.2/resnets.1/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3682,7 +4422,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.132,onnx::Cast_510">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm1/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3690,10 +4430,7 @@
</port>
</output>
</layer>
- <layer id="188" name="input.136" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.136, onnx::Mul_512"/>
- </rt_info>
+ <layer id="242" name="/encoder/down_blocks.2/resnets.1/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3703,7 +4440,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.136">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.2/resnets.1/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3711,13 +4448,10 @@
</port>
</output>
</layer>
- <layer id="189" name="m.encoder.down_blocks.2.resnets.1.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="28431904" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.resnets.1.conv1.weight"/>
- </rt_info>
+ <layer id="243" name="vae.encoder.down_blocks.2.resnets.1.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="14215968" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.resnets.1.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -3725,11 +4459,30 @@
</port>
</output>
</layer>
- <layer id="190" name="Convolution_2324" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="244" name="vae.encoder.down_blocks.2.resnets.1.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2324"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.resnets.1.conv1.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="245" name="/encoder/down_blocks.2/resnets.1/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3753,10 +4506,10 @@
</port>
</output>
</layer>
- <layer id="191" name="Reshape_2344" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="37869088" size="2048"/>
+ <layer id="246" name="Reshape_119615_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="18934560" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3764,11 +4517,30 @@
</port>
</output>
</layer>
- <layer id="192" name="onnx::Cast_514" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="247" name="Reshape_119615" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2343, Reshape_2344, input.140, onnx::Cast_514"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="248" name="/encoder/down_blocks.2/resnets.1/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3784,7 +4556,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.140,onnx::Cast_514">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3792,22 +4564,16 @@
</port>
</output>
</layer>
- <layer id="193" name="onnx::Reshape_516" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_516"/>
- </rt_info>
+ <layer id="249" name="/encoder/down_blocks.2/resnets.1/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_516">
+ <port id="0" precision="I64" names="/encoder/down_blocks.2/resnets.1/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="194" name="onnx::InstanceNormalization_517" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_517"/>
- </rt_info>
+ <layer id="250" name="/encoder/down_blocks.2/resnets.1/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3820,29 +4586,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_517">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="195" name="Constant_2382" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_2382"/>
- </rt_info>
+ <layer id="251" name="Constant_119652" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="196" name="MVN_2383" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_2402, Concat_2447, MVN_2383, Multiply_2430, Reshape_2403, Reshape_2448, onnx::Reshape_520"/>
- </rt_info>
+ <layer id="252" name="MVN_119653" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3854,18 +4614,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_520">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>262144</dim>
</port>
</output>
</layer>
- <layer id="197" name="onnx::Reshape_521" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_521"/>
- </rt_info>
+ <layer id="253" name="/encoder/down_blocks.2/resnets.1/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3875,16 +4632,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_521">
+ <port id="1" precision="I64" names="/encoder/down_blocks.2/resnets.1/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="198" name="onnx::Mul_522" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_522"/>
- </rt_info>
+ <layer id="254" name="/encoder/down_blocks.2/resnets.1/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3896,7 +4650,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_522">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3904,10 +4658,10 @@
</port>
</output>
</layer>
- <layer id="199" name="Constant_13467" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="37871136" size="2048"/>
+ <layer id="255" name="Constant_155078_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="18935584" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3915,11 +4669,30 @@
</port>
</output>
</layer>
- <layer id="200" name="onnx::Add_525" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="256" name="Constant_155078" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_525"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="257" name="/encoder/down_blocks.2/resnets.1/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3935,7 +4708,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_525">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm2/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3943,10 +4716,10 @@
</port>
</output>
</layer>
- <layer id="201" name="Constant_13468" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="37873184" size="2048"/>
+ <layer id="258" name="Constant_155079_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="18936608" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -3954,11 +4727,30 @@
</port>
</output>
</layer>
- <layer id="202" name="onnx::Cast_528" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="259" name="Constant_155079" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.144, onnx::Cast_528"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="260" name="/encoder/down_blocks.2/resnets.1/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3974,7 +4766,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.144,onnx::Cast_528">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -3982,10 +4774,7 @@
</port>
</output>
</layer>
- <layer id="203" name="input.148" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.148, onnx::Mul_530"/>
- </rt_info>
+ <layer id="261" name="/encoder/down_blocks.2/resnets.1/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -3995,7 +4784,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.148">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.2/resnets.1/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -4003,13 +4792,10 @@
</port>
</output>
</layer>
- <layer id="204" name="m.encoder.down_blocks.2.resnets.1.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="37875232" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.resnets.1.conv2.weight"/>
- </rt_info>
+ <layer id="262" name="vae.encoder.down_blocks.2.resnets.1.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="18937632" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.resnets.1.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -4017,11 +4803,30 @@
</port>
</output>
</layer>
- <layer id="205" name="Convolution_2488" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="263" name="vae.encoder.down_blocks.2.resnets.1.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2488"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.resnets.1.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="264" name="/encoder/down_blocks.2/resnets.1/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4045,10 +4850,10 @@
</port>
</output>
</layer>
- <layer id="206" name="Reshape_2508" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="47312416" size="2048"/>
+ <layer id="265" name="Reshape_119777_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="23656224" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4056,11 +4861,30 @@
</port>
</output>
</layer>
- <layer id="207" name="onnx::Add_532" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="266" name="Reshape_119777" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2507, Reshape_2508, onnx::Add_532"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="267" name="/encoder/down_blocks.2/resnets.1/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4076,7 +4900,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_532">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -4084,11 +4908,8 @@
</port>
</output>
</layer>
- <layer id="208" name="onnx::Div_533" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Div_533, onnx::Pad_535"/>
- </rt_info>
+ <layer id="268" name="/encoder/down_blocks.2/resnets.1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4104,7 +4925,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Div_533,onnx::Pad_535">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/resnets.1/Add_output_0,/encoder/down_blocks.2/resnets.1/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>128</dim>
@@ -4112,13 +4933,10 @@
</port>
</output>
</layer>
- <layer id="209" name="m.encoder.down_blocks.2.downsamplers.0.conv.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="47314464" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.2.downsamplers.0.conv.weight"/>
- </rt_info>
+ <layer id="269" name="vae.encoder.down_blocks.2.downsamplers.0.conv.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="23657248" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.2.downsamplers.0.conv.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -4126,19 +4944,13 @@
</port>
</output>
</layer>
- <layer id="210" name="Convolution_2637" type="Convolution" version="opset1">
- <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="270" name="vae.encoder.down_blocks.2.downsamplers.0.conv.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2637, Split_2569, input.152"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>512</dim>
- <dim>128</dim>
- <dim>128</dim>
- </port>
- <port id="1" precision="FP32">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -4146,7 +4958,32 @@
</port>
</input>
<output>
- <port id="2" precision="FP32">
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.2.downsamplers.0.conv.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="271" name="/encoder/down_blocks.2/downsamplers.0/conv/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>128</dim>
+ <dim>128</dim>
+ </port>
+ <port id="1" precision="FP32">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4154,10 +4991,10 @@
</port>
</output>
</layer>
- <layer id="211" name="Reshape_2657" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="56751648" size="2048"/>
+ <layer id="272" name="Reshape_119932_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="28375840" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4165,11 +5002,30 @@
</port>
</output>
</layer>
- <layer id="212" name="onnx::Cast_560" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="273" name="Reshape_119932" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2656, Reshape_2657, input.156, onnx::Cast_560"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="274" name="/encoder/down_blocks.2/downsamplers.0/conv/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4185,7 +5041,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.156,onnx::Cast_560">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.2/downsamplers.0/conv/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4193,22 +5049,16 @@
</port>
</output>
</layer>
- <layer id="213" name="onnx::Reshape_562" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_562"/>
- </rt_info>
+ <layer id="275" name="/encoder/down_blocks.3/resnets.0/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_562">
+ <port id="0" precision="I64" names="/encoder/down_blocks.3/resnets.0/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="214" name="onnx::InstanceNormalization_563" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_563"/>
- </rt_info>
+ <layer id="276" name="/encoder/down_blocks.3/resnets.0/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4221,29 +5071,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_563">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="215" name="Constant_2695" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_2695"/>
- </rt_info>
+ <layer id="277" name="Constant_119969" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="216" name="MVN_2696" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_2715, Concat_2760, MVN_2696, Multiply_2743, Reshape_2716, Reshape_2761, onnx::Reshape_566"/>
- </rt_info>
+ <layer id="278" name="MVN_119970" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4255,18 +5099,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_566">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="217" name="onnx::Reshape_567" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_567"/>
- </rt_info>
+ <layer id="279" name="/encoder/down_blocks.3/resnets.0/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4276,16 +5117,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_567">
+ <port id="1" precision="I64" names="/encoder/down_blocks.3/resnets.0/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="218" name="onnx::Mul_568" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_568"/>
- </rt_info>
+ <layer id="280" name="/encoder/down_blocks.3/resnets.0/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4297,7 +5135,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_568">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4305,10 +5143,10 @@
</port>
</output>
</layer>
- <layer id="219" name="Constant_13469" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="56753696" size="2048"/>
+ <layer id="281" name="Constant_155080_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="28376864" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4316,11 +5154,30 @@
</port>
</output>
</layer>
- <layer id="220" name="onnx::Add_571" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="282" name="Constant_155080" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_571"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="283" name="/encoder/down_blocks.3/resnets.0/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4336,7 +5193,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_571">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4344,10 +5201,10 @@
</port>
</output>
</layer>
- <layer id="221" name="Constant_13470" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="56755744" size="2048"/>
+ <layer id="284" name="Constant_155081_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="28377888" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4355,11 +5212,30 @@
</port>
</output>
</layer>
- <layer id="222" name="onnx::Cast_574" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="285" name="Constant_155081" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.160, onnx::Cast_574"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="286" name="/encoder/down_blocks.3/resnets.0/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4375,7 +5251,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.160,onnx::Cast_574">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm1/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4383,10 +5259,7 @@
</port>
</output>
</layer>
- <layer id="223" name="input.164" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.164, onnx::Mul_576"/>
- </rt_info>
+ <layer id="287" name="/encoder/down_blocks.3/resnets.0/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4396,7 +5269,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.164">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.3/resnets.0/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4404,13 +5277,10 @@
</port>
</output>
</layer>
- <layer id="224" name="m.encoder.down_blocks.3.resnets.0.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="56757792" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.3.resnets.0.conv1.weight"/>
- </rt_info>
+ <layer id="288" name="vae.encoder.down_blocks.3.resnets.0.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="28378912" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.3.resnets.0.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -4418,11 +5288,30 @@
</port>
</output>
</layer>
- <layer id="225" name="Convolution_2801" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="289" name="vae.encoder.down_blocks.3.resnets.0.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2801"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.3.resnets.0.conv1.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="290" name="/encoder/down_blocks.3/resnets.0/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4446,10 +5335,10 @@
</port>
</output>
</layer>
- <layer id="226" name="Reshape_2821" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="66194976" size="2048"/>
+ <layer id="291" name="Reshape_120094_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="33097504" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4457,11 +5346,30 @@
</port>
</output>
</layer>
- <layer id="227" name="onnx::Cast_578" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="292" name="Reshape_120094" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2820, Reshape_2821, input.168, onnx::Cast_578"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="293" name="/encoder/down_blocks.3/resnets.0/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4477,7 +5385,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.168,onnx::Cast_578">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4485,22 +5393,16 @@
</port>
</output>
</layer>
- <layer id="228" name="onnx::Reshape_580" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_580"/>
- </rt_info>
+ <layer id="294" name="/encoder/down_blocks.3/resnets.0/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_580">
+ <port id="0" precision="I64" names="/encoder/down_blocks.3/resnets.0/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="229" name="onnx::InstanceNormalization_581" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_581"/>
- </rt_info>
+ <layer id="295" name="/encoder/down_blocks.3/resnets.0/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4513,29 +5415,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_581">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="230" name="Constant_2859" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_2859"/>
- </rt_info>
+ <layer id="296" name="Constant_120131" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="231" name="MVN_2860" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_2879, Concat_2924, MVN_2860, Multiply_2907, Reshape_2880, Reshape_2925, onnx::Reshape_584"/>
- </rt_info>
+ <layer id="297" name="MVN_120132" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4547,18 +5443,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_584">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="232" name="onnx::Reshape_585" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_585"/>
- </rt_info>
+ <layer id="298" name="/encoder/down_blocks.3/resnets.0/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4568,16 +5461,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_585">
+ <port id="1" precision="I64" names="/encoder/down_blocks.3/resnets.0/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="233" name="onnx::Mul_586" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_586"/>
- </rt_info>
+ <layer id="299" name="/encoder/down_blocks.3/resnets.0/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4589,7 +5479,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_586">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4597,10 +5487,10 @@
</port>
</output>
</layer>
- <layer id="234" name="Constant_13471" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="66197024" size="2048"/>
+ <layer id="300" name="Constant_155082_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="33098528" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4608,11 +5498,30 @@
</port>
</output>
</layer>
- <layer id="235" name="onnx::Add_589" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="301" name="Constant_155082" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_589"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="302" name="/encoder/down_blocks.3/resnets.0/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4628,7 +5537,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_589">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm2/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4636,10 +5545,10 @@
</port>
</output>
</layer>
- <layer id="236" name="Constant_13472" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="66199072" size="2048"/>
+ <layer id="303" name="Constant_155083_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="33099552" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4647,11 +5556,30 @@
</port>
</output>
</layer>
- <layer id="237" name="onnx::Cast_592" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="304" name="Constant_155083" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.172, onnx::Cast_592"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="305" name="/encoder/down_blocks.3/resnets.0/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4667,7 +5595,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.172,onnx::Cast_592">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4675,10 +5603,7 @@
</port>
</output>
</layer>
- <layer id="238" name="input.176" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.176, onnx::Mul_594"/>
- </rt_info>
+ <layer id="306" name="/encoder/down_blocks.3/resnets.0/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4688,7 +5613,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.176">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.3/resnets.0/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4696,13 +5621,10 @@
</port>
</output>
</layer>
- <layer id="239" name="m.encoder.down_blocks.3.resnets.0.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="66201120" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.3.resnets.0.conv2.weight"/>
- </rt_info>
+ <layer id="307" name="vae.encoder.down_blocks.3.resnets.0.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="33100576" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.3.resnets.0.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -4710,11 +5632,30 @@
</port>
</output>
</layer>
- <layer id="240" name="Convolution_2965" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="308" name="vae.encoder.down_blocks.3.resnets.0.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_2965"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.3.resnets.0.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="309" name="/encoder/down_blocks.3/resnets.0/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4738,10 +5679,10 @@
</port>
</output>
</layer>
- <layer id="241" name="Reshape_2985" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="75638304" size="2048"/>
+ <layer id="310" name="Reshape_120256_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="37819168" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4749,11 +5690,30 @@
</port>
</output>
</layer>
- <layer id="242" name="onnx::Add_596" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="311" name="Reshape_120256" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_2984, Reshape_2985, onnx::Add_596"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="312" name="/encoder/down_blocks.3/resnets.0/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4769,7 +5729,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_596">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4777,11 +5737,8 @@
</port>
</output>
</layer>
- <layer id="243" name="onnx::Div_597" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.180, onnx::Cast_599, onnx::Div_597"/>
- </rt_info>
+ <layer id="313" name="/encoder/down_blocks.3/resnets.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4797,7 +5754,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.180,onnx::Cast_599,onnx::Div_597">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.0/Add_output_0,/encoder/down_blocks.3/resnets.0/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4805,22 +5762,16 @@
</port>
</output>
</layer>
- <layer id="244" name="onnx::Reshape_601" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_601"/>
- </rt_info>
+ <layer id="314" name="/encoder/down_blocks.3/resnets.1/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_601">
+ <port id="0" precision="I64" names="/encoder/down_blocks.3/resnets.1/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="245" name="onnx::InstanceNormalization_602" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_602"/>
- </rt_info>
+ <layer id="315" name="/encoder/down_blocks.3/resnets.1/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4833,29 +5784,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_602">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="246" name="Constant_3026" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3026"/>
- </rt_info>
+ <layer id="316" name="Constant_120296" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="247" name="MVN_3027" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_3046, Concat_3091, MVN_3027, Multiply_3074, Reshape_3047, Reshape_3092, onnx::Reshape_605"/>
- </rt_info>
+ <layer id="317" name="MVN_120297" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4867,18 +5812,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_605">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="248" name="onnx::Reshape_606" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_606"/>
- </rt_info>
+ <layer id="318" name="/encoder/down_blocks.3/resnets.1/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4888,16 +5830,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_606">
+ <port id="1" precision="I64" names="/encoder/down_blocks.3/resnets.1/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="249" name="onnx::Mul_607" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_607"/>
- </rt_info>
+ <layer id="319" name="/encoder/down_blocks.3/resnets.1/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4909,7 +5848,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_607">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4917,10 +5856,10 @@
</port>
</output>
</layer>
- <layer id="250" name="Constant_13473" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="75640352" size="2048"/>
+ <layer id="320" name="Constant_155084_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="37820192" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4928,11 +5867,30 @@
</port>
</output>
</layer>
- <layer id="251" name="onnx::Add_610" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="321" name="Constant_155084" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_610"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="322" name="/encoder/down_blocks.3/resnets.1/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4948,7 +5906,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_610">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4956,10 +5914,10 @@
</port>
</output>
</layer>
- <layer id="252" name="Constant_13474" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="75642400" size="2048"/>
+ <layer id="323" name="Constant_155085_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="37821216" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -4967,11 +5925,30 @@
</port>
</output>
</layer>
- <layer id="253" name="onnx::Cast_613" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="324" name="Constant_155085" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.184, onnx::Cast_613"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="325" name="/encoder/down_blocks.3/resnets.1/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -4987,7 +5964,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.184,onnx::Cast_613">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm1/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -4995,10 +5972,7 @@
</port>
</output>
</layer>
- <layer id="254" name="input.188" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.188, onnx::Mul_615"/>
- </rt_info>
+ <layer id="326" name="/encoder/down_blocks.3/resnets.1/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5008,7 +5982,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.188">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.3/resnets.1/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5016,13 +5990,10 @@
</port>
</output>
</layer>
- <layer id="255" name="m.encoder.down_blocks.3.resnets.1.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="75644448" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.3.resnets.1.conv1.weight"/>
- </rt_info>
+ <layer id="327" name="vae.encoder.down_blocks.3.resnets.1.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="37822240" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.3.resnets.1.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -5030,11 +6001,30 @@
</port>
</output>
</layer>
- <layer id="256" name="Convolution_3132" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="328" name="vae.encoder.down_blocks.3.resnets.1.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_3132"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.3.resnets.1.conv1.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="329" name="/encoder/down_blocks.3/resnets.1/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5058,10 +6048,10 @@
</port>
</output>
</layer>
- <layer id="257" name="Reshape_3152" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="85081632" size="2048"/>
+ <layer id="330" name="Reshape_120421_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="42540832" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5069,11 +6059,30 @@
</port>
</output>
</layer>
- <layer id="258" name="onnx::Cast_617" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="331" name="Reshape_120421" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_3151, Reshape_3152, input.192, onnx::Cast_617"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="332" name="/encoder/down_blocks.3/resnets.1/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5089,7 +6098,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.192,onnx::Cast_617">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5097,22 +6106,16 @@
</port>
</output>
</layer>
- <layer id="259" name="onnx::Reshape_619" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_619"/>
- </rt_info>
+ <layer id="333" name="/encoder/down_blocks.3/resnets.1/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_619">
+ <port id="0" precision="I64" names="/encoder/down_blocks.3/resnets.1/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="260" name="onnx::InstanceNormalization_620" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_620"/>
- </rt_info>
+ <layer id="334" name="/encoder/down_blocks.3/resnets.1/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5125,29 +6128,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_620">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="261" name="Constant_3190" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3190"/>
- </rt_info>
+ <layer id="335" name="Constant_120458" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="262" name="MVN_3191" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_3210, Concat_3255, MVN_3191, Multiply_3238, Reshape_3211, Reshape_3256, onnx::Reshape_623"/>
- </rt_info>
+ <layer id="336" name="MVN_120459" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5159,18 +6156,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_623">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="263" name="onnx::Reshape_624" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_624"/>
- </rt_info>
+ <layer id="337" name="/encoder/down_blocks.3/resnets.1/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5180,16 +6174,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_624">
+ <port id="1" precision="I64" names="/encoder/down_blocks.3/resnets.1/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="264" name="onnx::Mul_625" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_625"/>
- </rt_info>
+ <layer id="338" name="/encoder/down_blocks.3/resnets.1/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5201,7 +6192,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_625">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5209,10 +6200,10 @@
</port>
</output>
</layer>
- <layer id="265" name="Constant_13475" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="85083680" size="2048"/>
+ <layer id="339" name="Constant_155086_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="42541856" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5220,11 +6211,30 @@
</port>
</output>
</layer>
- <layer id="266" name="onnx::Add_628" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="340" name="Constant_155086" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_628"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="341" name="/encoder/down_blocks.3/resnets.1/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5240,7 +6250,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_628">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm2/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5248,10 +6258,10 @@
</port>
</output>
</layer>
- <layer id="267" name="Constant_13476" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="85085728" size="2048"/>
+ <layer id="342" name="Constant_155087_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="42542880" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5259,11 +6269,30 @@
</port>
</output>
</layer>
- <layer id="268" name="onnx::Cast_631" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="343" name="Constant_155087" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.196, onnx::Cast_631"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="344" name="/encoder/down_blocks.3/resnets.1/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5279,7 +6308,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.196,onnx::Cast_631">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5287,10 +6316,7 @@
</port>
</output>
</layer>
- <layer id="269" name="input.200" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.200, onnx::Mul_633"/>
- </rt_info>
+ <layer id="345" name="/encoder/down_blocks.3/resnets.1/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5300,7 +6326,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.200">
+ <port id="1" precision="FP32" names="/encoder/down_blocks.3/resnets.1/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5308,13 +6334,10 @@
</port>
</output>
</layer>
- <layer id="270" name="m.encoder.down_blocks.3.resnets.1.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="85087776" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.down_blocks.3.resnets.1.conv2.weight"/>
- </rt_info>
+ <layer id="346" name="vae.encoder.down_blocks.3.resnets.1.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="42543904" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.down_blocks.3.resnets.1.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -5322,11 +6345,30 @@
</port>
</output>
</layer>
- <layer id="271" name="Convolution_3296" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="347" name="vae.encoder.down_blocks.3.resnets.1.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_3296"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.down_blocks.3.resnets.1.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="348" name="/encoder/down_blocks.3/resnets.1/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5350,10 +6392,10 @@
</port>
</output>
</layer>
- <layer id="272" name="Reshape_3316" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="94524960" size="2048"/>
+ <layer id="349" name="Reshape_120583_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="47262496" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5361,11 +6403,30 @@
</port>
</output>
</layer>
- <layer id="273" name="onnx::Add_635" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="350" name="Reshape_120583" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_3315, Reshape_3316, onnx::Add_635"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="351" name="/encoder/down_blocks.3/resnets.1/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5381,7 +6442,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_635">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5389,11 +6450,8 @@
</port>
</output>
</layer>
- <layer id="274" name="onnx::Div_636" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.204, onnx::Cast_638, onnx::Div_636"/>
- </rt_info>
+ <layer id="352" name="/encoder/down_blocks.3/resnets.1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5409,7 +6467,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.204,onnx::Cast_638,onnx::Div_636">
+ <port id="2" precision="FP32" names="/encoder/down_blocks.3/resnets.1/Add_output_0,/encoder/down_blocks.3/resnets.1/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5417,22 +6475,16 @@
</port>
</output>
</layer>
- <layer id="275" name="onnx::Reshape_640" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_640"/>
- </rt_info>
+ <layer id="353" name="/encoder/mid_block/resnets.0/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_640">
+ <port id="0" precision="I64" names="/encoder/mid_block/resnets.0/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="276" name="onnx::InstanceNormalization_641" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_641"/>
- </rt_info>
+ <layer id="354" name="/encoder/mid_block/resnets.0/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5445,29 +6497,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_641">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="277" name="Constant_3357" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3357"/>
- </rt_info>
+ <layer id="355" name="Constant_120623" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="278" name="MVN_3358" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_3377, Concat_3422, MVN_3358, Multiply_3405, Reshape_3378, Reshape_3423, onnx::Reshape_644"/>
- </rt_info>
+ <layer id="356" name="MVN_120624" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5479,18 +6525,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_644">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="279" name="onnx::Reshape_645" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_645"/>
- </rt_info>
+ <layer id="357" name="/encoder/mid_block/resnets.0/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5500,16 +6543,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_645">
+ <port id="1" precision="I64" names="/encoder/mid_block/resnets.0/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="280" name="onnx::Mul_646" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_646"/>
- </rt_info>
+ <layer id="358" name="/encoder/mid_block/resnets.0/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5521,7 +6561,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_646">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5529,10 +6569,10 @@
</port>
</output>
</layer>
- <layer id="281" name="Constant_13477" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="94527008" size="2048"/>
+ <layer id="359" name="Constant_155088_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="47263520" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5540,11 +6580,30 @@
</port>
</output>
</layer>
- <layer id="282" name="onnx::Add_649" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="360" name="Constant_155088" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_649"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="361" name="/encoder/mid_block/resnets.0/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5560,7 +6619,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_649">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5568,10 +6627,10 @@
</port>
</output>
</layer>
- <layer id="283" name="Constant_13478" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="94529056" size="2048"/>
+ <layer id="362" name="Constant_155089_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="47264544" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5579,11 +6638,30 @@
</port>
</output>
</layer>
- <layer id="284" name="onnx::Cast_652" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="363" name="Constant_155089" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.208, onnx::Cast_652"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="364" name="/encoder/mid_block/resnets.0/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5599,7 +6677,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.208,onnx::Cast_652">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm1/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5607,10 +6685,7 @@
</port>
</output>
</layer>
- <layer id="285" name="input.212" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.212, onnx::Mul_654"/>
- </rt_info>
+ <layer id="365" name="/encoder/mid_block/resnets.0/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5620,7 +6695,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.212">
+ <port id="1" precision="FP32" names="/encoder/mid_block/resnets.0/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5628,13 +6703,10 @@
</port>
</output>
</layer>
- <layer id="286" name="m.encoder.mid_block.resnets.0.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="94531104" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.mid_block.resnets.0.conv1.weight"/>
- </rt_info>
+ <layer id="366" name="vae.encoder.mid_block.resnets.0.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="47265568" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.mid_block.resnets.0.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -5642,11 +6714,30 @@
</port>
</output>
</layer>
- <layer id="287" name="Convolution_3463" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="367" name="vae.encoder.mid_block.resnets.0.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_3463"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.mid_block.resnets.0.conv1.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="368" name="/encoder/mid_block/resnets.0/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5670,10 +6761,10 @@
</port>
</output>
</layer>
- <layer id="288" name="Reshape_3483" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="103968288" size="2048"/>
+ <layer id="369" name="Reshape_120748_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="51984160" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5681,11 +6772,30 @@
</port>
</output>
</layer>
- <layer id="289" name="onnx::Cast_656" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="370" name="Reshape_120748" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_3482, Reshape_3483, input.216, onnx::Cast_656"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="371" name="/encoder/mid_block/resnets.0/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5701,7 +6811,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.216,onnx::Cast_656">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5709,22 +6819,16 @@
</port>
</output>
</layer>
- <layer id="290" name="onnx::Reshape_658" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_658"/>
- </rt_info>
+ <layer id="372" name="/encoder/mid_block/resnets.0/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_658">
+ <port id="0" precision="I64" names="/encoder/mid_block/resnets.0/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="291" name="onnx::InstanceNormalization_659" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_659"/>
- </rt_info>
+ <layer id="373" name="/encoder/mid_block/resnets.0/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5737,29 +6841,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_659">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="292" name="Constant_3521" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3521"/>
- </rt_info>
+ <layer id="374" name="Constant_120785" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="293" name="MVN_3522" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_3541, Concat_3586, MVN_3522, Multiply_3569, Reshape_3542, Reshape_3587, onnx::Reshape_662"/>
- </rt_info>
+ <layer id="375" name="MVN_120786" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5771,18 +6869,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_662">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="294" name="onnx::Reshape_663" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_663"/>
- </rt_info>
+ <layer id="376" name="/encoder/mid_block/resnets.0/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5792,16 +6887,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_663">
+ <port id="1" precision="I64" names="/encoder/mid_block/resnets.0/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="295" name="onnx::Mul_664" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_664"/>
- </rt_info>
+ <layer id="377" name="/encoder/mid_block/resnets.0/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5813,7 +6905,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_664">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5821,10 +6913,10 @@
</port>
</output>
</layer>
- <layer id="296" name="Constant_13479" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="103970336" size="2048"/>
+ <layer id="378" name="Constant_155090_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="51985184" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5832,11 +6924,30 @@
</port>
</output>
</layer>
- <layer id="297" name="onnx::Add_667" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="379" name="Constant_155090" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_667"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="380" name="/encoder/mid_block/resnets.0/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5852,7 +6963,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_667">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm2/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5860,10 +6971,10 @@
</port>
</output>
</layer>
- <layer id="298" name="Constant_13480" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="103972384" size="2048"/>
+ <layer id="381" name="Constant_155091_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="51986208" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5871,11 +6982,30 @@
</port>
</output>
</layer>
- <layer id="299" name="onnx::Cast_670" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="382" name="Constant_155091" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.220, onnx::Cast_670"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="383" name="/encoder/mid_block/resnets.0/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5891,7 +7021,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.220,onnx::Cast_670">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5899,10 +7029,7 @@
</port>
</output>
</layer>
- <layer id="300" name="input.224" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.224, onnx::Mul_672"/>
- </rt_info>
+ <layer id="384" name="/encoder/mid_block/resnets.0/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5912,7 +7039,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.224">
+ <port id="1" precision="FP32" names="/encoder/mid_block/resnets.0/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5920,13 +7047,10 @@
</port>
</output>
</layer>
- <layer id="301" name="m.encoder.mid_block.resnets.0.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="103974432" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.mid_block.resnets.0.conv2.weight"/>
- </rt_info>
+ <layer id="385" name="vae.encoder.mid_block.resnets.0.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="51987232" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.mid_block.resnets.0.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -5934,19 +7058,13 @@
</port>
</output>
</layer>
- <layer id="302" name="Convolution_3627" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="386" name="vae.encoder.mid_block.resnets.0.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_3627"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>512</dim>
- <dim>64</dim>
- <dim>64</dim>
- </port>
- <port id="1" precision="FP32">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -5954,7 +7072,32 @@
</port>
</input>
<output>
- <port id="2" precision="FP32">
+ <port id="1" precision="FP32" names="vae.encoder.mid_block.resnets.0.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="387" name="/encoder/mid_block/resnets.0/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>64</dim>
+ <dim>64</dim>
+ </port>
+ <port id="1" precision="FP32">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -5962,10 +7105,10 @@
</port>
</output>
</layer>
- <layer id="303" name="Reshape_3647" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="113411616" size="2048"/>
+ <layer id="388" name="Reshape_120910_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="56705824" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -5973,11 +7116,30 @@
</port>
</output>
</layer>
- <layer id="304" name="onnx::Add_674" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="389" name="Reshape_120910" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_3646, Reshape_3647, onnx::Add_674"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="390" name="/encoder/mid_block/resnets.0/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -5993,7 +7155,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_674">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -6001,11 +7163,8 @@
</port>
</output>
</layer>
- <layer id="305" name="onnx::Div_675" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.228, onnx::Div_675"/>
- </rt_info>
+ <layer id="391" name="/encoder/mid_block/resnets.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6021,7 +7180,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.228,onnx::Div_675">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.0/Add_output_0,/encoder/mid_block/resnets.0/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -6029,22 +7188,16 @@
</port>
</output>
</layer>
- <layer id="306" name="onnx::Reshape_690" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_690"/>
- </rt_info>
+ <layer id="392" name="/encoder/mid_block/attentions.0/group_norm/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_690">
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/group_norm/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="307" name="onnx::InstanceNormalization_691" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_691"/>
- </rt_info>
+ <layer id="393" name="/encoder/mid_block/attentions.0/group_norm/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6057,29 +7210,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_691">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/group_norm/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="308" name="Constant_3703" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3703"/>
- </rt_info>
+ <layer id="394" name="Constant_120966" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="309" name="MVN_3704" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_3723, Concat_3768, MVN_3704, Multiply_3751, Reshape_3724, Reshape_3769, onnx::Reshape_694"/>
- </rt_info>
+ <layer id="395" name="MVN_120967" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6091,18 +7238,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_694">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/group_norm/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="310" name="onnx::Reshape_695" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Gather_678, onnx::Gather_681, onnx::Gather_684, onnx::Gather_687, onnx::Reshape_695, onnx::Reshape_816"/>
- </rt_info>
+ <layer id="396" name="/encoder/mid_block/attentions.0/group_norm/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6112,16 +7256,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Gather_678,onnx::Gather_681,onnx::Gather_684,onnx::Gather_687,onnx::Reshape_695,onnx::Reshape_816">
+ <port id="1" precision="I64" names="/encoder/mid_block/attentions.0/Concat_10_output_0,/encoder/mid_block/attentions.0/Shape_1_output_0,/encoder/mid_block/attentions.0/Shape_2_output_0,/encoder/mid_block/attentions.0/Shape_3_output_0,/encoder/mid_block/attentions.0/Shape_output_0,/encoder/mid_block/attentions.0/group_norm/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="311" name="onnx::Mul_696" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_696"/>
- </rt_info>
+ <layer id="397" name="/encoder/mid_block/attentions.0/group_norm/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6133,7 +7274,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_696">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/group_norm/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -6141,10 +7282,10 @@
</port>
</output>
</layer>
- <layer id="312" name="Constant_13481" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="113413664" size="2048"/>
+ <layer id="398" name="Constant_155092_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="56706848" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -6152,11 +7293,30 @@
</port>
</output>
</layer>
- <layer id="313" name="onnx::Add_699" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="399" name="Constant_155092" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_699"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="400" name="/encoder/mid_block/attentions.0/group_norm/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6172,7 +7332,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_699">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/group_norm/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -6180,10 +7340,10 @@
</port>
</output>
</layer>
- <layer id="314" name="Constant_13482" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="113415712" size="2048"/>
+ <layer id="401" name="Constant_155093_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="56707872" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -6191,11 +7351,30 @@
</port>
</output>
</layer>
- <layer id="315" name="onnx::Reshape_702" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="402" name="Constant_155093" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_702"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="403" name="/encoder/mid_block/attentions.0/group_norm/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6211,7 +7390,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_702">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/group_norm/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -6219,28 +7398,22 @@
</port>
</output>
</layer>
- <layer id="316" name="Constant_11761" type="Const" version="opset1">
- <data element_type="i64" shape="2" offset="113417760" size="16"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_710"/>
- </rt_info>
+ <layer id="404" name="Constant_150367" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="56708896" size="16" />
<output>
<port id="0" precision="I64">
<dim>2</dim>
</port>
</output>
</layer>
- <layer id="317" name="Constant_11762" type="Const" version="opset1">
- <data element_type="i64" shape="" offset="113417776" size="8"/>
+ <layer id="405" name="Constant_150368" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
<output>
- <port id="0" precision="I64"/>
+ <port id="0" precision="I64" />
</output>
</layer>
- <layer id="318" name="Gather_11763" type="Gather" version="opset8">
- <data batch_dims="0"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_710"/>
- </rt_info>
+ <layer id="406" name="Gather_150369" type="Gather" version="opset8">
+ <data batch_dims="0" />
<input>
<port id="0" precision="I64">
<dim>4</dim>
@@ -6248,7 +7421,7 @@
<port id="1" precision="I64">
<dim>2</dim>
</port>
- <port id="2" precision="I64"/>
+ <port id="2" precision="I64" />
</input>
<output>
<port id="3" precision="I64">
@@ -6256,119 +7429,89 @@
</port>
</output>
</layer>
- <layer id="319" name="onnx::Gather_685" type="Const" version="opset1">
- <data element_type="i64" shape="" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Gather_685"/>
- </rt_info>
+ <layer id="407" name="/encoder/mid_block/attentions.0/Constant_2" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="9240" size="8" />
<output>
- <port id="0" precision="I64" names="onnx::Gather_685"/>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_2_output_0" />
</output>
</layer>
- <layer id="320" name="Constant_3688" type="Const" version="opset1">
- <data element_type="i64" shape="" offset="113417776" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3688"/>
- </rt_info>
+ <layer id="408" name="Constant_120951" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
<output>
- <port id="0" precision="I64"/>
+ <port id="0" precision="I64" />
</output>
</layer>
- <layer id="321" name="onnx::Mul_686" type="Gather" version="opset8">
- <data batch_dims="0"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3688, onnx::Gather_685, onnx::Mul_686"/>
- </rt_info>
+ <layer id="409" name="/encoder/mid_block/attentions.0/Gather_2" type="Gather" version="opset8">
+ <data batch_dims="0" />
<input>
<port id="0" precision="I64">
<dim>4</dim>
</port>
- <port id="1" precision="I64"/>
- <port id="2" precision="I64"/>
+ <port id="1" precision="I64" />
+ <port id="2" precision="I64" />
</input>
<output>
- <port id="3" precision="I64" names="onnx::Mul_686"/>
+ <port id="3" precision="I64" names="/encoder/mid_block/attentions.0/Gather_2_output_0" />
</output>
</layer>
- <layer id="322" name="onnx::Gather_688" type="Const" version="opset1">
- <data element_type="i64" shape="" offset="113417784" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Gather_688"/>
- </rt_info>
+ <layer id="410" name="/encoder/mid_block/attentions.0/Constant_3" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708920" size="8" />
<output>
- <port id="0" precision="I64" names="onnx::Gather_688"/>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_3_output_0" />
</output>
</layer>
- <layer id="323" name="Constant_3692" type="Const" version="opset1">
- <data element_type="i64" shape="" offset="113417776" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3692"/>
- </rt_info>
+ <layer id="411" name="Constant_120955" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
<output>
- <port id="0" precision="I64"/>
+ <port id="0" precision="I64" />
</output>
</layer>
- <layer id="324" name="onnx::Mul_689" type="Gather" version="opset8">
- <data batch_dims="0"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3692, onnx::Gather_688, onnx::Mul_689"/>
- </rt_info>
+ <layer id="412" name="/encoder/mid_block/attentions.0/Gather_3" type="Gather" version="opset8">
+ <data batch_dims="0" />
<input>
<port id="0" precision="I64">
<dim>4</dim>
</port>
- <port id="1" precision="I64"/>
- <port id="2" precision="I64"/>
+ <port id="1" precision="I64" />
+ <port id="2" precision="I64" />
</input>
<output>
- <port id="3" precision="I64" names="onnx::Mul_689"/>
+ <port id="3" precision="I64" names="/encoder/mid_block/attentions.0/Gather_3_output_0" />
</output>
</layer>
- <layer id="325" name="onnx::Unsqueeze_703" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Unsqueeze_703"/>
- </rt_info>
+ <layer id="413" name="/encoder/mid_block/attentions.0/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
- <port id="0" precision="I64"/>
- <port id="1" precision="I64"/>
+ <port id="0" precision="I64" />
+ <port id="1" precision="I64" />
</input>
<output>
- <port id="2" precision="I64" names="onnx::Unsqueeze_703"/>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Mul_output_0" />
</output>
</layer>
- <layer id="326" name="onnx::Unsqueeze_708" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="113417776" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Unsqueeze_708"/>
- </rt_info>
+ <layer id="414" name="Constant_326" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="56708912" size="8" />
<output>
- <port id="0" precision="I64" names="onnx::Unsqueeze_708">
+ <port id="0" precision="I64" names="onnx::Unsqueeze_672">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="327" name="onnx::Concat_709" type="Unsqueeze" version="opset1">
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Concat_709, onnx::Unsqueeze_708"/>
- </rt_info>
+ <layer id="415" name="/encoder/mid_block/attentions.0/Unsqueeze_2" type="Unsqueeze" version="opset1">
<input>
- <port id="0" precision="I64"/>
+ <port id="0" precision="I64" />
<port id="1" precision="I64">
<dim>1</dim>
</port>
</input>
<output>
- <port id="2" precision="I64" names="onnx::Concat_709">
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Unsqueeze_2_output_0">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="328" name="onnx::Reshape_710" type="Concat" version="opset1">
- <data axis="0"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_710"/>
- </rt_info>
+ <layer id="416" name="/encoder/mid_block/attentions.0/Concat" type="Concat" version="opset1">
+ <data axis="0" />
<input>
<port id="0" precision="I64">
<dim>2</dim>
@@ -6378,16 +7521,13 @@
</port>
</input>
<output>
- <port id="2" precision="I64" names="onnx::Reshape_710">
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Concat_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="329" name="onnx::Transpose_711" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Transpose_711"/>
- </rt_info>
+ <layer id="417" name="/encoder/mid_block/attentions.0/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6400,68 +7540,47 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_711">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>4096</dim>
</port>
</output>
</layer>
- <layer id="330" name="Constant_3889" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="113417792" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_3889"/>
- </rt_info>
+ <layer id="418" name="Constant_154905_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512" offset="56708928" size="524288" />
<output>
- <port id="0" precision="I64">
- <dim>3</dim>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
</port>
</output>
</layer>
- <layer id="331" name="onnx::MatMul_712" type="Transpose" version="opset1">
+ <layer id="419" name="Constant_154905" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::MatMul_712"/>
+ <attribute name="decompression" version="0" />
</rt_info>
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
+ <port id="0" precision="FP16">
<dim>512</dim>
- <dim>4096</dim>
- </port>
- <port id="1" precision="I64">
- <dim>3</dim>
- </port>
- </input>
- <output>
- <port id="2" precision="FP32" names="onnx::MatMul_712">
- <dim>1</dim>
- <dim>4096</dim>
<dim>512</dim>
</port>
- </output>
- </layer>
- <layer id="332" name="Constant_13329" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512" offset="113417816" size="1048576"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_714, onnx::MatMul_930"/>
- </rt_info>
+ </input>
<output>
- <port id="0" precision="FP32">
+ <port id="1" precision="FP32">
<dim>512</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="333" name="onnx::Add_714" type="MatMul" version="opset1">
- <data transpose_a="false" transpose_b="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_714, onnx::MatMul_930"/>
- </rt_info>
+ <layer id="420" name="/encoder/mid_block/attentions.0/query/MatMul" type="MatMul" version="opset1">
+ <data transpose_a="true" transpose_b="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
- <dim>4096</dim>
<dim>512</dim>
+ <dim>4096</dim>
</port>
<port id="1" precision="FP32">
<dim>512</dim>
@@ -6469,18 +7588,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_714">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/query/MatMul_output_0">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="334" name="query_proj" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="query_proj"/>
- </rt_info>
+ <layer id="421" name="/encoder/mid_block/attentions.0/query/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6494,211 +7610,1124 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="query_proj">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/query/Add_output_0">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="335" name="onnx::Reshape_738" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="114466392" size="32"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Concat_935, onnx::Concat_936, onnx::Reshape_738"/>
- </rt_info>
+ <layer id="422" name="Constant_152701" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="57233216" size="16" />
<output>
<port id="0" precision="I64">
- <dim>4</dim>
+ <dim>2</dim>
</port>
</output>
</layer>
- <layer id="336" name="onnx::Transpose_739" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Transpose_739"/>
- </rt_info>
+ <layer id="423" name="/encoder/mid_block/attentions.0/Constant_8" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="57233232" size="8" />
+ <output>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_8_output_0">
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="424" name="/encoder/mid_block/attentions.0/Shape_4" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
- <port id="1" precision="I64">
- <dim>4</dim>
- </port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_739">
- <dim>1</dim>
- <dim>4096</dim>
- <dim>1</dim>
- <dim>512</dim>
+ <port id="1" precision="I64" names="/encoder/mid_block/attentions.0/Shape_4_output_0,/encoder/mid_block/attentions.0/Shape_5_output_0,/encoder/mid_block/attentions.0/Shape_6_output_0">
+ <dim>3</dim>
</port>
</output>
</layer>
- <layer id="337" name="Constant_13331" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="114466424" size="32"/>
+ <layer id="425" name="/encoder/mid_block/attentions.0/Constant_6" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="9240" size="8" />
<output>
- <port id="0" precision="I64">
- <dim>4</dim>
- </port>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_6_output_0" />
</output>
</layer>
- <layer id="338" name="onnx::Mul_740" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_740"/>
- </rt_info>
+ <layer id="426" name="Constant_121170" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
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+ <data element_type="i64" shape="" offset="56708912" size="8" />
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+ <port id="1" precision="I64">
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+ <dim>1</dim>
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+ <dim>4096</dim>
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+ </output>
+ </layer>
+ <layer id="482" name="Constant_155097_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 1, 1" offset="57758586" size="2" />
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+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>1</dim>
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+ <data destination_type="f32" />
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+ <attribute name="decompression" version="0" />
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+ <dim>1</dim>
+ <dim>1</dim>
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+ <dim>1</dim>
+ <dim>1</dim>
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+ <dim>4096</dim>
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+ <layer id="485" name="/encoder/mid_block/attentions.0/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
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+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>4096</dim>
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+ <output>
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Add_output_0,/encoder/mid_block/attentions.0/Cast_6_output_0">
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+ <dim>4096</dim>
+ <dim>4096</dim>
+ </port>
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+ <data axis="-1" />
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+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>4096</dim>
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+ </input>
+ <output>
+ <port id="1" precision="FP32" names="/encoder/mid_block/attentions.0/Cast_7_output_0,/encoder/mid_block/attentions.0/Softmax_output_0">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>4096</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="487" name="Constant_155098_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 1, 512" offset="57758588" size="1024" />
+ <output>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="488" name="Constant_155098" type="Convert" version="opset1">
+ <data destination_type="f32" />
+ <rt_info>
+ <attribute name="decompression" version="0" />
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+ <input>
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+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
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+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>512</dim>
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+ <layer id="489" name="Constant_154933_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512" offset="57759612" size="524288" />
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+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ </output>
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+ <layer id="490" name="Constant_154933" type="Convert" version="opset1">
+ <data destination_type="f32" />
+ <rt_info>
+ <attribute name="decompression" version="0" />
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+ <dim>512</dim>
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+ <output>
+ <port id="1" precision="FP32">
+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="491" name="/encoder/mid_block/attentions.0/value/MatMul" type="MatMul" version="opset1">
+ <data transpose_a="true" transpose_b="true" />
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+ <port id="0" precision="FP32">
+ <dim>1</dim>
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+ <dim>4096</dim>
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+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/value/MatMul_output_0">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
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+ </output>
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+ <data auto_broadcast="numpy" />
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+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/value/Add_output_0">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="493" name="Constant_152889" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="57233216" size="16" />
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+ <port id="0" precision="I64">
+ <dim>2</dim>
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+ </output>
+ </layer>
+ <layer id="494" name="/encoder/mid_block/attentions.0/Constant_18" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="57233232" size="8" />
+ <output>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_18_output_0">
+ <dim>1</dim>
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+ </layer>
+ <layer id="495" name="/encoder/mid_block/attentions.0/Shape_10" type="ShapeOf" version="opset3">
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+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="I64" names="/encoder/mid_block/attentions.0/Shape_10_output_0,/encoder/mid_block/attentions.0/Shape_11_output_0,/encoder/mid_block/attentions.0/Shape_12_output_0">
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="496" name="/encoder/mid_block/attentions.0/Constant_16" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="9240" size="8" />
+ <output>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_16_output_0" />
+ </output>
+ </layer>
+ <layer id="497" name="Constant_121630" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
+ <layer id="498" name="/encoder/mid_block/attentions.0/Gather_12" type="Gather" version="opset8">
+ <data batch_dims="0" />
+ <input>
+ <port id="0" precision="I64">
+ <dim>3</dim>
+ </port>
+ <port id="1" precision="I64" />
+ <port id="2" precision="I64" />
+ </input>
+ <output>
+ <port id="3" precision="I64" names="/encoder/mid_block/attentions.0/Cast_4_output_0,/encoder/mid_block/attentions.0/Cast_5_output_0,/encoder/mid_block/attentions.0/Div_2_output_0,/encoder/mid_block/attentions.0/Gather_12_output_0" />
+ </output>
+ </layer>
+ <layer id="499" name="Constant_417" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" names="onnx::Unsqueeze_769">
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="500" name="/encoder/mid_block/attentions.0/Unsqueeze_17" type="Unsqueeze" version="opset1">
+ <input>
+ <port id="0" precision="I64" />
+ <port id="1" precision="I64">
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Unsqueeze_17_output_0">
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="501" name="/encoder/mid_block/attentions.0/Concat_5" type="Concat" version="opset1">
+ <data axis="0" />
+ <input>
+ <port id="0" precision="I64">
+ <dim>2</dim>
+ </port>
+ <port id="1" precision="I64">
+ <dim>1</dim>
+ </port>
+ <port id="2" precision="I64">
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="3" precision="I64">
+ <dim>4</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="502" name="/encoder/mid_block/attentions.0/Reshape_5" type="Reshape" version="opset1">
+ <data special_zero="true" />
+ <input>
+ <port id="0" precision="FP32">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
+ </port>
+ <port id="1" precision="I64">
+ <dim>4</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_5_output_0">
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>1</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="503" name="Constant_154935" type="Const" version="opset1">
+ <data element_type="i64" shape="4" offset="57233240" size="32" />
+ <output>
+ <port id="0" precision="I64">
+ <dim>4</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="504" name="/encoder/mid_block/attentions.0/Transpose_3" type="Reshape" version="opset1">
+ <data special_zero="true" />
+ <input>
<port id="0" precision="FP32">
<dim>1</dim>
<dim>4096</dim>
+ <dim>1</dim>
<dim>512</dim>
</port>
<port id="1" precision="I64">
@@ -6706,225 +8735,246 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_758">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Transpose_3_output_0">
+ <dim>1</dim>
+ <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="505" name="Constant_150402" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="56708896" size="16" />
+ <output>
+ <port id="0" precision="I64">
+ <dim>2</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="506" name="Constant_150403" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
+ <layer id="507" name="Gather_150404" type="Gather" version="opset8">
+ <data batch_dims="0" />
+ <input>
+ <port id="0" precision="I64">
+ <dim>3</dim>
+ </port>
+ <port id="1" precision="I64">
+ <dim>2</dim>
+ </port>
+ <port id="2" precision="I64" />
+ </input>
+ <output>
+ <port id="3" precision="I64">
+ <dim>2</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="508" name="Constant_426" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" names="onnx::Unsqueeze_778">
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="509" name="/encoder/mid_block/attentions.0/Unsqueeze_20" type="Unsqueeze" version="opset1">
+ <input>
+ <port id="0" precision="I64" />
+ <port id="1" precision="I64">
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Unsqueeze_20_output_0">
<dim>1</dim>
- <dim>4096</dim>
- <dim>1</dim>
- <dim>512</dim>
</port>
</output>
</layer>
- <layer id="347" name="Constant_4086" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="115517084" size="32"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_4086"/>
- </rt_info>
- <output>
+ <layer id="510" name="/encoder/mid_block/attentions.0/Concat_6" type="Concat" version="opset1">
+ <data axis="0" />
+ <input>
<port id="0" precision="I64">
- <dim>4</dim>
+ <dim>2</dim>
+ </port>
+ <port id="1" precision="I64">
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Concat_6_output_0">
+ <dim>3</dim>
</port>
</output>
</layer>
- <layer id="348" name="onnx::Mul_780" type="Transpose" version="opset1">
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_780"/>
- </rt_info>
+ <layer id="511" name="/encoder/mid_block/attentions.0/Reshape_6" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
- <dim>4096</dim>
<dim>1</dim>
+ <dim>4096</dim>
<dim>512</dim>
</port>
<port id="1" precision="I64">
- <dim>4</dim>
+ <dim>3</dim>
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_780">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_6_output_0">
<dim>1</dim>
- <dim>1</dim>
- <dim>512</dim>
<dim>4096</dim>
+ <dim>512</dim>
</port>
</output>
</layer>
- <layer id="349" name="Constant_13486" type="Const" version="opset1">
- <data element_type="f32" shape="1, 1, 1, 1" offset="114466456" size="4"/>
- <output>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>1</dim>
- <dim>1</dim>
- <dim>1</dim>
- </port>
- </output>
- </layer>
- <layer id="350" name="onnx::MatMul_782" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::MatMul_782"/>
- </rt_info>
+ <layer id="512" name="/encoder/mid_block/attentions.0/MatMul_1" type="MatMul" version="opset1">
+ <data transpose_a="false" transpose_b="false" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
- <dim>1</dim>
- <dim>512</dim>
+ <dim>4096</dim>
<dim>4096</dim>
</port>
<port id="1" precision="FP32">
<dim>1</dim>
- <dim>1</dim>
- <dim>1</dim>
- <dim>1</dim>
+ <dim>4096</dim>
+ <dim>512</dim>
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::MatMul_782">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/MatMul_1_output_0">
<dim>1</dim>
- <dim>1</dim>
- <dim>512</dim>
<dim>4096</dim>
+ <dim>512</dim>
</port>
</output>
</layer>
- <layer id="351" name="onnx::Cast_783" type="MatMul" version="opset1">
- <data transpose_a="false" transpose_b="false"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Cast_783, onnx::Softmax_784"/>
- </rt_info>
+ <layer id="513" name="/encoder/mid_block/attentions.0/Shape_16" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
- <dim>1</dim>
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
- <port id="1" precision="FP32">
- <dim>1</dim>
- <dim>1</dim>
- <dim>512</dim>
- <dim>4096</dim>
+ </input>
+ <output>
+ <port id="1" precision="I64" names="/encoder/mid_block/attentions.0/Shape_16_output_0,/encoder/mid_block/attentions.0/Shape_17_output_0,/encoder/mid_block/attentions.0/Shape_18_output_0">
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="514" name="/encoder/mid_block/attentions.0/Constant_24" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_24_output_0" />
+ </output>
+ </layer>
+ <layer id="515" name="Constant_121945" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
+ <layer id="516" name="/encoder/mid_block/attentions.0/Gather_16" type="Gather" version="opset8">
+ <data batch_dims="0" />
+ <input>
+ <port id="0" precision="I64">
+ <dim>3</dim>
</port>
+ <port id="1" precision="I64" />
+ <port id="2" precision="I64" />
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Cast_783,onnx::Softmax_784">
- <dim>1</dim>
+ <port id="3" precision="I64" names="/encoder/mid_block/attentions.0/Cast_8_output_0,/encoder/mid_block/attentions.0/Cast_9_output_0,/encoder/mid_block/attentions.0/Div_3_output_0,/encoder/mid_block/attentions.0/Gather_16_output_0" />
+ </output>
+ </layer>
+ <layer id="517" name="Constant_471" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" names="onnx::Unsqueeze_824">
<dim>1</dim>
- <dim>4096</dim>
- <dim>4096</dim>
</port>
</output>
</layer>
- <layer id="352" name="onnx::Cast_785" type="SoftMax" version="opset8">
- <data axis="-1"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Cast_785, onnx::MatMul_786"/>
- </rt_info>
+ <layer id="518" name="/encoder/mid_block/attentions.0/Unsqueeze_24" type="Unsqueeze" version="opset1">
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
+ <port id="0" precision="I64" />
+ <port id="1" precision="I64">
<dim>1</dim>
- <dim>4096</dim>
- <dim>4096</dim>
</port>
</input>
<output>
- <port id="1" precision="FP32" names="onnx::Cast_785,onnx::MatMul_786">
- <dim>1</dim>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Unsqueeze_24_output_0">
<dim>1</dim>
- <dim>4096</dim>
- <dim>4096</dim>
</port>
</output>
</layer>
- <layer id="353" name="Constant_13487" type="Const" version="opset1">
- <data element_type="f32" shape="1, 1, 512" offset="115517116" size="2048"/>
+ <layer id="519" name="/encoder/mid_block/attentions.0/Constant_28" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="57233232" size="8" />
<output>
- <port id="0" precision="FP32">
- <dim>1</dim>
+ <port id="0" precision="I64" names="/encoder/mid_block/attentions.0/Constant_28_output_0">
<dim>1</dim>
- <dim>512</dim>
</port>
</output>
</layer>
- <layer id="354" name="Constant_13350" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512" offset="115519164" size="1048576"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_720, onnx::MatMul_932"/>
- </rt_info>
+ <layer id="520" name="Constant_150407" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="58283900" size="16" />
<output>
- <port id="0" precision="FP32">
- <dim>512</dim>
- <dim>512</dim>
+ <port id="0" precision="I64">
+ <dim>2</dim>
</port>
</output>
</layer>
- <layer id="355" name="onnx::Add_720" type="MatMul" version="opset1">
- <data transpose_a="false" transpose_b="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_720, onnx::MatMul_932"/>
- </rt_info>
+ <layer id="521" name="Constant_150408" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
+ <layer id="522" name="Gather_150409" type="Gather" version="opset8">
+ <data batch_dims="0" />
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
+ <port id="0" precision="I64">
+ <dim>3</dim>
</port>
- <port id="1" precision="FP32">
- <dim>512</dim>
- <dim>512</dim>
+ <port id="1" precision="I64">
+ <dim>2</dim>
</port>
+ <port id="2" precision="I64" />
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_720">
- <dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
+ <port id="3" precision="I64">
+ <dim>2</dim>
</port>
</output>
</layer>
- <layer id="356" name="value_proj" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="value_proj"/>
- </rt_info>
+ <layer id="523" name="/encoder/mid_block/attentions.0/Concat_8" type="Concat" version="opset1">
+ <data axis="0" />
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
+ <port id="0" precision="I64">
<dim>1</dim>
- <dim>512</dim>
</port>
- <port id="1" precision="FP32">
+ <port id="1" precision="I64">
<dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
</port>
- </input>
- <output>
- <port id="2" precision="FP32" names="value_proj">
- <dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
+ <port id="2" precision="I64">
+ <dim>2</dim>
</port>
- </output>
- </layer>
- <layer id="357" name="onnx::Reshape_775" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="114466392" size="32"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Concat_935, onnx::Concat_936, onnx::Reshape_775"/>
- </rt_info>
+ </input>
<output>
- <port id="0" precision="I64">
+ <port id="3" precision="I64" names="/encoder/mid_block/attentions.0/Concat_8_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="358" name="onnx::Transpose_776" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Transpose_776"/>
- </rt_info>
+ <layer id="524" name="/encoder/mid_block/attentions.0/Reshape_7" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -6936,32 +8986,29 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_776">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_7_output_0">
<dim>1</dim>
- <dim>4096</dim>
<dim>1</dim>
+ <dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="359" name="Constant_13352" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="114466424" size="32"/>
+ <layer id="525" name="Constant_154942" type="Const" version="opset1">
+ <data element_type="i64" shape="4" offset="58283916" size="32" />
<output>
<port id="0" precision="I64">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="360" name="onnx::MatMul_777" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::MatMul_777"/>
- </rt_info>
+ <layer id="526" name="/encoder/mid_block/attentions.0/Transpose_5" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
- <dim>4096</dim>
<dim>1</dim>
+ <dim>4096</dim>
<dim>512</dim>
</port>
<port id="1" precision="I64">
@@ -6969,91 +9016,84 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::MatMul_777">
- <dim>1</dim>
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Transpose_5_output_0">
<dim>1</dim>
<dim>4096</dim>
+ <dim>1</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="361" name="onnx::Transpose_787" type="MatMul" version="opset1">
- <data transpose_a="false" transpose_b="false"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Transpose_787"/>
- </rt_info>
- <input>
- <port id="0" precision="FP32">
- <dim>1</dim>
+ <layer id="527" name="Constant_481" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" names="onnx::Unsqueeze_835">
<dim>1</dim>
- <dim>4096</dim>
- <dim>4096</dim>
</port>
- <port id="1" precision="FP32">
- <dim>1</dim>
+ </output>
+ </layer>
+ <layer id="528" name="/encoder/mid_block/attentions.0/Unsqueeze_27" type="Unsqueeze" version="opset1">
+ <input>
+ <port id="0" precision="I64" />
+ <port id="1" precision="I64">
<dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_787">
- <dim>1</dim>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Unsqueeze_27_output_0">
<dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
</port>
</output>
</layer>
- <layer id="362" name="Constant_13359" type="Const" version="opset1">
- <data element_type="i64" shape="4" offset="116567740" size="32"/>
+ <layer id="529" name="Constant_150412" type="Const" version="opset1">
+ <data element_type="i64" shape="2" offset="58283900" size="16" />
<output>
<port id="0" precision="I64">
- <dim>4</dim>
+ <dim>2</dim>
</port>
</output>
</layer>
- <layer id="363" name="onnx::Shape_788" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Shape_788"/>
- </rt_info>
+ <layer id="530" name="Constant_150413" type="Const" version="opset1">
+ <data element_type="i64" shape="" offset="56708912" size="8" />
+ <output>
+ <port id="0" precision="I64" />
+ </output>
+ </layer>
+ <layer id="531" name="Gather_150414" type="Gather" version="opset8">
+ <data batch_dims="0" />
<input>
- <port id="0" precision="FP32">
- <dim>1</dim>
- <dim>1</dim>
- <dim>4096</dim>
- <dim>512</dim>
+ <port id="0" precision="I64">
+ <dim>3</dim>
</port>
<port id="1" precision="I64">
- <dim>4</dim>
+ <dim>2</dim>
</port>
+ <port id="2" precision="I64" />
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Shape_788">
- <dim>1</dim>
- <dim>4096</dim>
- <dim>1</dim>
- <dim>512</dim>
+ <port id="3" precision="I64">
+ <dim>2</dim>
</port>
</output>
</layer>
- <layer id="364" name="onnx::Reshape_802" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="116567772" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Concat_939, onnx::Reshape_802"/>
- </rt_info>
- <output>
+ <layer id="532" name="/encoder/mid_block/attentions.0/Concat_9" type="Concat" version="opset1">
+ <data axis="0" />
+ <input>
<port id="0" precision="I64">
+ <dim>1</dim>
+ </port>
+ <port id="1" precision="I64">
+ <dim>2</dim>
+ </port>
+ </input>
+ <output>
+ <port id="2" precision="I64" names="/encoder/mid_block/attentions.0/Concat_9_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="365" name="onnx::MatMul_803" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::MatMul_803"/>
- </rt_info>
+ <layer id="533" name="/encoder/mid_block/attentions.0/Reshape_8" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7066,30 +9106,42 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::MatMul_803">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_8_output_0">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="366" name="Constant_13371" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512" offset="116567796" size="1048576"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_805, onnx::MatMul_940"/>
- </rt_info>
+ <layer id="534" name="Constant_154954_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512" offset="58283948" size="524288" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="367" name="onnx::Add_805" type="MatMul" version="opset1">
- <data transpose_a="false" transpose_b="true"/>
+ <layer id="535" name="Constant_154954" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_805, onnx::MatMul_940"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>512</dim>
+ <dim>512</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="536" name="/encoder/mid_block/attentions.0/proj_attn/MatMul" type="MatMul" version="opset1">
+ <data transpose_a="false" transpose_b="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7102,18 +9154,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_805">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/proj_attn/MatMul_output_0">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="368" name="onnx::Transpose_806" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Transpose_806"/>
- </rt_info>
+ <layer id="537" name="/encoder/mid_block/attentions.0/proj_attn/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7127,28 +9176,22 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Transpose_806">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/proj_attn/Add_output_0">
<dim>1</dim>
<dim>4096</dim>
<dim>512</dim>
</port>
</output>
</layer>
- <layer id="369" name="Constant_4157" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="113417792" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_4157"/>
- </rt_info>
+ <layer id="538" name="Constant_122175" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="58808236" size="24" />
<output>
<port id="0" precision="I64">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="370" name="onnx::Reshape_807" type="Transpose" version="opset1">
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_807"/>
- </rt_info>
+ <layer id="539" name="/encoder/mid_block/attentions.0/Transpose_6" type="Transpose" version="opset1">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7160,18 +9203,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_807">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Transpose_6_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>4096</dim>
</port>
</output>
</layer>
- <layer id="371" name="onnx::Add_817" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_817"/>
- </rt_info>
+ <layer id="540" name="/encoder/mid_block/attentions.0/Reshape_9" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7183,7 +9223,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_817">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Reshape_9_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7191,11 +9231,8 @@
</port>
</output>
</layer>
- <layer id="372" name="onnx::Div_818" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.232, onnx::Cast_820, onnx::Div_818"/>
- </rt_info>
+ <layer id="541" name="/encoder/mid_block/attentions.0/Add_1" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7211,7 +9248,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.232,onnx::Cast_820,onnx::Div_818">
+ <port id="2" precision="FP32" names="/encoder/mid_block/attentions.0/Add_1_output_0,/encoder/mid_block/attentions.0/Div_4_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7219,22 +9256,16 @@
</port>
</output>
</layer>
- <layer id="373" name="onnx::Reshape_822" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_822"/>
- </rt_info>
+ <layer id="542" name="/encoder/mid_block/resnets.1/norm1/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_822">
+ <port id="0" precision="I64" names="/encoder/mid_block/resnets.1/norm1/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="374" name="onnx::InstanceNormalization_823" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_823"/>
- </rt_info>
+ <layer id="543" name="/encoder/mid_block/resnets.1/norm1/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7247,29 +9278,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_823">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm1/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="375" name="Constant_4259" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_4259"/>
- </rt_info>
+ <layer id="544" name="Constant_122276" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="376" name="MVN_4260" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_4279, Concat_4324, MVN_4260, Multiply_4307, Reshape_4280, Reshape_4325, onnx::Reshape_826"/>
- </rt_info>
+ <layer id="545" name="MVN_122277" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7281,18 +9306,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_826">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm1/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="377" name="onnx::Reshape_827" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_827"/>
- </rt_info>
+ <layer id="546" name="/encoder/mid_block/resnets.1/norm1/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7302,16 +9324,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_827">
+ <port id="1" precision="I64" names="/encoder/mid_block/resnets.1/norm1/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="378" name="onnx::Mul_828" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_828"/>
- </rt_info>
+ <layer id="547" name="/encoder/mid_block/resnets.1/norm1/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7323,7 +9342,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_828">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm1/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7331,10 +9350,10 @@
</port>
</output>
</layer>
- <layer id="379" name="Constant_13489" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="117616372" size="2048"/>
+ <layer id="548" name="Constant_155100_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="58808260" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7342,11 +9361,30 @@
</port>
</output>
</layer>
- <layer id="380" name="onnx::Add_831" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="549" name="Constant_155100" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_831"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="550" name="/encoder/mid_block/resnets.1/norm1/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7362,7 +9400,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_831">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7370,10 +9408,10 @@
</port>
</output>
</layer>
- <layer id="381" name="Constant_13490" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="117618420" size="2048"/>
+ <layer id="551" name="Constant_155101_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="58809284" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7381,11 +9419,30 @@
</port>
</output>
</layer>
- <layer id="382" name="onnx::Cast_834" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="552" name="Constant_155101" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.236, onnx::Cast_834"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="553" name="/encoder/mid_block/resnets.1/norm1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7401,7 +9458,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.236,onnx::Cast_834">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm1/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7409,10 +9466,7 @@
</port>
</output>
</layer>
- <layer id="383" name="input.240" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.240, onnx::Mul_836"/>
- </rt_info>
+ <layer id="554" name="/encoder/mid_block/resnets.1/nonlinearity/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7422,7 +9476,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.240">
+ <port id="1" precision="FP32" names="/encoder/mid_block/resnets.1/nonlinearity/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7430,13 +9484,10 @@
</port>
</output>
</layer>
- <layer id="384" name="m.encoder.mid_block.resnets.1.conv1.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="117620468" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.mid_block.resnets.1.conv1.weight"/>
- </rt_info>
+ <layer id="555" name="vae.encoder.mid_block.resnets.1.conv1.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="58810308" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.mid_block.resnets.1.conv1.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -7444,11 +9495,30 @@
</port>
</output>
</layer>
- <layer id="385" name="Convolution_4365" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="556" name="vae.encoder.mid_block.resnets.1.conv1.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_4365"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.mid_block.resnets.1.conv1.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="557" name="/encoder/mid_block/resnets.1/conv1/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7472,10 +9542,10 @@
</port>
</output>
</layer>
- <layer id="386" name="Reshape_4385" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="127057652" size="2048"/>
+ <layer id="558" name="Reshape_122401_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="63528900" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7483,11 +9553,30 @@
</port>
</output>
</layer>
- <layer id="387" name="onnx::Cast_838" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="559" name="Reshape_122401" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_4384, Reshape_4385, input.244, onnx::Cast_838"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="560" name="/encoder/mid_block/resnets.1/conv1/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7503,7 +9592,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.244,onnx::Cast_838">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/conv1/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7511,22 +9600,16 @@
</port>
</output>
</layer>
- <layer id="388" name="onnx::Reshape_840" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_840"/>
- </rt_info>
+ <layer id="561" name="/encoder/mid_block/resnets.1/norm2/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_840">
+ <port id="0" precision="I64" names="/encoder/mid_block/resnets.1/norm2/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="389" name="onnx::InstanceNormalization_841" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_841"/>
- </rt_info>
+ <layer id="562" name="/encoder/mid_block/resnets.1/norm2/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7539,29 +9622,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_841">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm2/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="390" name="Constant_4423" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_4423"/>
- </rt_info>
+ <layer id="563" name="Constant_122438" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="391" name="MVN_4424" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_4443, Concat_4488, MVN_4424, Multiply_4471, Reshape_4444, Reshape_4489, onnx::Reshape_844"/>
- </rt_info>
+ <layer id="564" name="MVN_122439" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7573,18 +9650,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_844">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm2/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="392" name="onnx::Reshape_845" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_845"/>
- </rt_info>
+ <layer id="565" name="/encoder/mid_block/resnets.1/norm2/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7594,16 +9668,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_845">
+ <port id="1" precision="I64" names="/encoder/mid_block/resnets.1/norm2/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="393" name="onnx::Mul_846" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_846"/>
- </rt_info>
+ <layer id="566" name="/encoder/mid_block/resnets.1/norm2/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7615,7 +9686,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_846">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm2/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7623,10 +9694,10 @@
</port>
</output>
</layer>
- <layer id="394" name="Constant_13491" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="127059700" size="2048"/>
+ <layer id="567" name="Constant_155102_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="63529924" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7634,11 +9705,30 @@
</port>
</output>
</layer>
- <layer id="395" name="onnx::Add_849" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="568" name="Constant_155102" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_849"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="569" name="/encoder/mid_block/resnets.1/norm2/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7654,7 +9744,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_849">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm2/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7662,10 +9752,10 @@
</port>
</output>
</layer>
- <layer id="396" name="Constant_13492" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="127061748" size="2048"/>
+ <layer id="570" name="Constant_155103_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="63530948" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7673,11 +9763,30 @@
</port>
</output>
</layer>
- <layer id="397" name="onnx::Cast_852" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="571" name="Constant_155103" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.248, onnx::Cast_852"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="572" name="/encoder/mid_block/resnets.1/norm2/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7693,7 +9802,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.248,onnx::Cast_852">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/norm2/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7701,10 +9810,7 @@
</port>
</output>
</layer>
- <layer id="398" name="input.252" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.252, onnx::Mul_854"/>
- </rt_info>
+ <layer id="573" name="/encoder/mid_block/resnets.1/nonlinearity_1/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7714,7 +9820,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.252">
+ <port id="1" precision="FP32" names="/encoder/mid_block/resnets.1/nonlinearity_1/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7722,13 +9828,10 @@
</port>
</output>
</layer>
- <layer id="399" name="m.encoder.mid_block.resnets.1.conv2.weight" type="Const" version="opset1">
- <data element_type="f32" shape="512, 512, 3, 3" offset="127063796" size="9437184"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.mid_block.resnets.1.conv2.weight"/>
- </rt_info>
+ <layer id="574" name="vae.encoder.mid_block.resnets.1.conv2.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="512, 512, 3, 3" offset="63531972" size="4718592" />
<output>
- <port id="0" precision="FP32" names="m.encoder.mid_block.resnets.1.conv2.weight">
+ <port id="0" precision="FP16">
<dim>512</dim>
<dim>512</dim>
<dim>3</dim>
@@ -7736,11 +9839,30 @@
</port>
</output>
</layer>
- <layer id="400" name="Convolution_4529" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="575" name="vae.encoder.mid_block.resnets.1.conv2.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_4529"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.mid_block.resnets.1.conv2.weight">
+ <dim>512</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="576" name="/encoder/mid_block/resnets.1/conv2/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7764,10 +9886,10 @@
</port>
</output>
</layer>
- <layer id="401" name="Reshape_4549" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="136500980" size="2048"/>
+ <layer id="577" name="Reshape_122563_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="68250564" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7775,11 +9897,30 @@
</port>
</output>
</layer>
- <layer id="402" name="onnx::Add_856" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="578" name="Reshape_122563" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_4548, Reshape_4549, onnx::Add_856"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="579" name="/encoder/mid_block/resnets.1/conv2/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7795,7 +9936,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_856">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/conv2/Conv_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7803,11 +9944,8 @@
</port>
</output>
</layer>
- <layer id="403" name="onnx::Div_857" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="input.256, onnx::Div_857"/>
- </rt_info>
+ <layer id="580" name="/encoder/mid_block/resnets.1/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7823,7 +9961,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.256,onnx::Div_857">
+ <port id="2" precision="FP32" names="/encoder/mid_block/resnets.1/Add_output_0,/encoder/mid_block/resnets.1/Div_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7831,22 +9969,16 @@
</port>
</output>
</layer>
- <layer id="404" name="onnx::Reshape_860" type="Const" version="opset1">
- <data element_type="i64" shape="3" offset="18432" size="24"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_860"/>
- </rt_info>
+ <layer id="581" name="/encoder/conv_norm_out/Constant" type="Const" version="opset1">
+ <data element_type="i64" shape="3" offset="9216" size="24" />
<output>
- <port id="0" precision="I64" names="onnx::Reshape_860">
+ <port id="0" precision="I64" names="/encoder/conv_norm_out/Constant_output_0">
<dim>3</dim>
</port>
</output>
</layer>
- <layer id="405" name="onnx::InstanceNormalization_861" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::InstanceNormalization_861"/>
- </rt_info>
+ <layer id="582" name="/encoder/conv_norm_out/Reshape" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7859,29 +9991,23 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::InstanceNormalization_861">
+ <port id="2" precision="FP32" names="/encoder/conv_norm_out/Reshape_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="406" name="Constant_4589" type="Const" version="opset1">
- <data element_type="i64" shape="1" offset="18456" size="8"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Constant_4589"/>
- </rt_info>
+ <layer id="583" name="Constant_122603" type="Const" version="opset1">
+ <data element_type="i64" shape="1" offset="9240" size="8" />
<output>
<port id="0" precision="I64">
<dim>1</dim>
</port>
</output>
</layer>
- <layer id="407" name="MVN_4590" type="MVN" version="opset6">
- <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="Concat_4609, Concat_4654, MVN_4590, Multiply_4637, Reshape_4610, Reshape_4655, onnx::Reshape_864"/>
- </rt_info>
+ <layer id="584" name="MVN_122604" type="MVN" version="opset6">
+ <data eps="9.9999999747524271e-07" normalize_variance="true" eps_mode="INSIDE_SQRT" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7893,18 +10019,15 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Reshape_864">
+ <port id="2" precision="FP32" names="/encoder/conv_norm_out/InstanceNormalization_output_0">
<dim>1</dim>
<dim>32</dim>
<dim>65536</dim>
</port>
</output>
</layer>
- <layer id="408" name="onnx::Reshape_865" type="ShapeOf" version="opset3">
- <data output_type="i64"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Reshape_865"/>
- </rt_info>
+ <layer id="585" name="/encoder/conv_norm_out/Shape" type="ShapeOf" version="opset3">
+ <data output_type="i64" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7914,16 +10037,13 @@
</port>
</input>
<output>
- <port id="1" precision="I64" names="onnx::Reshape_865">
+ <port id="1" precision="I64" names="/encoder/conv_norm_out/Shape_output_0">
<dim>4</dim>
</port>
</output>
</layer>
- <layer id="409" name="onnx::Mul_866" type="Reshape" version="opset1">
- <data special_zero="true"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="onnx::Mul_866"/>
- </rt_info>
+ <layer id="586" name="/encoder/conv_norm_out/Reshape_1" type="Reshape" version="opset1">
+ <data special_zero="true" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7935,7 +10055,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Mul_866">
+ <port id="2" precision="FP32" names="/encoder/conv_norm_out/Reshape_1_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7943,10 +10063,10 @@
</port>
</output>
</layer>
- <layer id="410" name="Constant_13493" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="136503028" size="2048"/>
+ <layer id="587" name="Constant_155104_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="68251588" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7954,11 +10074,30 @@
</port>
</output>
</layer>
- <layer id="411" name="onnx::Add_869" type="Multiply" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="588" name="Constant_155104" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="onnx::Add_869"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="589" name="/encoder/conv_norm_out/Mul" type="Multiply" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -7974,7 +10113,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="onnx::Add_869">
+ <port id="2" precision="FP32" names="/encoder/conv_norm_out/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -7982,10 +10121,10 @@
</port>
</output>
</layer>
- <layer id="412" name="Constant_13494" type="Const" version="opset1">
- <data element_type="f32" shape="1, 512, 1, 1" offset="136505076" size="2048"/>
+ <layer id="590" name="Constant_155105_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 512, 1, 1" offset="68252612" size="1024" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>512</dim>
<dim>1</dim>
@@ -7993,11 +10132,30 @@
</port>
</output>
</layer>
- <layer id="413" name="input.260" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="591" name="Constant_155105" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="input.260"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>512</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="592" name="/encoder/conv_norm_out/Add" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8013,7 +10171,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.260">
+ <port id="2" precision="FP32" names="/encoder/conv_norm_out/Add_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -8021,10 +10179,7 @@
</port>
</output>
</layer>
- <layer id="414" name="input.264" type="Swish" version="opset4">
- <rt_info>
- <attribute name="fused_names" version="0" value="input.264, onnx::Mul_873"/>
- </rt_info>
+ <layer id="593" name="/encoder/conv_act/Mul" type="Swish" version="opset4">
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8034,7 +10189,7 @@
</port>
</input>
<output>
- <port id="1" precision="FP32" names="input.264">
+ <port id="1" precision="FP32" names="/encoder/conv_act/Mul_output_0">
<dim>1</dim>
<dim>512</dim>
<dim>64</dim>
@@ -8042,13 +10197,10 @@
</port>
</output>
</layer>
- <layer id="415" name="m.encoder.conv_out.weight" type="Const" version="opset1">
- <data element_type="f32" shape="8, 512, 3, 3" offset="136507124" size="147456"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.encoder.conv_out.weight"/>
- </rt_info>
+ <layer id="594" name="vae.encoder.conv_out.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="8, 512, 3, 3" offset="68253636" size="73728" />
<output>
- <port id="0" precision="FP32" names="m.encoder.conv_out.weight">
+ <port id="0" precision="FP16">
<dim>8</dim>
<dim>512</dim>
<dim>3</dim>
@@ -8056,11 +10208,30 @@
</port>
</output>
</layer>
- <layer id="416" name="Convolution_4694" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+ <layer id="595" name="vae.encoder.conv_out.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_4694"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>8</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.encoder.conv_out.weight">
+ <dim>8</dim>
+ <dim>512</dim>
+ <dim>3</dim>
+ <dim>3</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="596" name="/encoder/conv_out/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8084,10 +10255,10 @@
</port>
</output>
</layer>
- <layer id="417" name="Reshape_4714" type="Const" version="opset1">
- <data element_type="f32" shape="1, 8, 1, 1" offset="136654580" size="32"/>
+ <layer id="597" name="Reshape_122728_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 8, 1, 1" offset="68327364" size="16" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>8</dim>
<dim>1</dim>
@@ -8095,11 +10266,30 @@
</port>
</output>
</layer>
- <layer id="418" name="input.268" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="598" name="Reshape_122728" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_4713, Reshape_4714, input.268"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="599" name="/encoder/conv_out/Conv" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8115,7 +10305,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="input.268">
+ <port id="2" precision="FP32" names="/encoder/conv_out/Conv_output_0">
<dim>1</dim>
<dim>8</dim>
<dim>64</dim>
@@ -8123,13 +10313,10 @@
</port>
</output>
</layer>
- <layer id="419" name="m.quant_conv.weight" type="Const" version="opset1">
- <data element_type="f32" shape="8, 8, 1, 1" offset="136654612" size="256"/>
- <rt_info>
- <attribute name="fused_names" version="0" value="m.quant_conv.weight"/>
- </rt_info>
+ <layer id="600" name="vae.quant_conv.weight_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="8, 8, 1, 1" offset="68327380" size="128" />
<output>
- <port id="0" precision="FP32" names="m.quant_conv.weight">
+ <port id="0" precision="FP16">
<dim>8</dim>
<dim>8</dim>
<dim>1</dim>
@@ -8137,11 +10324,30 @@
</port>
</output>
</layer>
- <layer id="420" name="Convolution_4742" type="Convolution" version="opset1">
- <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+ <layer id="601" name="vae.quant_conv.weight" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Convolution_4742"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>8</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32" names="vae.quant_conv.weight">
+ <dim>8</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="602" name="/quant_conv/Conv/WithoutBiases" type="Convolution" version="opset1">
+ <data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8165,10 +10371,10 @@
</port>
</output>
</layer>
- <layer id="421" name="Reshape_4762" type="Const" version="opset1">
- <data element_type="f32" shape="1, 8, 1, 1" offset="136654868" size="32"/>
+ <layer id="603" name="Reshape_122776_compressed" type="Const" version="opset1">
+ <data element_type="f16" shape="1, 8, 1, 1" offset="68327508" size="16" />
<output>
- <port id="0" precision="FP32">
+ <port id="0" precision="FP16">
<dim>1</dim>
<dim>8</dim>
<dim>1</dim>
@@ -8176,11 +10382,30 @@
</port>
</output>
</layer>
- <layer id="422" name="moments" type="Add" version="opset1">
- <data auto_broadcast="numpy"/>
+ <layer id="604" name="Reshape_122776" type="Convert" version="opset1">
+ <data destination_type="f32" />
<rt_info>
- <attribute name="fused_names" version="0" value="Concat_4761, Reshape_4762, moments"/>
+ <attribute name="decompression" version="0" />
</rt_info>
+ <input>
+ <port id="0" precision="FP16">
+ <dim>1</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </input>
+ <output>
+ <port id="1" precision="FP32">
+ <dim>1</dim>
+ <dim>8</dim>
+ <dim>1</dim>
+ <dim>1</dim>
+ </port>
+ </output>
+ </layer>
+ <layer id="605" name="image_latent" type="Add" version="opset1">
+ <data auto_broadcast="numpy" />
<input>
<port id="0" precision="FP32">
<dim>1</dim>
@@ -8196,7 +10421,7 @@
</port>
</input>
<output>
- <port id="2" precision="FP32" names="moments">
+ <port id="2" precision="FP32" names="image_latent">
<dim>1</dim>
<dim>8</dim>
<dim>64</dim>
@@ -8204,10 +10429,7 @@
</port>
</output>
</layer>
- <layer id="423" name="moments/sink_port_0" type="Result" version="opset1">
- <rt_info>
- <attribute name="fused_names" version="0" value="moments/sink_port_0"/>
- </rt_info>
+ <layer id="606" name="image_latent/sink_port_0" type="Result" version="opset1">
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<port id="0" precision="FP32">
<dim>1</dim>
@@ -8219,514 +10441,674 @@
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