openvino_multi_modal_projector_model.xml

<?xml version="1.0"?>
<net name="Model9" version="11">
	<layers>
		<layer id="0" name="image_features" type="Parameter" version="opset1">
			<data shape="?,?,1024" element_type="f32" />
			<output>
				<port id="0" precision="FP32" names="image_features">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1024</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="self.linear_1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="4096, 1024" offset="0" size="16777216" />
			<output>
				<port id="0" precision="FP32" names="self.linear_1.weight">
					<dim>4096</dim>
					<dim>1024</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="__module.linear_1/ov_ext::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="false" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>1024</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4096</dim>
					<dim>1024</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="Constant_81245" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 4096" offset="16777216" size="16384" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="__module.linear_1/ov_ext::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>4096</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="11,input">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="__module.act/aten::gelu/Gelu" type="Gelu" version="opset7">
			<data approximation_mode="ERF" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="13">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="self.linear_2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="4096, 4096" offset="16793600" size="67108864" />
			<output>
				<port id="0" precision="FP32" names="self.linear_2.weight">
					<dim>4096</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="__module.linear_2/ov_ext::linear/MatMul" type="MatMul" version="opset1">
			<data transpose_a="false" transpose_b="true" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4096</dim>
					<dim>4096</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="8" name="Constant_81246" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 4096" offset="83902464" size="16384" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="__module.linear_2/ov_ext::linear/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>4096</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="hidden_states">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="Result_79362" type="Result" version="opset1" output_names="hidden_states">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>-1</dim>
					<dim>4096</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="2" to-port="0" />
		<edge from-layer="1" from-port="0" to-layer="2" to-port="1" />
		<edge from-layer="2" from-port="2" to-layer="4" to-port="0" />
		<edge from-layer="3" from-port="0" to-layer="4" to-port="1" />
		<edge from-layer="4" from-port="2" to-layer="5" to-port="0" />
		<edge from-layer="5" from-port="1" to-layer="7" to-port="0" />
		<edge from-layer="6" from-port="0" to-layer="7" to-port="1" />
		<edge from-layer="7" from-port="2" to-layer="9" to-port="0" />
		<edge from-layer="8" from-port="0" to-layer="9" to-port="1" />
		<edge from-layer="9" from-port="2" to-layer="10" to-port="0" />
	</edges>
	<rt_info>
		<Runtime_version value="2025.2.0-19140-c01cd93e24d-releases/2025/2" />
		<conversion_parameters>
			<framework value="pytorch" />
			<is_python_object value="True" />
		</conversion_parameters>
		<optimum>
			<optimum_intel_version value="1.24.0" />
			<optimum_version value="1.26.1" />
			<pytorch_version value="2.7.1" />
			<transformers_version value="4.52.4" />
		</optimum>
	</rt_info>
</net>