# AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _align as align
from torch import device, empty_strided
from torch._inductor.async_compile import AsyncCompile
from torch._inductor.select_algorithm import extern_kernels
from torch._inductor.codegen.multi_kernel import MultiKernelCall
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid, split_scan_grid, grid_combo_kernels, start_graph, end_graph
from torch._C import _cuda_getCurrentRawStream as get_raw_stream

aten = torch.ops.aten
inductor_ops = torch.ops.inductor
_quantized = torch.ops._quantized
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cpu = torch._C._dynamo.guards._empty_strided_cpu
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
empty_strided_xpu = torch._C._dynamo.guards._empty_strided_xpu
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor
alloc_from_pool = torch.ops.inductor._alloc_from_pool
async_compile = AsyncCompile()


# kernel path: runs/run_shard_8/inductor_cache/ej/cejfrwnzxinkchwn6symdb72fdtj7gix5hy2vuswodhbeh45mrae.py
# Topologically Sorted Source Nodes: [input_1, input_2], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_1 => convolution
#   input_2 => relu
# Graph fragment:
#   %convolution : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%primals_3, %primals_1, %primals_2, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution,), kwargs = {})
triton_poi_fused_convolution_relu_0 = async_compile.triton('triton_poi_fused_convolution_relu_0', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[1048576], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_0', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_0(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 1048576
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 4096) % 64
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/7z/c7zuih2ysjtir5rh5seep5ijnhokjlgkyjw2edhf257ahvz4iipr.py
# Topologically Sorted Source Nodes: [input_5], Original ATen: [aten.max_pool2d_with_indices]
# Source node to ATen node mapping:
#   input_5 => getitem, getitem_1
# Graph fragment:
#   %getitem : [num_users=2] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets, 0), kwargs = {})
#   %getitem_1 : [num_users=1] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets, 1), kwargs = {})
triton_poi_fused_max_pool2d_with_indices_1 = async_compile.triton('triton_poi_fused_max_pool2d_with_indices_1', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[262144], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*i8', 3: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_max_pool2d_with_indices_1', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 4, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_max_pool2d_with_indices_1(in_ptr0, out_ptr0, out_ptr1, xnumel, XBLOCK : tl.constexpr):
    xnumel = 262144
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 32
    x1 = (xindex // 32)
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + ((2*x0) + (128*x1)), None, eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + (2*x0) + (128*x1)), None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr0 + (64 + (2*x0) + (128*x1)), None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (65 + (2*x0) + (128*x1)), None, eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + (x2), tmp6, None)
    tl.store(out_ptr1 + (x2), tmp16, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/xq/cxqz2dr7nh2qabrtemj52pazmhrknj5ltcy32ka252ia6a3jgpqi.py
# Topologically Sorted Source Nodes: [input_6, input_7], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_6 => convolution_2
#   input_7 => relu_2
# Graph fragment:
#   %convolution_2 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%getitem, %primals_6, %primals_7, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_2 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_2,), kwargs = {})
triton_poi_fused_convolution_relu_2 = async_compile.triton('triton_poi_fused_convolution_relu_2', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[524288], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_2', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_2(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 524288
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 1024) % 128
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/pr/cpri5daxkfbmt5ostbhb5o2avircr64a2rmdkxfackaxyjfc7owe.py
# Topologically Sorted Source Nodes: [input_10], Original ATen: [aten.max_pool2d_with_indices]
# Source node to ATen node mapping:
#   input_10 => getitem_2, getitem_3
# Graph fragment:
#   %getitem_2 : [num_users=2] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets_1, 0), kwargs = {})
#   %getitem_3 : [num_users=1] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets_1, 1), kwargs = {})
triton_poi_fused_max_pool2d_with_indices_3 = async_compile.triton('triton_poi_fused_max_pool2d_with_indices_3', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[131072], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*i8', 3: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_max_pool2d_with_indices_3', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 4, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_max_pool2d_with_indices_3(in_ptr0, out_ptr0, out_ptr1, xnumel, XBLOCK : tl.constexpr):
    xnumel = 131072
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 16
    x1 = (xindex // 16)
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + ((2*x0) + (64*x1)), None, eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + (2*x0) + (64*x1)), None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr0 + (32 + (2*x0) + (64*x1)), None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (33 + (2*x0) + (64*x1)), None, eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + (x2), tmp6, None)
    tl.store(out_ptr1 + (x2), tmp16, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/of/cof37d5wbqzvtkioj7k4me7wqpvfv55rs62ytonj7gij2o3abnod.py
# Topologically Sorted Source Nodes: [input_11, input_12], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_11 => convolution_4
#   input_12 => relu_4
# Graph fragment:
#   %convolution_4 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%getitem_2, %primals_10, %primals_11, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_4 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_4,), kwargs = {})
triton_poi_fused_convolution_relu_4 = async_compile.triton('triton_poi_fused_convolution_relu_4', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[262144], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_4', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_4(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 262144
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 256) % 256
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/mn/cmnzsv2cdbsuq2sygridqvwumzmcvknuthlumel5m25l2ajsr4ft.py
# Topologically Sorted Source Nodes: [input_19], Original ATen: [aten.max_pool2d_with_indices]
# Source node to ATen node mapping:
#   input_19 => getitem_4, getitem_5
# Graph fragment:
#   %getitem_4 : [num_users=2] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets_2, 0), kwargs = {})
#   %getitem_5 : [num_users=1] = call_function[target=operator.getitem](args = (%_low_memory_max_pool2d_with_offsets_2, 1), kwargs = {})
triton_poi_fused_max_pool2d_with_indices_5 = async_compile.triton('triton_poi_fused_max_pool2d_with_indices_5', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[65536], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*i8', 3: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_max_pool2d_with_indices_5', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 4, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_max_pool2d_with_indices_5(in_ptr0, out_ptr0, out_ptr1, xnumel, XBLOCK : tl.constexpr):
    xnumel = 65536
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 8
    x1 = (xindex // 8)
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + ((2*x0) + (32*x1)), None, eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + (2*x0) + (32*x1)), None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr0 + (16 + (2*x0) + (32*x1)), None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (17 + (2*x0) + (32*x1)), None, eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + (x2), tmp6, None)
    tl.store(out_ptr1 + (x2), tmp16, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/ic/cicsjqc3cfcjzqlztx4hz7ssqwe47ngo3g2onc6463k3vgfmt5cw.py
# Topologically Sorted Source Nodes: [input_20, input_21], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_20 => convolution_8
#   input_21 => relu_8
# Graph fragment:
#   %convolution_8 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%getitem_4, %primals_18, %primals_19, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_8 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_8,), kwargs = {})
triton_poi_fused_convolution_relu_6 = async_compile.triton('triton_poi_fused_convolution_relu_6', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[131072], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_6', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_6(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 131072
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 64) % 512
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/rs/crsb2j7t6kjc2dizrgavde3h3rerob3nhf7iqux6o24562lkvvoe.py
# Topologically Sorted Source Nodes: [input_24, input_25], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_24 => convolution_10
#   input_25 => relu_10
# Graph fragment:
#   %convolution_10 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_9, %primals_22, %primals_23, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_10 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_10,), kwargs = {})
triton_poi_fused_convolution_relu_7 = async_compile.triton('triton_poi_fused_convolution_relu_7', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[65536], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_7', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_7(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 65536
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 64) % 256
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/qy/cqyis4pzdzl2zcpdenz7kfyw4uxhak4ugnkkhusp7xtxj4qytdez.py
# Topologically Sorted Source Nodes: [input_26, input_27], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_26 => convolution_11
#   input_27 => relu_11
# Graph fragment:
#   %convolution_11 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_10, %primals_24, %primals_25, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_11 : [num_users=8] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_11,), kwargs = {})
triton_poi_fused_convolution_relu_8 = async_compile.triton('triton_poi_fused_convolution_relu_8', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[32768], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_8', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_8(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 32768
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 64) % 128
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + (x3), tmp4, None)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/xh/cxh5qnz7467zwx7kksukcyl5yqbimdzz2jusq6gmtz3v7ngsbddj.py
# Topologically Sorted Source Nodes: [out2], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   out2 => cat
# Graph fragment:
#   %cat : [num_users=3] = call_function[target=torch.ops.aten.cat.default](args = ([%convolution_16, %convolution_21, %relu_11], 1), kwargs = {})
triton_poi_fused_cat_9 = async_compile.triton('triton_poi_fused_cat_9', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[65536], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*fp32', 3: '*fp32', 4: '*fp32', 5: '*fp32', 6: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3, 4, 5, 6), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_cat_9', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 5, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_cat_9(in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 47360
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = (xindex // 64) % 185
    x0 = xindex % 64
    x2 = (xindex // 11840)
    x3 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 38, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + (64*x1) + (2432*x2)), tmp4 & xmask, other=0.0)
    tmp6 = tl.load(in_ptr1 + (x1), tmp4 & xmask, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full(tmp7.shape, 0.0, tmp7.dtype)
    tmp9 = tl.where(tmp4, tmp7, tmp8)
    tmp10 = tmp0 >= tmp3
    tmp11 = tl.full([1], 57, tl.int64)
    tmp12 = tmp0 < tmp11
    tmp13 = tmp10 & tmp12
    tmp14 = tl.load(in_ptr2 + (x0 + (64*((-38) + x1)) + (1216*x2)), tmp13 & xmask, other=0.0)
    tmp15 = tl.load(in_ptr3 + ((-38) + x1), tmp13 & xmask, eviction_policy='evict_last', other=0.0)
    tmp16 = tmp14 + tmp15
    tmp17 = tl.full(tmp16.shape, 0.0, tmp16.dtype)
    tmp18 = tl.where(tmp13, tmp16, tmp17)
    tmp19 = tmp0 >= tmp11
    tmp20 = tl.full([1], 185, tl.int64)
    tmp21 = tmp0 < tmp20
    tmp22 = tl.load(in_ptr4 + (x0 + (64*((-57) + x1)) + (8192*x2)), tmp19 & xmask, other=0.0)
    tmp23 = tl.where(tmp13, tmp18, tmp22)
    tmp24 = tl.where(tmp4, tmp9, tmp23)
    tl.store(out_ptr0 + (x3), tmp24, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/4y/c4y6uyvhmsek266ivpsqvnnoksgofgtz3h3rggm6nksziikdh57s.py
# Topologically Sorted Source Nodes: [input_162], Original ATen: [aten.convolution]
# Source node to ATen node mapping:
#   input_162 => convolution_84
# Graph fragment:
#   %convolution_84 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_73, %primals_170, %primals_171, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
triton_poi_fused_convolution_10 = async_compile.triton('triton_poi_fused_convolution_10', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[16384], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_10', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_10(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 9728
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 64) % 38
    tmp0 = tl.load(in_out_ptr0 + (x3), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + (x3), tmp2, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_8/inductor_cache/ce/ccekwplfoihswfouqfjqcwmfd2cg37pkjpmovikpxyaqzec4g3iq.py
# Topologically Sorted Source Nodes: [input_175, input_176], Original ATen: [aten.convolution, aten.relu, aten.threshold_backward]
# Source node to ATen node mapping:
#   input_175 => convolution_91
#   input_176 => relu_80
# Graph fragment:
#   %convolution_91 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_79, %primals_184, %primals_185, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_80 : [num_users=2] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_91,), kwargs = {})
#   %le : [num_users=1] = call_function[target=torch.ops.aten.le.Scalar](args = (%relu_80, 0), kwargs = {})
triton_poi_fused_convolution_relu_threshold_backward_11 = async_compile.triton('triton_poi_fused_convolution_relu_threshold_backward_11', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[8192], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*i1', 3: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_convolution_relu_threshold_backward_11', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 2, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_11(in_out_ptr0, in_ptr0, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 4864
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x4 = xindex
    x1 = (xindex // 64) % 19
    x2 = (xindex // 1216)
    x3 = xindex % 1216
    tmp0 = tl.load(in_out_ptr0 + (x4), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(in_out_ptr0 + (x4), tmp4, xmask)
    tl.store(out_ptr0 + (x3 + (1280*x2)), tmp6, xmask)
''', device_str='cuda')


async_compile.wait(globals())
del async_compile

def call(args):
    primals_1, primals_2, primals_3, primals_4, primals_5, primals_6, primals_7, primals_8, primals_9, primals_10, primals_11, primals_12, primals_13, primals_14, primals_15, primals_16, primals_17, primals_18, primals_19, primals_20, primals_21, primals_22, primals_23, primals_24, primals_25, primals_26, primals_27, primals_28, primals_29, primals_30, primals_31, primals_32, primals_33, primals_34, primals_35, primals_36, primals_37, primals_38, primals_39, primals_40, primals_41, primals_42, primals_43, primals_44, primals_45, primals_46, primals_47, primals_48, primals_49, primals_50, primals_51, primals_52, primals_53, primals_54, primals_55, primals_56, primals_57, primals_58, primals_59, primals_60, primals_61, primals_62, primals_63, primals_64, primals_65, primals_66, primals_67, primals_68, primals_69, primals_70, primals_71, primals_72, primals_73, primals_74, primals_75, primals_76, primals_77, primals_78, primals_79, primals_80, primals_81, primals_82, primals_83, primals_84, primals_85, primals_86, primals_87, primals_88, primals_89, primals_90, primals_91, primals_92, primals_93, primals_94, primals_95, primals_96, primals_97, primals_98, primals_99, primals_100, primals_101, primals_102, primals_103, primals_104, primals_105, primals_106, primals_107, primals_108, primals_109, primals_110, primals_111, primals_112, primals_113, primals_114, primals_115, primals_116, primals_117, primals_118, primals_119, primals_120, primals_121, primals_122, primals_123, primals_124, primals_125, primals_126, primals_127, primals_128, primals_129, primals_130, primals_131, primals_132, primals_133, primals_134, primals_135, primals_136, primals_137, primals_138, primals_139, primals_140, primals_141, primals_142, primals_143, primals_144, primals_145, primals_146, primals_147, primals_148, primals_149, primals_150, primals_151, primals_152, primals_153, primals_154, primals_155, primals_156, primals_157, primals_158, primals_159, primals_160, primals_161, primals_162, primals_163, primals_164, primals_165, primals_166, primals_167, primals_168, primals_169, primals_170, primals_171, primals_172, primals_173, primals_174, primals_175, primals_176, primals_177, primals_178, primals_179, primals_180, primals_181, primals_182, primals_183, primals_184, primals_185 = args
    args.clear()
    assert_size_stride(primals_1, (64, 3, 3, 3), (27, 9, 3, 1))
    assert_size_stride(primals_2, (64, ), (1, ))
    assert_size_stride(primals_3, (4, 3, 64, 64), (12288, 4096, 64, 1))
    assert_size_stride(primals_4, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_5, (64, ), (1, ))
    assert_size_stride(primals_6, (128, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_7, (128, ), (1, ))
    assert_size_stride(primals_8, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_9, (128, ), (1, ))
    assert_size_stride(primals_10, (256, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_11, (256, ), (1, ))
    assert_size_stride(primals_12, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_13, (256, ), (1, ))
    assert_size_stride(primals_14, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_15, (256, ), (1, ))
    assert_size_stride(primals_16, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_17, (256, ), (1, ))
    assert_size_stride(primals_18, (512, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_19, (512, ), (1, ))
    assert_size_stride(primals_20, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_21, (512, ), (1, ))
    assert_size_stride(primals_22, (256, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_23, (256, ), (1, ))
    assert_size_stride(primals_24, (128, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_25, (128, ), (1, ))
    assert_size_stride(primals_26, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_27, (128, ), (1, ))
    assert_size_stride(primals_28, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_29, (128, ), (1, ))
    assert_size_stride(primals_30, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_31, (128, ), (1, ))
    assert_size_stride(primals_32, (512, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_33, (512, ), (1, ))
    assert_size_stride(primals_34, (38, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_35, (38, ), (1, ))
    assert_size_stride(primals_36, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_37, (128, ), (1, ))
    assert_size_stride(primals_38, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_39, (128, ), (1, ))
    assert_size_stride(primals_40, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_41, (128, ), (1, ))
    assert_size_stride(primals_42, (512, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_43, (512, ), (1, ))
    assert_size_stride(primals_44, (19, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_45, (19, ), (1, ))
    assert_size_stride(primals_46, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_47, (128, ), (1, ))
    assert_size_stride(primals_48, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_49, (128, ), (1, ))
    assert_size_stride(primals_50, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_51, (128, ), (1, ))
    assert_size_stride(primals_52, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_53, (128, ), (1, ))
    assert_size_stride(primals_54, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_55, (128, ), (1, ))
    assert_size_stride(primals_56, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_57, (128, ), (1, ))
    assert_size_stride(primals_58, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_59, (38, ), (1, ))
    assert_size_stride(primals_60, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_61, (128, ), (1, ))
    assert_size_stride(primals_62, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_63, (128, ), (1, ))
    assert_size_stride(primals_64, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_65, (128, ), (1, ))
    assert_size_stride(primals_66, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_67, (128, ), (1, ))
    assert_size_stride(primals_68, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_69, (128, ), (1, ))
    assert_size_stride(primals_70, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_71, (128, ), (1, ))
    assert_size_stride(primals_72, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_73, (19, ), (1, ))
    assert_size_stride(primals_74, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_75, (128, ), (1, ))
    assert_size_stride(primals_76, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_77, (128, ), (1, ))
    assert_size_stride(primals_78, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_79, (128, ), (1, ))
    assert_size_stride(primals_80, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_81, (128, ), (1, ))
    assert_size_stride(primals_82, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_83, (128, ), (1, ))
    assert_size_stride(primals_84, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_85, (128, ), (1, ))
    assert_size_stride(primals_86, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_87, (38, ), (1, ))
    assert_size_stride(primals_88, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_89, (128, ), (1, ))
    assert_size_stride(primals_90, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_91, (128, ), (1, ))
    assert_size_stride(primals_92, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_93, (128, ), (1, ))
    assert_size_stride(primals_94, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_95, (128, ), (1, ))
    assert_size_stride(primals_96, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_97, (128, ), (1, ))
    assert_size_stride(primals_98, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_99, (128, ), (1, ))
    assert_size_stride(primals_100, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_101, (19, ), (1, ))
    assert_size_stride(primals_102, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_103, (128, ), (1, ))
    assert_size_stride(primals_104, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_105, (128, ), (1, ))
    assert_size_stride(primals_106, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_107, (128, ), (1, ))
    assert_size_stride(primals_108, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_109, (128, ), (1, ))
    assert_size_stride(primals_110, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_111, (128, ), (1, ))
    assert_size_stride(primals_112, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_113, (128, ), (1, ))
    assert_size_stride(primals_114, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_115, (38, ), (1, ))
    assert_size_stride(primals_116, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_117, (128, ), (1, ))
    assert_size_stride(primals_118, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_119, (128, ), (1, ))
    assert_size_stride(primals_120, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_121, (128, ), (1, ))
    assert_size_stride(primals_122, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_123, (128, ), (1, ))
    assert_size_stride(primals_124, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_125, (128, ), (1, ))
    assert_size_stride(primals_126, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_127, (128, ), (1, ))
    assert_size_stride(primals_128, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_129, (19, ), (1, ))
    assert_size_stride(primals_130, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_131, (128, ), (1, ))
    assert_size_stride(primals_132, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_133, (128, ), (1, ))
    assert_size_stride(primals_134, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_135, (128, ), (1, ))
    assert_size_stride(primals_136, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_137, (128, ), (1, ))
    assert_size_stride(primals_138, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_139, (128, ), (1, ))
    assert_size_stride(primals_140, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_141, (128, ), (1, ))
    assert_size_stride(primals_142, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_143, (38, ), (1, ))
    assert_size_stride(primals_144, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_145, (128, ), (1, ))
    assert_size_stride(primals_146, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_147, (128, ), (1, ))
    assert_size_stride(primals_148, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_149, (128, ), (1, ))
    assert_size_stride(primals_150, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_151, (128, ), (1, ))
    assert_size_stride(primals_152, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_153, (128, ), (1, ))
    assert_size_stride(primals_154, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_155, (128, ), (1, ))
    assert_size_stride(primals_156, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_157, (19, ), (1, ))
    assert_size_stride(primals_158, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_159, (128, ), (1, ))
    assert_size_stride(primals_160, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_161, (128, ), (1, ))
    assert_size_stride(primals_162, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_163, (128, ), (1, ))
    assert_size_stride(primals_164, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_165, (128, ), (1, ))
    assert_size_stride(primals_166, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_167, (128, ), (1, ))
    assert_size_stride(primals_168, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_169, (128, ), (1, ))
    assert_size_stride(primals_170, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_171, (38, ), (1, ))
    assert_size_stride(primals_172, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_173, (128, ), (1, ))
    assert_size_stride(primals_174, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_175, (128, ), (1, ))
    assert_size_stride(primals_176, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_177, (128, ), (1, ))
    assert_size_stride(primals_178, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_179, (128, ), (1, ))
    assert_size_stride(primals_180, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_181, (128, ), (1, ))
    assert_size_stride(primals_182, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_183, (128, ), (1, ))
    assert_size_stride(primals_184, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_185, (19, ), (1, ))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        # Topologically Sorted Source Nodes: [input_1], Original ATen: [aten.convolution]
        buf0 = extern_kernels.convolution(primals_3, primals_1, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf0, (4, 64, 64, 64), (262144, 4096, 64, 1))
        buf1 = buf0; del buf0  # reuse
        # Topologically Sorted Source Nodes: [input_1, input_2], Original ATen: [aten.convolution, aten.relu]
        stream0 = get_raw_stream(0)
        triton_poi_fused_convolution_relu_0.run(buf1, primals_2, 1048576, grid=grid(1048576), stream=stream0)
        del primals_2
        # Topologically Sorted Source Nodes: [input_3], Original ATen: [aten.convolution]
        buf2 = extern_kernels.convolution(buf1, primals_4, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf2, (4, 64, 64, 64), (262144, 4096, 64, 1))
        buf3 = buf2; del buf2  # reuse
        # Topologically Sorted Source Nodes: [input_3, input_4], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_0.run(buf3, primals_5, 1048576, grid=grid(1048576), stream=stream0)
        del primals_5
        buf4 = empty_strided_cuda((4, 64, 32, 32), (65536, 1024, 32, 1), torch.float32)
        buf5 = empty_strided_cuda((4, 64, 32, 32), (65536, 1024, 32, 1), torch.int8)
        # Topologically Sorted Source Nodes: [input_5], Original ATen: [aten.max_pool2d_with_indices]
        triton_poi_fused_max_pool2d_with_indices_1.run(buf3, buf4, buf5, 262144, grid=grid(262144), stream=stream0)
        # Topologically Sorted Source Nodes: [input_6], Original ATen: [aten.convolution]
        buf6 = extern_kernels.convolution(buf4, primals_6, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf6, (4, 128, 32, 32), (131072, 1024, 32, 1))
        buf7 = buf6; del buf6  # reuse
        # Topologically Sorted Source Nodes: [input_6, input_7], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_2.run(buf7, primals_7, 524288, grid=grid(524288), stream=stream0)
        del primals_7
        # Topologically Sorted Source Nodes: [input_8], Original ATen: [aten.convolution]
        buf8 = extern_kernels.convolution(buf7, primals_8, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf8, (4, 128, 32, 32), (131072, 1024, 32, 1))
        buf9 = buf8; del buf8  # reuse
        # Topologically Sorted Source Nodes: [input_8, input_9], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_2.run(buf9, primals_9, 524288, grid=grid(524288), stream=stream0)
        del primals_9
        buf10 = empty_strided_cuda((4, 128, 16, 16), (32768, 256, 16, 1), torch.float32)
        buf11 = empty_strided_cuda((4, 128, 16, 16), (32768, 256, 16, 1), torch.int8)
        # Topologically Sorted Source Nodes: [input_10], Original ATen: [aten.max_pool2d_with_indices]
        triton_poi_fused_max_pool2d_with_indices_3.run(buf9, buf10, buf11, 131072, grid=grid(131072), stream=stream0)
        # Topologically Sorted Source Nodes: [input_11], Original ATen: [aten.convolution]
        buf12 = extern_kernels.convolution(buf10, primals_10, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf12, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf13 = buf12; del buf12  # reuse
        # Topologically Sorted Source Nodes: [input_11, input_12], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_4.run(buf13, primals_11, 262144, grid=grid(262144), stream=stream0)
        del primals_11
        # Topologically Sorted Source Nodes: [input_13], Original ATen: [aten.convolution]
        buf14 = extern_kernels.convolution(buf13, primals_12, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf14, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf15 = buf14; del buf14  # reuse
        # Topologically Sorted Source Nodes: [input_13, input_14], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_4.run(buf15, primals_13, 262144, grid=grid(262144), stream=stream0)
        del primals_13
        # Topologically Sorted Source Nodes: [input_15], Original ATen: [aten.convolution]
        buf16 = extern_kernels.convolution(buf15, primals_14, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf16, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf17 = buf16; del buf16  # reuse
        # Topologically Sorted Source Nodes: [input_15, input_16], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_4.run(buf17, primals_15, 262144, grid=grid(262144), stream=stream0)
        del primals_15
        # Topologically Sorted Source Nodes: [input_17], Original ATen: [aten.convolution]
        buf18 = extern_kernels.convolution(buf17, primals_16, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf19 = buf18; del buf18  # reuse
        # Topologically Sorted Source Nodes: [input_17, input_18], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_4.run(buf19, primals_17, 262144, grid=grid(262144), stream=stream0)
        del primals_17
        buf20 = empty_strided_cuda((4, 256, 8, 8), (16384, 64, 8, 1), torch.float32)
        buf21 = empty_strided_cuda((4, 256, 8, 8), (16384, 64, 8, 1), torch.int8)
        # Topologically Sorted Source Nodes: [input_19], Original ATen: [aten.max_pool2d_with_indices]
        triton_poi_fused_max_pool2d_with_indices_5.run(buf19, buf20, buf21, 65536, grid=grid(65536), stream=stream0)
        # Topologically Sorted Source Nodes: [input_20], Original ATen: [aten.convolution]
        buf22 = extern_kernels.convolution(buf20, primals_18, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf22, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf23 = buf22; del buf22  # reuse
        # Topologically Sorted Source Nodes: [input_20, input_21], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_6.run(buf23, primals_19, 131072, grid=grid(131072), stream=stream0)
        del primals_19
        # Topologically Sorted Source Nodes: [input_22], Original ATen: [aten.convolution]
        buf24 = extern_kernels.convolution(buf23, primals_20, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf24, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf25 = buf24; del buf24  # reuse
        # Topologically Sorted Source Nodes: [input_22, input_23], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_6.run(buf25, primals_21, 131072, grid=grid(131072), stream=stream0)
        del primals_21
        # Topologically Sorted Source Nodes: [input_24], Original ATen: [aten.convolution]
        buf26 = extern_kernels.convolution(buf25, primals_22, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf26, (4, 256, 8, 8), (16384, 64, 8, 1))
        buf27 = buf26; del buf26  # reuse
        # Topologically Sorted Source Nodes: [input_24, input_25], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf27, primals_23, 65536, grid=grid(65536), stream=stream0)
        del primals_23
        # Topologically Sorted Source Nodes: [input_26], Original ATen: [aten.convolution]
        buf28 = extern_kernels.convolution(buf27, primals_24, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf28, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf29 = buf28; del buf28  # reuse
        # Topologically Sorted Source Nodes: [input_26, input_27], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf29, primals_25, 32768, grid=grid(32768), stream=stream0)
        del primals_25
        # Topologically Sorted Source Nodes: [input_28], Original ATen: [aten.convolution]
        buf30 = extern_kernels.convolution(buf29, primals_26, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf30, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf31 = buf30; del buf30  # reuse
        # Topologically Sorted Source Nodes: [input_28, input_29], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf31, primals_27, 32768, grid=grid(32768), stream=stream0)
        del primals_27
        # Topologically Sorted Source Nodes: [input_30], Original ATen: [aten.convolution]
        buf32 = extern_kernels.convolution(buf31, primals_28, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf32, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf33 = buf32; del buf32  # reuse
        # Topologically Sorted Source Nodes: [input_30, input_31], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf33, primals_29, 32768, grid=grid(32768), stream=stream0)
        del primals_29
        # Topologically Sorted Source Nodes: [input_32], Original ATen: [aten.convolution]
        buf34 = extern_kernels.convolution(buf33, primals_30, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf34, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf35 = buf34; del buf34  # reuse
        # Topologically Sorted Source Nodes: [input_32, input_33], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf35, primals_31, 32768, grid=grid(32768), stream=stream0)
        del primals_31
        # Topologically Sorted Source Nodes: [input_34], Original ATen: [aten.convolution]
        buf36 = extern_kernels.convolution(buf35, primals_32, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf36, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf37 = buf36; del buf36  # reuse
        # Topologically Sorted Source Nodes: [input_34, input_35], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_6.run(buf37, primals_33, 131072, grid=grid(131072), stream=stream0)
        del primals_33
        # Topologically Sorted Source Nodes: [input_36], Original ATen: [aten.convolution]
        buf38 = extern_kernels.convolution(buf37, primals_34, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf38, (4, 38, 8, 8), (2432, 64, 8, 1))
        # Topologically Sorted Source Nodes: [input_37], Original ATen: [aten.convolution]
        buf39 = extern_kernels.convolution(buf29, primals_36, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf39, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf40 = buf39; del buf39  # reuse
        # Topologically Sorted Source Nodes: [input_37, input_38], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf40, primals_37, 32768, grid=grid(32768), stream=stream0)
        del primals_37
        # Topologically Sorted Source Nodes: [input_39], Original ATen: [aten.convolution]
        buf41 = extern_kernels.convolution(buf40, primals_38, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf41, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf42 = buf41; del buf41  # reuse
        # Topologically Sorted Source Nodes: [input_39, input_40], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf42, primals_39, 32768, grid=grid(32768), stream=stream0)
        del primals_39
        # Topologically Sorted Source Nodes: [input_41], Original ATen: [aten.convolution]
        buf43 = extern_kernels.convolution(buf42, primals_40, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf43, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf44 = buf43; del buf43  # reuse
        # Topologically Sorted Source Nodes: [input_41, input_42], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf44, primals_41, 32768, grid=grid(32768), stream=stream0)
        del primals_41
        # Topologically Sorted Source Nodes: [input_43], Original ATen: [aten.convolution]
        buf45 = extern_kernels.convolution(buf44, primals_42, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf45, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf46 = buf45; del buf45  # reuse
        # Topologically Sorted Source Nodes: [input_43, input_44], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_6.run(buf46, primals_43, 131072, grid=grid(131072), stream=stream0)
        del primals_43
        # Topologically Sorted Source Nodes: [input_45], Original ATen: [aten.convolution]
        buf47 = extern_kernels.convolution(buf46, primals_44, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf47, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf48 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out2], Original ATen: [aten.cat]
        triton_poi_fused_cat_9.run(buf38, primals_35, buf47, primals_45, buf29, buf48, 47360, grid=grid(47360), stream=stream0)
        del buf38
        del buf47
        del primals_35
        del primals_45
        # Topologically Sorted Source Nodes: [input_46], Original ATen: [aten.convolution]
        buf49 = extern_kernels.convolution(buf48, primals_46, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf49, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf50 = buf49; del buf49  # reuse
        # Topologically Sorted Source Nodes: [input_46, input_47], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf50, primals_47, 32768, grid=grid(32768), stream=stream0)
        del primals_47
        # Topologically Sorted Source Nodes: [input_48], Original ATen: [aten.convolution]
        buf51 = extern_kernels.convolution(buf50, primals_48, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf51, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf52 = buf51; del buf51  # reuse
        # Topologically Sorted Source Nodes: [input_48, input_49], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf52, primals_49, 32768, grid=grid(32768), stream=stream0)
        del primals_49
        # Topologically Sorted Source Nodes: [input_50], Original ATen: [aten.convolution]
        buf53 = extern_kernels.convolution(buf52, primals_50, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf53, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf54 = buf53; del buf53  # reuse
        # Topologically Sorted Source Nodes: [input_50, input_51], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf54, primals_51, 32768, grid=grid(32768), stream=stream0)
        del primals_51
        # Topologically Sorted Source Nodes: [input_52], Original ATen: [aten.convolution]
        buf55 = extern_kernels.convolution(buf54, primals_52, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf55, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf56 = buf55; del buf55  # reuse
        # Topologically Sorted Source Nodes: [input_52, input_53], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf56, primals_53, 32768, grid=grid(32768), stream=stream0)
        del primals_53
        # Topologically Sorted Source Nodes: [input_54], Original ATen: [aten.convolution]
        buf57 = extern_kernels.convolution(buf56, primals_54, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf57, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf58 = buf57; del buf57  # reuse
        # Topologically Sorted Source Nodes: [input_54, input_55], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf58, primals_55, 32768, grid=grid(32768), stream=stream0)
        del primals_55
        # Topologically Sorted Source Nodes: [input_56], Original ATen: [aten.convolution]
        buf59 = extern_kernels.convolution(buf58, primals_56, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf59, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf60 = buf59; del buf59  # reuse
        # Topologically Sorted Source Nodes: [input_56, input_57], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf60, primals_57, 32768, grid=grid(32768), stream=stream0)
        del primals_57
        # Topologically Sorted Source Nodes: [input_58], Original ATen: [aten.convolution]
        buf61 = extern_kernels.convolution(buf60, primals_58, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf61, (4, 38, 8, 8), (2432, 64, 8, 1))
        # Topologically Sorted Source Nodes: [input_59], Original ATen: [aten.convolution]
        buf62 = extern_kernels.convolution(buf48, primals_60, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf62, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf63 = buf62; del buf62  # reuse
        # Topologically Sorted Source Nodes: [input_59, input_60], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf63, primals_61, 32768, grid=grid(32768), stream=stream0)
        del primals_61
        # Topologically Sorted Source Nodes: [input_61], Original ATen: [aten.convolution]
        buf64 = extern_kernels.convolution(buf63, primals_62, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf64, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf65 = buf64; del buf64  # reuse
        # Topologically Sorted Source Nodes: [input_61, input_62], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf65, primals_63, 32768, grid=grid(32768), stream=stream0)
        del primals_63
        # Topologically Sorted Source Nodes: [input_63], Original ATen: [aten.convolution]
        buf66 = extern_kernels.convolution(buf65, primals_64, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf66, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf67 = buf66; del buf66  # reuse
        # Topologically Sorted Source Nodes: [input_63, input_64], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf67, primals_65, 32768, grid=grid(32768), stream=stream0)
        del primals_65
        # Topologically Sorted Source Nodes: [input_65], Original ATen: [aten.convolution]
        buf68 = extern_kernels.convolution(buf67, primals_66, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf68, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf69 = buf68; del buf68  # reuse
        # Topologically Sorted Source Nodes: [input_65, input_66], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf69, primals_67, 32768, grid=grid(32768), stream=stream0)
        del primals_67
        # Topologically Sorted Source Nodes: [input_67], Original ATen: [aten.convolution]
        buf70 = extern_kernels.convolution(buf69, primals_68, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf70, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf71 = buf70; del buf70  # reuse
        # Topologically Sorted Source Nodes: [input_67, input_68], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf71, primals_69, 32768, grid=grid(32768), stream=stream0)
        del primals_69
        # Topologically Sorted Source Nodes: [input_69], Original ATen: [aten.convolution]
        buf72 = extern_kernels.convolution(buf71, primals_70, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf72, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf73 = buf72; del buf72  # reuse
        # Topologically Sorted Source Nodes: [input_69, input_70], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf73, primals_71, 32768, grid=grid(32768), stream=stream0)
        del primals_71
        # Topologically Sorted Source Nodes: [input_71], Original ATen: [aten.convolution]
        buf74 = extern_kernels.convolution(buf73, primals_72, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf75 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out3], Original ATen: [aten.cat]
        triton_poi_fused_cat_9.run(buf61, primals_59, buf74, primals_73, buf29, buf75, 47360, grid=grid(47360), stream=stream0)
        del buf61
        del buf74
        del primals_59
        del primals_73
        # Topologically Sorted Source Nodes: [input_72], Original ATen: [aten.convolution]
        buf76 = extern_kernels.convolution(buf75, primals_74, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf76, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf77 = buf76; del buf76  # reuse
        # Topologically Sorted Source Nodes: [input_72, input_73], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf77, primals_75, 32768, grid=grid(32768), stream=stream0)
        del primals_75
        # Topologically Sorted Source Nodes: [input_74], Original ATen: [aten.convolution]
        buf78 = extern_kernels.convolution(buf77, primals_76, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf78, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf79 = buf78; del buf78  # reuse
        # Topologically Sorted Source Nodes: [input_74, input_75], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf79, primals_77, 32768, grid=grid(32768), stream=stream0)
        del primals_77
        # Topologically Sorted Source Nodes: [input_76], Original ATen: [aten.convolution]
        buf80 = extern_kernels.convolution(buf79, primals_78, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf81 = buf80; del buf80  # reuse
        # Topologically Sorted Source Nodes: [input_76, input_77], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf81, primals_79, 32768, grid=grid(32768), stream=stream0)
        del primals_79
        # Topologically Sorted Source Nodes: [input_78], Original ATen: [aten.convolution]
        buf82 = extern_kernels.convolution(buf81, primals_80, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf82, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf83 = buf82; del buf82  # reuse
        # Topologically Sorted Source Nodes: [input_78, input_79], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf83, primals_81, 32768, grid=grid(32768), stream=stream0)
        del primals_81
        # Topologically Sorted Source Nodes: [input_80], Original ATen: [aten.convolution]
        buf84 = extern_kernels.convolution(buf83, primals_82, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf84, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf85 = buf84; del buf84  # reuse
        # Topologically Sorted Source Nodes: [input_80, input_81], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf85, primals_83, 32768, grid=grid(32768), stream=stream0)
        del primals_83
        # Topologically Sorted Source Nodes: [input_82], Original ATen: [aten.convolution]
        buf86 = extern_kernels.convolution(buf85, primals_84, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf86, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf87 = buf86; del buf86  # reuse
        # Topologically Sorted Source Nodes: [input_82, input_83], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf87, primals_85, 32768, grid=grid(32768), stream=stream0)
        del primals_85
        # Topologically Sorted Source Nodes: [input_84], Original ATen: [aten.convolution]
        buf88 = extern_kernels.convolution(buf87, primals_86, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf88, (4, 38, 8, 8), (2432, 64, 8, 1))
        # Topologically Sorted Source Nodes: [input_85], Original ATen: [aten.convolution]
        buf89 = extern_kernels.convolution(buf75, primals_88, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf89, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf90 = buf89; del buf89  # reuse
        # Topologically Sorted Source Nodes: [input_85, input_86], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf90, primals_89, 32768, grid=grid(32768), stream=stream0)
        del primals_89
        # Topologically Sorted Source Nodes: [input_87], Original ATen: [aten.convolution]
        buf91 = extern_kernels.convolution(buf90, primals_90, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf91, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf92 = buf91; del buf91  # reuse
        # Topologically Sorted Source Nodes: [input_87, input_88], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf92, primals_91, 32768, grid=grid(32768), stream=stream0)
        del primals_91
        # Topologically Sorted Source Nodes: [input_89], Original ATen: [aten.convolution]
        buf93 = extern_kernels.convolution(buf92, primals_92, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf93, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf94 = buf93; del buf93  # reuse
        # Topologically Sorted Source Nodes: [input_89, input_90], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf94, primals_93, 32768, grid=grid(32768), stream=stream0)
        del primals_93
        # Topologically Sorted Source Nodes: [input_91], Original ATen: [aten.convolution]
        buf95 = extern_kernels.convolution(buf94, primals_94, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf95, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf96 = buf95; del buf95  # reuse
        # Topologically Sorted Source Nodes: [input_91, input_92], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf96, primals_95, 32768, grid=grid(32768), stream=stream0)
        del primals_95
        # Topologically Sorted Source Nodes: [input_93], Original ATen: [aten.convolution]
        buf97 = extern_kernels.convolution(buf96, primals_96, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf97, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf98 = buf97; del buf97  # reuse
        # Topologically Sorted Source Nodes: [input_93, input_94], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf98, primals_97, 32768, grid=grid(32768), stream=stream0)
        del primals_97
        # Topologically Sorted Source Nodes: [input_95], Original ATen: [aten.convolution]
        buf99 = extern_kernels.convolution(buf98, primals_98, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf99, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf100 = buf99; del buf99  # reuse
        # Topologically Sorted Source Nodes: [input_95, input_96], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf100, primals_99, 32768, grid=grid(32768), stream=stream0)
        del primals_99
        # Topologically Sorted Source Nodes: [input_97], Original ATen: [aten.convolution]
        buf101 = extern_kernels.convolution(buf100, primals_100, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf101, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf102 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out4], Original ATen: [aten.cat]
        triton_poi_fused_cat_9.run(buf88, primals_87, buf101, primals_101, buf29, buf102, 47360, grid=grid(47360), stream=stream0)
        del buf101
        del buf88
        del primals_101
        del primals_87
        # Topologically Sorted Source Nodes: [input_98], Original ATen: [aten.convolution]
        buf103 = extern_kernels.convolution(buf102, primals_102, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf103, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf104 = buf103; del buf103  # reuse
        # Topologically Sorted Source Nodes: [input_98, input_99], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf104, primals_103, 32768, grid=grid(32768), stream=stream0)
        del primals_103
        # Topologically Sorted Source Nodes: [input_100], Original ATen: [aten.convolution]
        buf105 = extern_kernels.convolution(buf104, primals_104, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf105, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf106 = buf105; del buf105  # reuse
        # Topologically Sorted Source Nodes: [input_100, input_101], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf106, primals_105, 32768, grid=grid(32768), stream=stream0)
        del primals_105
        # Topologically Sorted Source Nodes: [input_102], Original ATen: [aten.convolution]
        buf107 = extern_kernels.convolution(buf106, primals_106, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf107, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf108 = buf107; del buf107  # reuse
        # Topologically Sorted Source Nodes: [input_102, input_103], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf108, primals_107, 32768, grid=grid(32768), stream=stream0)
        del primals_107
        # Topologically Sorted Source Nodes: [input_104], Original ATen: [aten.convolution]
        buf109 = extern_kernels.convolution(buf108, primals_108, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf109, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf110 = buf109; del buf109  # reuse
        # Topologically Sorted Source Nodes: [input_104, input_105], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf110, primals_109, 32768, grid=grid(32768), stream=stream0)
        del primals_109
        # Topologically Sorted Source Nodes: [input_106], Original ATen: [aten.convolution]
        buf111 = extern_kernels.convolution(buf110, primals_110, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf111, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf112 = buf111; del buf111  # reuse
        # Topologically Sorted Source Nodes: [input_106, input_107], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf112, primals_111, 32768, grid=grid(32768), stream=stream0)
        del primals_111
        # Topologically Sorted Source Nodes: [input_108], Original ATen: [aten.convolution]
        buf113 = extern_kernels.convolution(buf112, primals_112, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf113, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf114 = buf113; del buf113  # reuse
        # Topologically Sorted Source Nodes: [input_108, input_109], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf114, primals_113, 32768, grid=grid(32768), stream=stream0)
        del primals_113
        # Topologically Sorted Source Nodes: [input_110], Original ATen: [aten.convolution]
        buf115 = extern_kernels.convolution(buf114, primals_114, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf115, (4, 38, 8, 8), (2432, 64, 8, 1))
        # Topologically Sorted Source Nodes: [input_111], Original ATen: [aten.convolution]
        buf116 = extern_kernels.convolution(buf102, primals_116, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf116, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf117 = buf116; del buf116  # reuse
        # Topologically Sorted Source Nodes: [input_111, input_112], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf117, primals_117, 32768, grid=grid(32768), stream=stream0)
        del primals_117
        # Topologically Sorted Source Nodes: [input_113], Original ATen: [aten.convolution]
        buf118 = extern_kernels.convolution(buf117, primals_118, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf118, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf119 = buf118; del buf118  # reuse
        # Topologically Sorted Source Nodes: [input_113, input_114], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf119, primals_119, 32768, grid=grid(32768), stream=stream0)
        del primals_119
        # Topologically Sorted Source Nodes: [input_115], Original ATen: [aten.convolution]
        buf120 = extern_kernels.convolution(buf119, primals_120, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf120, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf121 = buf120; del buf120  # reuse
        # Topologically Sorted Source Nodes: [input_115, input_116], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf121, primals_121, 32768, grid=grid(32768), stream=stream0)
        del primals_121
        # Topologically Sorted Source Nodes: [input_117], Original ATen: [aten.convolution]
        buf122 = extern_kernels.convolution(buf121, primals_122, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf122, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf123 = buf122; del buf122  # reuse
        # Topologically Sorted Source Nodes: [input_117, input_118], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf123, primals_123, 32768, grid=grid(32768), stream=stream0)
        del primals_123
        # Topologically Sorted Source Nodes: [input_119], Original ATen: [aten.convolution]
        buf124 = extern_kernels.convolution(buf123, primals_124, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf124, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf125 = buf124; del buf124  # reuse
        # Topologically Sorted Source Nodes: [input_119, input_120], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf125, primals_125, 32768, grid=grid(32768), stream=stream0)
        del primals_125
        # Topologically Sorted Source Nodes: [input_121], Original ATen: [aten.convolution]
        buf126 = extern_kernels.convolution(buf125, primals_126, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf126, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf127 = buf126; del buf126  # reuse
        # Topologically Sorted Source Nodes: [input_121, input_122], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf127, primals_127, 32768, grid=grid(32768), stream=stream0)
        del primals_127
        # Topologically Sorted Source Nodes: [input_123], Original ATen: [aten.convolution]
        buf128 = extern_kernels.convolution(buf127, primals_128, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf128, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf129 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out5], Original ATen: [aten.cat]
        triton_poi_fused_cat_9.run(buf115, primals_115, buf128, primals_129, buf29, buf129, 47360, grid=grid(47360), stream=stream0)
        del buf115
        del buf128
        del primals_115
        del primals_129
        # Topologically Sorted Source Nodes: [input_124], Original ATen: [aten.convolution]
        buf130 = extern_kernels.convolution(buf129, primals_130, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf130, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf131 = buf130; del buf130  # reuse
        # Topologically Sorted Source Nodes: [input_124, input_125], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf131, primals_131, 32768, grid=grid(32768), stream=stream0)
        del primals_131
        # Topologically Sorted Source Nodes: [input_126], Original ATen: [aten.convolution]
        buf132 = extern_kernels.convolution(buf131, primals_132, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf132, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf133 = buf132; del buf132  # reuse
        # Topologically Sorted Source Nodes: [input_126, input_127], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf133, primals_133, 32768, grid=grid(32768), stream=stream0)
        del primals_133
        # Topologically Sorted Source Nodes: [input_128], Original ATen: [aten.convolution]
        buf134 = extern_kernels.convolution(buf133, primals_134, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf134, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf135 = buf134; del buf134  # reuse
        # Topologically Sorted Source Nodes: [input_128, input_129], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf135, primals_135, 32768, grid=grid(32768), stream=stream0)
        del primals_135
        # Topologically Sorted Source Nodes: [input_130], Original ATen: [aten.convolution]
        buf136 = extern_kernels.convolution(buf135, primals_136, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf136, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf137 = buf136; del buf136  # reuse
        # Topologically Sorted Source Nodes: [input_130, input_131], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf137, primals_137, 32768, grid=grid(32768), stream=stream0)
        del primals_137
        # Topologically Sorted Source Nodes: [input_132], Original ATen: [aten.convolution]
        buf138 = extern_kernels.convolution(buf137, primals_138, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf138, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf139 = buf138; del buf138  # reuse
        # Topologically Sorted Source Nodes: [input_132, input_133], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf139, primals_139, 32768, grid=grid(32768), stream=stream0)
        del primals_139
        # Topologically Sorted Source Nodes: [input_134], Original ATen: [aten.convolution]
        buf140 = extern_kernels.convolution(buf139, primals_140, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf140, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf141 = buf140; del buf140  # reuse
        # Topologically Sorted Source Nodes: [input_134, input_135], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf141, primals_141, 32768, grid=grid(32768), stream=stream0)
        del primals_141
        # Topologically Sorted Source Nodes: [input_136], Original ATen: [aten.convolution]
        buf142 = extern_kernels.convolution(buf141, primals_142, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf142, (4, 38, 8, 8), (2432, 64, 8, 1))
        # Topologically Sorted Source Nodes: [input_137], Original ATen: [aten.convolution]
        buf143 = extern_kernels.convolution(buf129, primals_144, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf143, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf144 = buf143; del buf143  # reuse
        # Topologically Sorted Source Nodes: [input_137, input_138], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf144, primals_145, 32768, grid=grid(32768), stream=stream0)
        del primals_145
        # Topologically Sorted Source Nodes: [input_139], Original ATen: [aten.convolution]
        buf145 = extern_kernels.convolution(buf144, primals_146, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf145, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf146 = buf145; del buf145  # reuse
        # Topologically Sorted Source Nodes: [input_139, input_140], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf146, primals_147, 32768, grid=grid(32768), stream=stream0)
        del primals_147
        # Topologically Sorted Source Nodes: [input_141], Original ATen: [aten.convolution]
        buf147 = extern_kernels.convolution(buf146, primals_148, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf147, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf148 = buf147; del buf147  # reuse
        # Topologically Sorted Source Nodes: [input_141, input_142], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf148, primals_149, 32768, grid=grid(32768), stream=stream0)
        del primals_149
        # Topologically Sorted Source Nodes: [input_143], Original ATen: [aten.convolution]
        buf149 = extern_kernels.convolution(buf148, primals_150, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf149, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf150 = buf149; del buf149  # reuse
        # Topologically Sorted Source Nodes: [input_143, input_144], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf150, primals_151, 32768, grid=grid(32768), stream=stream0)
        del primals_151
        # Topologically Sorted Source Nodes: [input_145], Original ATen: [aten.convolution]
        buf151 = extern_kernels.convolution(buf150, primals_152, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf151, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf152 = buf151; del buf151  # reuse
        # Topologically Sorted Source Nodes: [input_145, input_146], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf152, primals_153, 32768, grid=grid(32768), stream=stream0)
        del primals_153
        # Topologically Sorted Source Nodes: [input_147], Original ATen: [aten.convolution]
        buf153 = extern_kernels.convolution(buf152, primals_154, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf153, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf154 = buf153; del buf153  # reuse
        # Topologically Sorted Source Nodes: [input_147, input_148], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf154, primals_155, 32768, grid=grid(32768), stream=stream0)
        del primals_155
        # Topologically Sorted Source Nodes: [input_149], Original ATen: [aten.convolution]
        buf155 = extern_kernels.convolution(buf154, primals_156, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf155, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf156 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out6], Original ATen: [aten.cat]
        triton_poi_fused_cat_9.run(buf142, primals_143, buf155, primals_157, buf29, buf156, 47360, grid=grid(47360), stream=stream0)
        del buf142
        del buf155
        del primals_143
        del primals_157
        # Topologically Sorted Source Nodes: [input_150], Original ATen: [aten.convolution]
        buf157 = extern_kernels.convolution(buf156, primals_158, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf157, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf158 = buf157; del buf157  # reuse
        # Topologically Sorted Source Nodes: [input_150, input_151], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf158, primals_159, 32768, grid=grid(32768), stream=stream0)
        del primals_159
        # Topologically Sorted Source Nodes: [input_152], Original ATen: [aten.convolution]
        buf159 = extern_kernels.convolution(buf158, primals_160, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf159, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf160 = buf159; del buf159  # reuse
        # Topologically Sorted Source Nodes: [input_152, input_153], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf160, primals_161, 32768, grid=grid(32768), stream=stream0)
        del primals_161
        # Topologically Sorted Source Nodes: [input_154], Original ATen: [aten.convolution]
        buf161 = extern_kernels.convolution(buf160, primals_162, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf161, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf162 = buf161; del buf161  # reuse
        # Topologically Sorted Source Nodes: [input_154, input_155], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf162, primals_163, 32768, grid=grid(32768), stream=stream0)
        del primals_163
        # Topologically Sorted Source Nodes: [input_156], Original ATen: [aten.convolution]
        buf163 = extern_kernels.convolution(buf162, primals_164, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf163, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf164 = buf163; del buf163  # reuse
        # Topologically Sorted Source Nodes: [input_156, input_157], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf164, primals_165, 32768, grid=grid(32768), stream=stream0)
        del primals_165
        # Topologically Sorted Source Nodes: [input_158], Original ATen: [aten.convolution]
        buf165 = extern_kernels.convolution(buf164, primals_166, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf165, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf166 = buf165; del buf165  # reuse
        # Topologically Sorted Source Nodes: [input_158, input_159], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf166, primals_167, 32768, grid=grid(32768), stream=stream0)
        del primals_167
        # Topologically Sorted Source Nodes: [input_160], Original ATen: [aten.convolution]
        buf167 = extern_kernels.convolution(buf166, primals_168, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf167, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf168 = buf167; del buf167  # reuse
        # Topologically Sorted Source Nodes: [input_160, input_161], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf168, primals_169, 32768, grid=grid(32768), stream=stream0)
        del primals_169
        # Topologically Sorted Source Nodes: [input_162], Original ATen: [aten.convolution]
        buf169 = extern_kernels.convolution(buf168, primals_170, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf169, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf170 = buf169; del buf169  # reuse
        # Topologically Sorted Source Nodes: [input_162], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_10.run(buf170, primals_171, 9728, grid=grid(9728), stream=stream0)
        del primals_171
        # Topologically Sorted Source Nodes: [input_163], Original ATen: [aten.convolution]
        buf171 = extern_kernels.convolution(buf156, primals_172, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf171, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf172 = buf171; del buf171  # reuse
        # Topologically Sorted Source Nodes: [input_163, input_164], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf172, primals_173, 32768, grid=grid(32768), stream=stream0)
        del primals_173
        # Topologically Sorted Source Nodes: [input_165], Original ATen: [aten.convolution]
        buf173 = extern_kernels.convolution(buf172, primals_174, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf173, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf174 = buf173; del buf173  # reuse
        # Topologically Sorted Source Nodes: [input_165, input_166], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf174, primals_175, 32768, grid=grid(32768), stream=stream0)
        del primals_175
        # Topologically Sorted Source Nodes: [input_167], Original ATen: [aten.convolution]
        buf175 = extern_kernels.convolution(buf174, primals_176, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf175, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf176 = buf175; del buf175  # reuse
        # Topologically Sorted Source Nodes: [input_167, input_168], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf176, primals_177, 32768, grid=grid(32768), stream=stream0)
        del primals_177
        # Topologically Sorted Source Nodes: [input_169], Original ATen: [aten.convolution]
        buf177 = extern_kernels.convolution(buf176, primals_178, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf177, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf178 = buf177; del buf177  # reuse
        # Topologically Sorted Source Nodes: [input_169, input_170], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf178, primals_179, 32768, grid=grid(32768), stream=stream0)
        del primals_179
        # Topologically Sorted Source Nodes: [input_171], Original ATen: [aten.convolution]
        buf179 = extern_kernels.convolution(buf178, primals_180, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf179, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf180 = buf179; del buf179  # reuse
        # Topologically Sorted Source Nodes: [input_171, input_172], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf180, primals_181, 32768, grid=grid(32768), stream=stream0)
        del primals_181
        # Topologically Sorted Source Nodes: [input_173], Original ATen: [aten.convolution]
        buf181 = extern_kernels.convolution(buf180, primals_182, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf181, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf182 = buf181; del buf181  # reuse
        # Topologically Sorted Source Nodes: [input_173, input_174], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_8.run(buf182, primals_183, 32768, grid=grid(32768), stream=stream0)
        del primals_183
        # Topologically Sorted Source Nodes: [input_175], Original ATen: [aten.convolution]
        buf183 = extern_kernels.convolution(buf182, primals_184, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf183, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf184 = buf183; del buf183  # reuse
        buf185 = empty_strided_cuda((4, 19, 8, 8), (1280, 64, 8, 1), torch.bool)
        # Topologically Sorted Source Nodes: [input_175, input_176], Original ATen: [aten.convolution, aten.relu, aten.threshold_backward]
        triton_poi_fused_convolution_relu_threshold_backward_11.run(buf184, primals_185, buf185, 4864, grid=grid(4864), stream=stream0)
        del primals_185
    return (buf170, buf184, primals_1, primals_3, primals_4, primals_6, primals_8, primals_10, primals_12, primals_14, primals_16, primals_18, primals_20, primals_22, primals_24, primals_26, primals_28, primals_30, primals_32, primals_34, primals_36, primals_38, primals_40, primals_42, primals_44, primals_46, primals_48, primals_50, primals_52, primals_54, primals_56, primals_58, primals_60, primals_62, primals_64, primals_66, primals_68, primals_70, primals_72, primals_74, primals_76, primals_78, primals_80, primals_82, primals_84, primals_86, primals_88, primals_90, primals_92, primals_94, primals_96, primals_98, primals_100, primals_102, primals_104, primals_106, primals_108, primals_110, primals_112, primals_114, primals_116, primals_118, primals_120, primals_122, primals_124, primals_126, primals_128, primals_130, primals_132, primals_134, primals_136, primals_138, primals_140, primals_142, primals_144, primals_146, primals_148, primals_150, primals_152, primals_154, primals_156, primals_158, primals_160, primals_162, primals_164, primals_166, primals_168, primals_170, primals_172, primals_174, primals_176, primals_178, primals_180, primals_182, primals_184, buf1, buf3, buf4, buf5, buf7, buf9, buf10, buf11, buf13, buf15, buf17, buf19, buf20, buf21, buf23, buf25, buf27, buf29, buf31, buf33, buf35, buf37, buf40, buf42, buf44, buf46, buf48, buf50, buf52, buf54, buf56, buf58, buf60, buf63, buf65, buf67, buf69, buf71, buf73, buf75, buf77, buf79, buf81, buf83, buf85, buf87, buf90, buf92, buf94, buf96, buf98, buf100, buf102, buf104, buf106, buf108, buf110, buf112, buf114, buf117, buf119, buf121, buf123, buf125, buf127, buf129, buf131, buf133, buf135, buf137, buf139, buf141, buf144, buf146, buf148, buf150, buf152, buf154, buf156, buf158, buf160, buf162, buf164, buf166, buf168, buf172, buf174, buf176, buf178, buf180, buf182, buf185, )


def benchmark_compiled_module(times=10, repeat=10):
    from torch._dynamo.testing import rand_strided
    from torch._inductor.utils import print_performance
    primals_1 = rand_strided((64, 3, 3, 3), (27, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_2 = rand_strided((64, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_3 = rand_strided((4, 3, 64, 64), (12288, 4096, 64, 1), device='cuda:0', dtype=torch.float32)
    primals_4 = rand_strided((64, 64, 3, 3), (576, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_5 = rand_strided((64, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_6 = rand_strided((128, 64, 3, 3), (576, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_7 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_8 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_9 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_10 = rand_strided((256, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_11 = rand_strided((256, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_12 = rand_strided((256, 256, 3, 3), (2304, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_13 = rand_strided((256, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_14 = rand_strided((256, 256, 3, 3), (2304, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_15 = rand_strided((256, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_16 = rand_strided((256, 256, 3, 3), (2304, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_17 = rand_strided((256, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_18 = rand_strided((512, 256, 3, 3), (2304, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_19 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_20 = rand_strided((512, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_21 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_22 = rand_strided((256, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_23 = rand_strided((256, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_24 = rand_strided((128, 256, 3, 3), (2304, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_25 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_26 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_27 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_28 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_29 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_30 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_31 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_32 = rand_strided((512, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_33 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_34 = rand_strided((38, 512, 1, 1), (512, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_35 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_36 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_37 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_38 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_39 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_40 = rand_strided((128, 128, 3, 3), (1152, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_41 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_42 = rand_strided((512, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_43 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_44 = rand_strided((19, 512, 1, 1), (512, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_45 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_46 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_47 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_48 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_49 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_50 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_51 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_52 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_53 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_54 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_55 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_56 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_57 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_58 = rand_strided((38, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_59 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_60 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_61 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_62 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_63 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_64 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_65 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_66 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_67 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_68 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_69 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_70 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_71 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_72 = rand_strided((19, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_73 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_74 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_75 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_76 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_77 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_78 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_79 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_80 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_81 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_82 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_83 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_84 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_85 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_86 = rand_strided((38, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_87 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_88 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_89 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_90 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_91 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_92 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_93 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_94 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_95 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_96 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_97 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_98 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_99 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_100 = rand_strided((19, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_101 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_102 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_103 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_104 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_105 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_106 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_107 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_108 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_109 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_110 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_111 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_112 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_113 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_114 = rand_strided((38, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_115 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_116 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_117 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_118 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_119 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_120 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_121 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_122 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_123 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_124 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_125 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_126 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_127 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_128 = rand_strided((19, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_129 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_130 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_131 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_132 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_133 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_134 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_135 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_136 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_137 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_138 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_139 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_140 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_141 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_142 = rand_strided((38, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_143 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_144 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_145 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_146 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_147 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_148 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_149 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_150 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_151 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_152 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_153 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_154 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_155 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_156 = rand_strided((19, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_157 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_158 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_159 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_160 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_161 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_162 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_163 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_164 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_165 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_166 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_167 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_168 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_169 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_170 = rand_strided((38, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_171 = rand_strided((38, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_172 = rand_strided((128, 185, 7, 7), (9065, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_173 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_174 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_175 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_176 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_177 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_178 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_179 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_180 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_181 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_182 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_183 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_184 = rand_strided((19, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_185 = rand_strided((19, ), (1, ), device='cuda:0', dtype=torch.float32)
    fn = lambda: call([primals_1, primals_2, primals_3, primals_4, primals_5, primals_6, primals_7, primals_8, primals_9, primals_10, primals_11, primals_12, primals_13, primals_14, primals_15, primals_16, primals_17, primals_18, primals_19, primals_20, primals_21, primals_22, primals_23, primals_24, primals_25, primals_26, primals_27, primals_28, primals_29, primals_30, primals_31, primals_32, primals_33, primals_34, primals_35, primals_36, primals_37, primals_38, primals_39, primals_40, primals_41, primals_42, primals_43, primals_44, primals_45, primals_46, primals_47, primals_48, primals_49, primals_50, primals_51, primals_52, primals_53, primals_54, primals_55, primals_56, primals_57, primals_58, primals_59, primals_60, primals_61, primals_62, primals_63, primals_64, primals_65, primals_66, primals_67, primals_68, primals_69, primals_70, primals_71, primals_72, primals_73, primals_74, primals_75, primals_76, primals_77, primals_78, primals_79, primals_80, primals_81, primals_82, primals_83, primals_84, primals_85, primals_86, primals_87, primals_88, primals_89, primals_90, primals_91, primals_92, primals_93, primals_94, primals_95, primals_96, primals_97, primals_98, primals_99, primals_100, primals_101, primals_102, primals_103, primals_104, primals_105, primals_106, primals_107, primals_108, primals_109, primals_110, primals_111, primals_112, primals_113, primals_114, primals_115, primals_116, primals_117, primals_118, primals_119, primals_120, primals_121, primals_122, primals_123, primals_124, primals_125, primals_126, primals_127, primals_128, primals_129, primals_130, primals_131, primals_132, primals_133, primals_134, primals_135, primals_136, primals_137, primals_138, primals_139, primals_140, primals_141, primals_142, primals_143, primals_144, primals_145, primals_146, primals_147, primals_148, primals_149, primals_150, primals_151, primals_152, primals_153, primals_154, primals_155, primals_156, primals_157, primals_158, primals_159, primals_160, primals_161, primals_162, primals_163, primals_164, primals_165, primals_166, primals_167, primals_168, primals_169, primals_170, primals_171, primals_172, primals_173, primals_174, primals_175, primals_176, primals_177, primals_178, primals_179, primals_180, primals_181, primals_182, primals_183, primals_184, primals_185])
    return print_performance(fn, times=times, repeat=repeat)


if __name__ == "__main__":
    from torch._inductor.wrapper_benchmark import compiled_module_main
    compiled_module_main('None', benchmark_compiled_module)

import torch
import torch.nn as nn
from collections import OrderedDict


def make_layers(block, no_relu_layers):
    layers = []
    for layer_name, v in block.items():
        if 'pool' in layer_name:
            layer = nn.MaxPool2d(kernel_size=v[0], stride=v[1], padding=v[2])
            layers.append((layer_name, layer))
        else:
            conv2d = nn.Conv2d(in_channels=v[0], out_channels=v[1],
                kernel_size=v[2], stride=v[3], padding=v[4])
            layers.append((layer_name, conv2d))
            if layer_name not in no_relu_layers:
                layers.append(('relu_' + layer_name, nn.ReLU(inplace=True)))
    return nn.Sequential(OrderedDict(layers))


class bodypose_model(nn.Module):

    def __init__(self):
        super(bodypose_model, self).__init__()
        no_relu_layers = ['conv5_5_CPM_L1', 'conv5_5_CPM_L2',
            'Mconv7_stage2_L1', 'Mconv7_stage2_L2', 'Mconv7_stage3_L1',
            'Mconv7_stage3_L2', 'Mconv7_stage4_L1', 'Mconv7_stage4_L2',
            'Mconv7_stage5_L1', 'Mconv7_stage5_L2', 'Mconv7_stage6_L1',
            'Mconv7_stage6_L1']
        blocks = {}
        block0 = OrderedDict({'conv1_1': [3, 64, 3, 1, 1], 'conv1_2': [64, 
            64, 3, 1, 1], 'pool1_stage1': [2, 2, 0], 'conv2_1': [64, 128, 3,
            1, 1], 'conv2_2': [128, 128, 3, 1, 1], 'pool2_stage1': [2, 2, 0
            ], 'conv3_1': [128, 256, 3, 1, 1], 'conv3_2': [256, 256, 3, 1, 
            1], 'conv3_3': [256, 256, 3, 1, 1], 'conv3_4': [256, 256, 3, 1,
            1], 'pool3_stage1': [2, 2, 0], 'conv4_1': [256, 512, 3, 1, 1],
            'conv4_2': [512, 512, 3, 1, 1], 'conv4_3_CPM': [512, 256, 3, 1,
            1], 'conv4_4_CPM': [256, 128, 3, 1, 1]})
        block1_1 = OrderedDict({'conv5_1_CPM_L1': [128, 128, 3, 1, 1],
            'conv5_2_CPM_L1': [128, 128, 3, 1, 1], 'conv5_3_CPM_L1': [128, 
            128, 3, 1, 1], 'conv5_4_CPM_L1': [128, 512, 1, 1, 0],
            'conv5_5_CPM_L1': [512, 38, 1, 1, 0]})
        block1_2 = OrderedDict({'conv5_1_CPM_L2': [128, 128, 3, 1, 1],
            'conv5_2_CPM_L2': [128, 128, 3, 1, 1], 'conv5_3_CPM_L2': [128, 
            128, 3, 1, 1], 'conv5_4_CPM_L2': [128, 512, 1, 1, 0],
            'conv5_5_CPM_L2': [512, 19, 1, 1, 0]})
        blocks['block1_1'] = block1_1
        blocks['block1_2'] = block1_2
        self.model0 = make_layers(block0, no_relu_layers)
        for i in range(2, 7):
            blocks['block%d_1' % i] = OrderedDict({('Mconv1_stage%d_L1' % i
                ): [185, 128, 7, 1, 3], ('Mconv2_stage%d_L1' % i): [128, 
                128, 7, 1, 3], ('Mconv3_stage%d_L1' % i): [128, 128, 7, 1, 
                3], ('Mconv4_stage%d_L1' % i): [128, 128, 7, 1, 3], (
                'Mconv5_stage%d_L1' % i): [128, 128, 7, 1, 3], (
                'Mconv6_stage%d_L1' % i): [128, 128, 1, 1, 0], (
                'Mconv7_stage%d_L1' % i): [128, 38, 1, 1, 0]})
            blocks['block%d_2' % i] = OrderedDict({('Mconv1_stage%d_L2' % i
                ): [185, 128, 7, 1, 3], ('Mconv2_stage%d_L2' % i): [128, 
                128, 7, 1, 3], ('Mconv3_stage%d_L2' % i): [128, 128, 7, 1, 
                3], ('Mconv4_stage%d_L2' % i): [128, 128, 7, 1, 3], (
                'Mconv5_stage%d_L2' % i): [128, 128, 7, 1, 3], (
                'Mconv6_stage%d_L2' % i): [128, 128, 1, 1, 0], (
                'Mconv7_stage%d_L2' % i): [128, 19, 1, 1, 0]})
        for k in blocks.keys():
            blocks[k] = make_layers(blocks[k], no_relu_layers)
        self.model1_1 = blocks['block1_1']
        self.model2_1 = blocks['block2_1']
        self.model3_1 = blocks['block3_1']
        self.model4_1 = blocks['block4_1']
        self.model5_1 = blocks['block5_1']
        self.model6_1 = blocks['block6_1']
        self.model1_2 = blocks['block1_2']
        self.model2_2 = blocks['block2_2']
        self.model3_2 = blocks['block3_2']
        self.model4_2 = blocks['block4_2']
        self.model5_2 = blocks['block5_2']
        self.model6_2 = blocks['block6_2']

    def forward(self, x):
        out1 = self.model0(x)
        out1_1 = self.model1_1(out1)
        out1_2 = self.model1_2(out1)
        out2 = torch.cat([out1_1, out1_2, out1], 1)
        out2_1 = self.model2_1(out2)
        out2_2 = self.model2_2(out2)
        out3 = torch.cat([out2_1, out2_2, out1], 1)
        out3_1 = self.model3_1(out3)
        out3_2 = self.model3_2(out3)
        out4 = torch.cat([out3_1, out3_2, out1], 1)
        out4_1 = self.model4_1(out4)
        out4_2 = self.model4_2(out4)
        out5 = torch.cat([out4_1, out4_2, out1], 1)
        out5_1 = self.model5_1(out5)
        out5_2 = self.model5_2(out5)
        out6 = torch.cat([out5_1, out5_2, out1], 1)
        out6_1 = self.model6_1(out6)
        out6_2 = self.model6_2(out6)
        return out6_1, out6_2


def get_inputs():
    return [torch.rand([4, 3, 64, 64])]


def get_init_inputs():
    return [[], {}]

import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from collections import OrderedDict
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda


@triton.jit
def triton_poi_fused_convolution_relu_0(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 4096 % 64
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_1(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 32
    x1 = xindex // 32
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 128 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 128 * x1), None, eviction_policy
        ='evict_last')
    tmp3 = tl.load(in_ptr0 + (64 + 2 * x0 + 128 * x1), None,
        eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (65 + 2 * x0 + 128 * x1), None,
        eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_relu_2(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 1024 % 128
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_3(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 16
    x1 = xindex // 16
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 64 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 64 * x1), None, eviction_policy=
        'evict_last')
    tmp3 = tl.load(in_ptr0 + (32 + 2 * x0 + 64 * x1), None, eviction_policy
        ='evict_last')
    tmp5 = tl.load(in_ptr0 + (33 + 2 * x0 + 64 * x1), None, eviction_policy
        ='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_relu_4(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 256 % 256
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_5(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 8
    x1 = xindex // 8
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 32 * x1), None, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 32 * x1), None, eviction_policy=
        'evict_last')
    tmp3 = tl.load(in_ptr0 + (16 + 2 * x0 + 32 * x1), None, eviction_policy
        ='evict_last')
    tmp5 = tl.load(in_ptr0 + (17 + 2 * x0 + 32 * x1), None, eviction_policy
        ='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + x2, tmp6, None)
    tl.store(out_ptr1 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_relu_6(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 512
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_convolution_relu_7(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 256
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_convolution_relu_8(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = xindex // 64 % 128
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x3, tmp4, None)


@triton.jit
def triton_poi_fused_cat_9(in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4,
    out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 47360
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 64 % 185
    x0 = xindex % 64
    x2 = xindex // 11840
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 38, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 64 * x1 + 2432 * x2), tmp4 & xmask,
        other=0.0)
    tmp6 = tl.load(in_ptr1 + x1, tmp4 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full(tmp7.shape, 0.0, tmp7.dtype)
    tmp9 = tl.where(tmp4, tmp7, tmp8)
    tmp10 = tmp0 >= tmp3
    tmp11 = tl.full([1], 57, tl.int64)
    tmp12 = tmp0 < tmp11
    tmp13 = tmp10 & tmp12
    tmp14 = tl.load(in_ptr2 + (x0 + 64 * (-38 + x1) + 1216 * x2), tmp13 &
        xmask, other=0.0)
    tmp15 = tl.load(in_ptr3 + (-38 + x1), tmp13 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp16 = tmp14 + tmp15
    tmp17 = tl.full(tmp16.shape, 0.0, tmp16.dtype)
    tmp18 = tl.where(tmp13, tmp16, tmp17)
    tmp19 = tmp0 >= tmp11
    tl.full([1], 185, tl.int64)
    tmp22 = tl.load(in_ptr4 + (x0 + 64 * (-57 + x1) + 8192 * x2), tmp19 &
        xmask, other=0.0)
    tmp23 = tl.where(tmp13, tmp18, tmp22)
    tmp24 = tl.where(tmp4, tmp9, tmp23)
    tl.store(out_ptr0 + x3, tmp24, xmask)


@triton.jit
def triton_poi_fused_convolution_10(in_out_ptr0, in_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 9728
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 64 % 38
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_11(in_out_ptr0,
    in_ptr0, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 4864
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x4 = xindex
    x1 = xindex // 64 % 19
    x2 = xindex // 1216
    x3 = xindex % 1216
    tmp0 = tl.load(in_out_ptr0 + x4, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(in_out_ptr0 + x4, tmp4, xmask)
    tl.store(out_ptr0 + (x3 + 1280 * x2), tmp6, xmask)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9, primals_10, primals_11, primals_12,
        primals_13, primals_14, primals_15, primals_16, primals_17,
        primals_18, primals_19, primals_20, primals_21, primals_22,
        primals_23, primals_24, primals_25, primals_26, primals_27,
        primals_28, primals_29, primals_30, primals_31, primals_32,
        primals_33, primals_34, primals_35, primals_36, primals_37,
        primals_38, primals_39, primals_40, primals_41, primals_42,
        primals_43, primals_44, primals_45, primals_46, primals_47,
        primals_48, primals_49, primals_50, primals_51, primals_52,
        primals_53, primals_54, primals_55, primals_56, primals_57,
        primals_58, primals_59, primals_60, primals_61, primals_62,
        primals_63, primals_64, primals_65, primals_66, primals_67,
        primals_68, primals_69, primals_70, primals_71, primals_72,
        primals_73, primals_74, primals_75, primals_76, primals_77,
        primals_78, primals_79, primals_80, primals_81, primals_82,
        primals_83, primals_84, primals_85, primals_86, primals_87,
        primals_88, primals_89, primals_90, primals_91, primals_92,
        primals_93, primals_94, primals_95, primals_96, primals_97,
        primals_98, primals_99, primals_100, primals_101, primals_102,
        primals_103, primals_104, primals_105, primals_106, primals_107,
        primals_108, primals_109, primals_110, primals_111, primals_112,
        primals_113, primals_114, primals_115, primals_116, primals_117,
        primals_118, primals_119, primals_120, primals_121, primals_122,
        primals_123, primals_124, primals_125, primals_126, primals_127,
        primals_128, primals_129, primals_130, primals_131, primals_132,
        primals_133, primals_134, primals_135, primals_136, primals_137,
        primals_138, primals_139, primals_140, primals_141, primals_142,
        primals_143, primals_144, primals_145, primals_146, primals_147,
        primals_148, primals_149, primals_150, primals_151, primals_152,
        primals_153, primals_154, primals_155, primals_156, primals_157,
        primals_158, primals_159, primals_160, primals_161, primals_162,
        primals_163, primals_164, primals_165, primals_166, primals_167,
        primals_168, primals_169, primals_170, primals_171, primals_172,
        primals_173, primals_174, primals_175, primals_176, primals_177,
        primals_178, primals_179, primals_180, primals_181, primals_182,
        primals_183, primals_184, primals_185) = args
    args.clear()
    assert_size_stride(primals_1, (64, 3, 3, 3), (27, 9, 3, 1))
    assert_size_stride(primals_2, (64,), (1,))
    assert_size_stride(primals_3, (4, 3, 64, 64), (12288, 4096, 64, 1))
    assert_size_stride(primals_4, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_5, (64,), (1,))
    assert_size_stride(primals_6, (128, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_7, (128,), (1,))
    assert_size_stride(primals_8, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_9, (128,), (1,))
    assert_size_stride(primals_10, (256, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_11, (256,), (1,))
    assert_size_stride(primals_12, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_13, (256,), (1,))
    assert_size_stride(primals_14, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_15, (256,), (1,))
    assert_size_stride(primals_16, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_17, (256,), (1,))
    assert_size_stride(primals_18, (512, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_19, (512,), (1,))
    assert_size_stride(primals_20, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_21, (512,), (1,))
    assert_size_stride(primals_22, (256, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_23, (256,), (1,))
    assert_size_stride(primals_24, (128, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_25, (128,), (1,))
    assert_size_stride(primals_26, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_27, (128,), (1,))
    assert_size_stride(primals_28, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_29, (128,), (1,))
    assert_size_stride(primals_30, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_31, (128,), (1,))
    assert_size_stride(primals_32, (512, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_33, (512,), (1,))
    assert_size_stride(primals_34, (38, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_35, (38,), (1,))
    assert_size_stride(primals_36, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_37, (128,), (1,))
    assert_size_stride(primals_38, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_39, (128,), (1,))
    assert_size_stride(primals_40, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_41, (128,), (1,))
    assert_size_stride(primals_42, (512, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_43, (512,), (1,))
    assert_size_stride(primals_44, (19, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_45, (19,), (1,))
    assert_size_stride(primals_46, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_47, (128,), (1,))
    assert_size_stride(primals_48, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_49, (128,), (1,))
    assert_size_stride(primals_50, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_51, (128,), (1,))
    assert_size_stride(primals_52, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_53, (128,), (1,))
    assert_size_stride(primals_54, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_55, (128,), (1,))
    assert_size_stride(primals_56, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_57, (128,), (1,))
    assert_size_stride(primals_58, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_59, (38,), (1,))
    assert_size_stride(primals_60, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_61, (128,), (1,))
    assert_size_stride(primals_62, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_63, (128,), (1,))
    assert_size_stride(primals_64, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_65, (128,), (1,))
    assert_size_stride(primals_66, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_67, (128,), (1,))
    assert_size_stride(primals_68, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_69, (128,), (1,))
    assert_size_stride(primals_70, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_71, (128,), (1,))
    assert_size_stride(primals_72, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_73, (19,), (1,))
    assert_size_stride(primals_74, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_75, (128,), (1,))
    assert_size_stride(primals_76, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_77, (128,), (1,))
    assert_size_stride(primals_78, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_79, (128,), (1,))
    assert_size_stride(primals_80, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_81, (128,), (1,))
    assert_size_stride(primals_82, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_83, (128,), (1,))
    assert_size_stride(primals_84, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_85, (128,), (1,))
    assert_size_stride(primals_86, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_87, (38,), (1,))
    assert_size_stride(primals_88, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_89, (128,), (1,))
    assert_size_stride(primals_90, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_91, (128,), (1,))
    assert_size_stride(primals_92, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_93, (128,), (1,))
    assert_size_stride(primals_94, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_95, (128,), (1,))
    assert_size_stride(primals_96, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_97, (128,), (1,))
    assert_size_stride(primals_98, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_99, (128,), (1,))
    assert_size_stride(primals_100, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_101, (19,), (1,))
    assert_size_stride(primals_102, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_103, (128,), (1,))
    assert_size_stride(primals_104, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_105, (128,), (1,))
    assert_size_stride(primals_106, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_107, (128,), (1,))
    assert_size_stride(primals_108, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_109, (128,), (1,))
    assert_size_stride(primals_110, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_111, (128,), (1,))
    assert_size_stride(primals_112, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_113, (128,), (1,))
    assert_size_stride(primals_114, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_115, (38,), (1,))
    assert_size_stride(primals_116, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_117, (128,), (1,))
    assert_size_stride(primals_118, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_119, (128,), (1,))
    assert_size_stride(primals_120, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_121, (128,), (1,))
    assert_size_stride(primals_122, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_123, (128,), (1,))
    assert_size_stride(primals_124, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_125, (128,), (1,))
    assert_size_stride(primals_126, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_127, (128,), (1,))
    assert_size_stride(primals_128, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_129, (19,), (1,))
    assert_size_stride(primals_130, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_131, (128,), (1,))
    assert_size_stride(primals_132, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_133, (128,), (1,))
    assert_size_stride(primals_134, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_135, (128,), (1,))
    assert_size_stride(primals_136, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_137, (128,), (1,))
    assert_size_stride(primals_138, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_139, (128,), (1,))
    assert_size_stride(primals_140, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_141, (128,), (1,))
    assert_size_stride(primals_142, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_143, (38,), (1,))
    assert_size_stride(primals_144, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_145, (128,), (1,))
    assert_size_stride(primals_146, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_147, (128,), (1,))
    assert_size_stride(primals_148, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_149, (128,), (1,))
    assert_size_stride(primals_150, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_151, (128,), (1,))
    assert_size_stride(primals_152, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_153, (128,), (1,))
    assert_size_stride(primals_154, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_155, (128,), (1,))
    assert_size_stride(primals_156, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_157, (19,), (1,))
    assert_size_stride(primals_158, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_159, (128,), (1,))
    assert_size_stride(primals_160, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_161, (128,), (1,))
    assert_size_stride(primals_162, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_163, (128,), (1,))
    assert_size_stride(primals_164, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_165, (128,), (1,))
    assert_size_stride(primals_166, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_167, (128,), (1,))
    assert_size_stride(primals_168, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_169, (128,), (1,))
    assert_size_stride(primals_170, (38, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_171, (38,), (1,))
    assert_size_stride(primals_172, (128, 185, 7, 7), (9065, 49, 7, 1))
    assert_size_stride(primals_173, (128,), (1,))
    assert_size_stride(primals_174, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_175, (128,), (1,))
    assert_size_stride(primals_176, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_177, (128,), (1,))
    assert_size_stride(primals_178, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_179, (128,), (1,))
    assert_size_stride(primals_180, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_181, (128,), (1,))
    assert_size_stride(primals_182, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_183, (128,), (1,))
    assert_size_stride(primals_184, (19, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_185, (19,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = extern_kernels.convolution(primals_3, primals_1, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf0, (4, 64, 64, 64), (262144, 4096, 64, 1))
        buf1 = buf0
        del buf0
        get_raw_stream(0)
        triton_poi_fused_convolution_relu_0[grid(1048576)](buf1, primals_2,
            1048576, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_2
        buf2 = extern_kernels.convolution(buf1, primals_4, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf2, (4, 64, 64, 64), (262144, 4096, 64, 1))
        buf3 = buf2
        del buf2
        triton_poi_fused_convolution_relu_0[grid(1048576)](buf3, primals_5,
            1048576, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_5
        buf4 = empty_strided_cuda((4, 64, 32, 32), (65536, 1024, 32, 1),
            torch.float32)
        buf5 = empty_strided_cuda((4, 64, 32, 32), (65536, 1024, 32, 1),
            torch.int8)
        triton_poi_fused_max_pool2d_with_indices_1[grid(262144)](buf3, buf4,
            buf5, 262144, XBLOCK=512, num_warps=8, num_stages=1)
        buf6 = extern_kernels.convolution(buf4, primals_6, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf6, (4, 128, 32, 32), (131072, 1024, 32, 1))
        buf7 = buf6
        del buf6
        triton_poi_fused_convolution_relu_2[grid(524288)](buf7, primals_7, 
            524288, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_7
        buf8 = extern_kernels.convolution(buf7, primals_8, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf8, (4, 128, 32, 32), (131072, 1024, 32, 1))
        buf9 = buf8
        del buf8
        triton_poi_fused_convolution_relu_2[grid(524288)](buf9, primals_9, 
            524288, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_9
        buf10 = empty_strided_cuda((4, 128, 16, 16), (32768, 256, 16, 1),
            torch.float32)
        buf11 = empty_strided_cuda((4, 128, 16, 16), (32768, 256, 16, 1),
            torch.int8)
        triton_poi_fused_max_pool2d_with_indices_3[grid(131072)](buf9,
            buf10, buf11, 131072, XBLOCK=512, num_warps=8, num_stages=1)
        buf12 = extern_kernels.convolution(buf10, primals_10, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf12, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf13 = buf12
        del buf12
        triton_poi_fused_convolution_relu_4[grid(262144)](buf13, primals_11,
            262144, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_11
        buf14 = extern_kernels.convolution(buf13, primals_12, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf14, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf15 = buf14
        del buf14
        triton_poi_fused_convolution_relu_4[grid(262144)](buf15, primals_13,
            262144, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_13
        buf16 = extern_kernels.convolution(buf15, primals_14, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf16, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf17 = buf16
        del buf16
        triton_poi_fused_convolution_relu_4[grid(262144)](buf17, primals_15,
            262144, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_15
        buf18 = extern_kernels.convolution(buf17, primals_16, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 256, 16, 16), (65536, 256, 16, 1))
        buf19 = buf18
        del buf18
        triton_poi_fused_convolution_relu_4[grid(262144)](buf19, primals_17,
            262144, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_17
        buf20 = empty_strided_cuda((4, 256, 8, 8), (16384, 64, 8, 1), torch
            .float32)
        buf21 = empty_strided_cuda((4, 256, 8, 8), (16384, 64, 8, 1), torch
            .int8)
        triton_poi_fused_max_pool2d_with_indices_5[grid(65536)](buf19,
            buf20, buf21, 65536, XBLOCK=256, num_warps=4, num_stages=1)
        buf22 = extern_kernels.convolution(buf20, primals_18, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf22, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf23 = buf22
        del buf22
        triton_poi_fused_convolution_relu_6[grid(131072)](buf23, primals_19,
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_19
        buf24 = extern_kernels.convolution(buf23, primals_20, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf24, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf25 = buf24
        del buf24
        triton_poi_fused_convolution_relu_6[grid(131072)](buf25, primals_21,
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_21
        buf26 = extern_kernels.convolution(buf25, primals_22, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf26, (4, 256, 8, 8), (16384, 64, 8, 1))
        buf27 = buf26
        del buf26
        triton_poi_fused_convolution_relu_7[grid(65536)](buf27, primals_23,
            65536, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_23
        buf28 = extern_kernels.convolution(buf27, primals_24, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf28, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf29 = buf28
        del buf28
        triton_poi_fused_convolution_relu_8[grid(32768)](buf29, primals_25,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_25
        buf30 = extern_kernels.convolution(buf29, primals_26, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf30, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf31 = buf30
        del buf30
        triton_poi_fused_convolution_relu_8[grid(32768)](buf31, primals_27,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_27
        buf32 = extern_kernels.convolution(buf31, primals_28, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf32, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf33 = buf32
        del buf32
        triton_poi_fused_convolution_relu_8[grid(32768)](buf33, primals_29,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_29
        buf34 = extern_kernels.convolution(buf33, primals_30, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf34, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf35 = buf34
        del buf34
        triton_poi_fused_convolution_relu_8[grid(32768)](buf35, primals_31,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_31
        buf36 = extern_kernels.convolution(buf35, primals_32, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf36, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf37 = buf36
        del buf36
        triton_poi_fused_convolution_relu_6[grid(131072)](buf37, primals_33,
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_33
        buf38 = extern_kernels.convolution(buf37, primals_34, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf38, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf39 = extern_kernels.convolution(buf29, primals_36, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf39, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf40 = buf39
        del buf39
        triton_poi_fused_convolution_relu_8[grid(32768)](buf40, primals_37,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_37
        buf41 = extern_kernels.convolution(buf40, primals_38, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf41, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf42 = buf41
        del buf41
        triton_poi_fused_convolution_relu_8[grid(32768)](buf42, primals_39,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_39
        buf43 = extern_kernels.convolution(buf42, primals_40, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf43, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf44 = buf43
        del buf43
        triton_poi_fused_convolution_relu_8[grid(32768)](buf44, primals_41,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_41
        buf45 = extern_kernels.convolution(buf44, primals_42, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf45, (4, 512, 8, 8), (32768, 64, 8, 1))
        buf46 = buf45
        del buf45
        triton_poi_fused_convolution_relu_6[grid(131072)](buf46, primals_43,
            131072, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_43
        buf47 = extern_kernels.convolution(buf46, primals_44, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf47, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf48 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch
            .float32)
        triton_poi_fused_cat_9[grid(47360)](buf38, primals_35, buf47,
            primals_45, buf29, buf48, 47360, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf38
        del buf47
        del primals_35
        del primals_45
        buf49 = extern_kernels.convolution(buf48, primals_46, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf49, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf50 = buf49
        del buf49
        triton_poi_fused_convolution_relu_8[grid(32768)](buf50, primals_47,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_47
        buf51 = extern_kernels.convolution(buf50, primals_48, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf51, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf52 = buf51
        del buf51
        triton_poi_fused_convolution_relu_8[grid(32768)](buf52, primals_49,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_49
        buf53 = extern_kernels.convolution(buf52, primals_50, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf53, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf54 = buf53
        del buf53
        triton_poi_fused_convolution_relu_8[grid(32768)](buf54, primals_51,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_51
        buf55 = extern_kernels.convolution(buf54, primals_52, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf55, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf56 = buf55
        del buf55
        triton_poi_fused_convolution_relu_8[grid(32768)](buf56, primals_53,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_53
        buf57 = extern_kernels.convolution(buf56, primals_54, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf57, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf58 = buf57
        del buf57
        triton_poi_fused_convolution_relu_8[grid(32768)](buf58, primals_55,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_55
        buf59 = extern_kernels.convolution(buf58, primals_56, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf59, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf60 = buf59
        del buf59
        triton_poi_fused_convolution_relu_8[grid(32768)](buf60, primals_57,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_57
        buf61 = extern_kernels.convolution(buf60, primals_58, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf61, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf62 = extern_kernels.convolution(buf48, primals_60, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf62, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf63 = buf62
        del buf62
        triton_poi_fused_convolution_relu_8[grid(32768)](buf63, primals_61,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_61
        buf64 = extern_kernels.convolution(buf63, primals_62, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf64, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf65 = buf64
        del buf64
        triton_poi_fused_convolution_relu_8[grid(32768)](buf65, primals_63,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_63
        buf66 = extern_kernels.convolution(buf65, primals_64, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf66, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf67 = buf66
        del buf66
        triton_poi_fused_convolution_relu_8[grid(32768)](buf67, primals_65,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_65
        buf68 = extern_kernels.convolution(buf67, primals_66, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf68, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf69 = buf68
        del buf68
        triton_poi_fused_convolution_relu_8[grid(32768)](buf69, primals_67,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_67
        buf70 = extern_kernels.convolution(buf69, primals_68, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf70, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf71 = buf70
        del buf70
        triton_poi_fused_convolution_relu_8[grid(32768)](buf71, primals_69,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_69
        buf72 = extern_kernels.convolution(buf71, primals_70, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf72, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf73 = buf72
        del buf72
        triton_poi_fused_convolution_relu_8[grid(32768)](buf73, primals_71,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_71
        buf74 = extern_kernels.convolution(buf73, primals_72, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf75 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1), torch
            .float32)
        triton_poi_fused_cat_9[grid(47360)](buf61, primals_59, buf74,
            primals_73, buf29, buf75, 47360, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf61
        del buf74
        del primals_59
        del primals_73
        buf76 = extern_kernels.convolution(buf75, primals_74, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf76, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf77 = buf76
        del buf76
        triton_poi_fused_convolution_relu_8[grid(32768)](buf77, primals_75,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_75
        buf78 = extern_kernels.convolution(buf77, primals_76, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf78, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf79 = buf78
        del buf78
        triton_poi_fused_convolution_relu_8[grid(32768)](buf79, primals_77,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_77
        buf80 = extern_kernels.convolution(buf79, primals_78, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf81 = buf80
        del buf80
        triton_poi_fused_convolution_relu_8[grid(32768)](buf81, primals_79,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_79
        buf82 = extern_kernels.convolution(buf81, primals_80, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf82, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf83 = buf82
        del buf82
        triton_poi_fused_convolution_relu_8[grid(32768)](buf83, primals_81,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_81
        buf84 = extern_kernels.convolution(buf83, primals_82, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf84, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf85 = buf84
        del buf84
        triton_poi_fused_convolution_relu_8[grid(32768)](buf85, primals_83,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_83
        buf86 = extern_kernels.convolution(buf85, primals_84, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf86, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf87 = buf86
        del buf86
        triton_poi_fused_convolution_relu_8[grid(32768)](buf87, primals_85,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_85
        buf88 = extern_kernels.convolution(buf87, primals_86, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf88, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf89 = extern_kernels.convolution(buf75, primals_88, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf89, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf90 = buf89
        del buf89
        triton_poi_fused_convolution_relu_8[grid(32768)](buf90, primals_89,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_89
        buf91 = extern_kernels.convolution(buf90, primals_90, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf91, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf92 = buf91
        del buf91
        triton_poi_fused_convolution_relu_8[grid(32768)](buf92, primals_91,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_91
        buf93 = extern_kernels.convolution(buf92, primals_92, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf93, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf94 = buf93
        del buf93
        triton_poi_fused_convolution_relu_8[grid(32768)](buf94, primals_93,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_93
        buf95 = extern_kernels.convolution(buf94, primals_94, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf95, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf96 = buf95
        del buf95
        triton_poi_fused_convolution_relu_8[grid(32768)](buf96, primals_95,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_95
        buf97 = extern_kernels.convolution(buf96, primals_96, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf97, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf98 = buf97
        del buf97
        triton_poi_fused_convolution_relu_8[grid(32768)](buf98, primals_97,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_97
        buf99 = extern_kernels.convolution(buf98, primals_98, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf99, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf100 = buf99
        del buf99
        triton_poi_fused_convolution_relu_8[grid(32768)](buf100, primals_99,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_99
        buf101 = extern_kernels.convolution(buf100, primals_100, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf101, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf102 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1),
            torch.float32)
        triton_poi_fused_cat_9[grid(47360)](buf88, primals_87, buf101,
            primals_101, buf29, buf102, 47360, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf101
        del buf88
        del primals_101
        del primals_87
        buf103 = extern_kernels.convolution(buf102, primals_102, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf103, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf104 = buf103
        del buf103
        triton_poi_fused_convolution_relu_8[grid(32768)](buf104,
            primals_103, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_103
        buf105 = extern_kernels.convolution(buf104, primals_104, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf105, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf106 = buf105
        del buf105
        triton_poi_fused_convolution_relu_8[grid(32768)](buf106,
            primals_105, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_105
        buf107 = extern_kernels.convolution(buf106, primals_106, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf107, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf108 = buf107
        del buf107
        triton_poi_fused_convolution_relu_8[grid(32768)](buf108,
            primals_107, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_107
        buf109 = extern_kernels.convolution(buf108, primals_108, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf109, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf110 = buf109
        del buf109
        triton_poi_fused_convolution_relu_8[grid(32768)](buf110,
            primals_109, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_109
        buf111 = extern_kernels.convolution(buf110, primals_110, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf111, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf112 = buf111
        del buf111
        triton_poi_fused_convolution_relu_8[grid(32768)](buf112,
            primals_111, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_111
        buf113 = extern_kernels.convolution(buf112, primals_112, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf113, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf114 = buf113
        del buf113
        triton_poi_fused_convolution_relu_8[grid(32768)](buf114,
            primals_113, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_113
        buf115 = extern_kernels.convolution(buf114, primals_114, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf115, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf116 = extern_kernels.convolution(buf102, primals_116, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf116, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf117 = buf116
        del buf116
        triton_poi_fused_convolution_relu_8[grid(32768)](buf117,
            primals_117, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_117
        buf118 = extern_kernels.convolution(buf117, primals_118, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf118, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf119 = buf118
        del buf118
        triton_poi_fused_convolution_relu_8[grid(32768)](buf119,
            primals_119, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_119
        buf120 = extern_kernels.convolution(buf119, primals_120, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf120, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf121 = buf120
        del buf120
        triton_poi_fused_convolution_relu_8[grid(32768)](buf121,
            primals_121, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_121
        buf122 = extern_kernels.convolution(buf121, primals_122, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf122, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf123 = buf122
        del buf122
        triton_poi_fused_convolution_relu_8[grid(32768)](buf123,
            primals_123, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_123
        buf124 = extern_kernels.convolution(buf123, primals_124, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf124, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf125 = buf124
        del buf124
        triton_poi_fused_convolution_relu_8[grid(32768)](buf125,
            primals_125, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_125
        buf126 = extern_kernels.convolution(buf125, primals_126, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf126, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf127 = buf126
        del buf126
        triton_poi_fused_convolution_relu_8[grid(32768)](buf127,
            primals_127, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_127
        buf128 = extern_kernels.convolution(buf127, primals_128, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf128, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf129 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1),
            torch.float32)
        triton_poi_fused_cat_9[grid(47360)](buf115, primals_115, buf128,
            primals_129, buf29, buf129, 47360, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf115
        del buf128
        del primals_115
        del primals_129
        buf130 = extern_kernels.convolution(buf129, primals_130, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf130, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf131 = buf130
        del buf130
        triton_poi_fused_convolution_relu_8[grid(32768)](buf131,
            primals_131, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_131
        buf132 = extern_kernels.convolution(buf131, primals_132, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf132, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf133 = buf132
        del buf132
        triton_poi_fused_convolution_relu_8[grid(32768)](buf133,
            primals_133, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_133
        buf134 = extern_kernels.convolution(buf133, primals_134, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf134, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf135 = buf134
        del buf134
        triton_poi_fused_convolution_relu_8[grid(32768)](buf135,
            primals_135, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_135
        buf136 = extern_kernels.convolution(buf135, primals_136, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf136, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf137 = buf136
        del buf136
        triton_poi_fused_convolution_relu_8[grid(32768)](buf137,
            primals_137, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_137
        buf138 = extern_kernels.convolution(buf137, primals_138, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf138, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf139 = buf138
        del buf138
        triton_poi_fused_convolution_relu_8[grid(32768)](buf139,
            primals_139, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_139
        buf140 = extern_kernels.convolution(buf139, primals_140, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf140, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf141 = buf140
        del buf140
        triton_poi_fused_convolution_relu_8[grid(32768)](buf141,
            primals_141, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_141
        buf142 = extern_kernels.convolution(buf141, primals_142, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf142, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf143 = extern_kernels.convolution(buf129, primals_144, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf143, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf144 = buf143
        del buf143
        triton_poi_fused_convolution_relu_8[grid(32768)](buf144,
            primals_145, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_145
        buf145 = extern_kernels.convolution(buf144, primals_146, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf145, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf146 = buf145
        del buf145
        triton_poi_fused_convolution_relu_8[grid(32768)](buf146,
            primals_147, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_147
        buf147 = extern_kernels.convolution(buf146, primals_148, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf147, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf148 = buf147
        del buf147
        triton_poi_fused_convolution_relu_8[grid(32768)](buf148,
            primals_149, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_149
        buf149 = extern_kernels.convolution(buf148, primals_150, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf149, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf150 = buf149
        del buf149
        triton_poi_fused_convolution_relu_8[grid(32768)](buf150,
            primals_151, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_151
        buf151 = extern_kernels.convolution(buf150, primals_152, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf151, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf152 = buf151
        del buf151
        triton_poi_fused_convolution_relu_8[grid(32768)](buf152,
            primals_153, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_153
        buf153 = extern_kernels.convolution(buf152, primals_154, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf153, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf154 = buf153
        del buf153
        triton_poi_fused_convolution_relu_8[grid(32768)](buf154,
            primals_155, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_155
        buf155 = extern_kernels.convolution(buf154, primals_156, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf155, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf156 = empty_strided_cuda((4, 185, 8, 8), (11840, 64, 8, 1),
            torch.float32)
        triton_poi_fused_cat_9[grid(47360)](buf142, primals_143, buf155,
            primals_157, buf29, buf156, 47360, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf142
        del buf155
        del primals_143
        del primals_157
        buf157 = extern_kernels.convolution(buf156, primals_158, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf157, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf158 = buf157
        del buf157
        triton_poi_fused_convolution_relu_8[grid(32768)](buf158,
            primals_159, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_159
        buf159 = extern_kernels.convolution(buf158, primals_160, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf159, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf160 = buf159
        del buf159
        triton_poi_fused_convolution_relu_8[grid(32768)](buf160,
            primals_161, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_161
        buf161 = extern_kernels.convolution(buf160, primals_162, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf161, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf162 = buf161
        del buf161
        triton_poi_fused_convolution_relu_8[grid(32768)](buf162,
            primals_163, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_163
        buf163 = extern_kernels.convolution(buf162, primals_164, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf163, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf164 = buf163
        del buf163
        triton_poi_fused_convolution_relu_8[grid(32768)](buf164,
            primals_165, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_165
        buf165 = extern_kernels.convolution(buf164, primals_166, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf165, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf166 = buf165
        del buf165
        triton_poi_fused_convolution_relu_8[grid(32768)](buf166,
            primals_167, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_167
        buf167 = extern_kernels.convolution(buf166, primals_168, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf167, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf168 = buf167
        del buf167
        triton_poi_fused_convolution_relu_8[grid(32768)](buf168,
            primals_169, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_169
        buf169 = extern_kernels.convolution(buf168, primals_170, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf169, (4, 38, 8, 8), (2432, 64, 8, 1))
        buf170 = buf169
        del buf169
        triton_poi_fused_convolution_10[grid(9728)](buf170, primals_171, 
            9728, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_171
        buf171 = extern_kernels.convolution(buf156, primals_172, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf171, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf172 = buf171
        del buf171
        triton_poi_fused_convolution_relu_8[grid(32768)](buf172,
            primals_173, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_173
        buf173 = extern_kernels.convolution(buf172, primals_174, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf173, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf174 = buf173
        del buf173
        triton_poi_fused_convolution_relu_8[grid(32768)](buf174,
            primals_175, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_175
        buf175 = extern_kernels.convolution(buf174, primals_176, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf175, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf176 = buf175
        del buf175
        triton_poi_fused_convolution_relu_8[grid(32768)](buf176,
            primals_177, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_177
        buf177 = extern_kernels.convolution(buf176, primals_178, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf177, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf178 = buf177
        del buf177
        triton_poi_fused_convolution_relu_8[grid(32768)](buf178,
            primals_179, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_179
        buf179 = extern_kernels.convolution(buf178, primals_180, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf179, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf180 = buf179
        del buf179
        triton_poi_fused_convolution_relu_8[grid(32768)](buf180,
            primals_181, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_181
        buf181 = extern_kernels.convolution(buf180, primals_182, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf181, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf182 = buf181
        del buf181
        triton_poi_fused_convolution_relu_8[grid(32768)](buf182,
            primals_183, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_183
        buf183 = extern_kernels.convolution(buf182, primals_184, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf183, (4, 19, 8, 8), (1216, 64, 8, 1))
        buf184 = buf183
        del buf183
        buf185 = empty_strided_cuda((4, 19, 8, 8), (1280, 64, 8, 1), torch.bool
            )
        triton_poi_fused_convolution_relu_threshold_backward_11[grid(4864)](
            buf184, primals_185, buf185, 4864, XBLOCK=256, num_warps=4,
            num_stages=1)
        del primals_185
    return (buf170, buf184, primals_1, primals_3, primals_4, primals_6,
        primals_8, primals_10, primals_12, primals_14, primals_16,
        primals_18, primals_20, primals_22, primals_24, primals_26,
        primals_28, primals_30, primals_32, primals_34, primals_36,
        primals_38, primals_40, primals_42, primals_44, primals_46,
        primals_48, primals_50, primals_52, primals_54, primals_56,
        primals_58, primals_60, primals_62, primals_64, primals_66,
        primals_68, primals_70, primals_72, primals_74, primals_76,
        primals_78, primals_80, primals_82, primals_84, primals_86,
        primals_88, primals_90, primals_92, primals_94, primals_96,
        primals_98, primals_100, primals_102, primals_104, primals_106,
        primals_108, primals_110, primals_112, primals_114, primals_116,
        primals_118, primals_120, primals_122, primals_124, primals_126,
        primals_128, primals_130, primals_132, primals_134, primals_136,
        primals_138, primals_140, primals_142, primals_144, primals_146,
        primals_148, primals_150, primals_152, primals_154, primals_156,
        primals_158, primals_160, primals_162, primals_164, primals_166,
        primals_168, primals_170, primals_172, primals_174, primals_176,
        primals_178, primals_180, primals_182, primals_184, buf1, buf3,
        buf4, buf5, buf7, buf9, buf10, buf11, buf13, buf15, buf17, buf19,
        buf20, buf21, buf23, buf25, buf27, buf29, buf31, buf33, buf35,
        buf37, buf40, buf42, buf44, buf46, buf48, buf50, buf52, buf54,
        buf56, buf58, buf60, buf63, buf65, buf67, buf69, buf71, buf73,
        buf75, buf77, buf79, buf81, buf83, buf85, buf87, buf90, buf92,
        buf94, buf96, buf98, buf100, buf102, buf104, buf106, buf108, buf110,
        buf112, buf114, buf117, buf119, buf121, buf123, buf125, buf127,
        buf129, buf131, buf133, buf135, buf137, buf139, buf141, buf144,
        buf146, buf148, buf150, buf152, buf154, buf156, buf158, buf160,
        buf162, buf164, buf166, buf168, buf172, buf174, buf176, buf178,
        buf180, buf182, buf185)


def make_layers(block, no_relu_layers):
    layers = []
    for layer_name, v in block.items():
        if 'pool' in layer_name:
            layer = nn.MaxPool2d(kernel_size=v[0], stride=v[1], padding=v[2])
            layers.append((layer_name, layer))
        else:
            conv2d = nn.Conv2d(in_channels=v[0], out_channels=v[1],
                kernel_size=v[2], stride=v[3], padding=v[4])
            layers.append((layer_name, conv2d))
            if layer_name not in no_relu_layers:
                layers.append(('relu_' + layer_name, nn.ReLU(inplace=True)))
    return nn.Sequential(OrderedDict(layers))


class bodypose_modelNew(nn.Module):

    def __init__(self):
        super(bodypose_modelNew, self).__init__()
        no_relu_layers = ['conv5_5_CPM_L1', 'conv5_5_CPM_L2',
            'Mconv7_stage2_L1', 'Mconv7_stage2_L2', 'Mconv7_stage3_L1',
            'Mconv7_stage3_L2', 'Mconv7_stage4_L1', 'Mconv7_stage4_L2',
            'Mconv7_stage5_L1', 'Mconv7_stage5_L2', 'Mconv7_stage6_L1',
            'Mconv7_stage6_L1']
        blocks = {}
        block0 = OrderedDict({'conv1_1': [3, 64, 3, 1, 1], 'conv1_2': [64, 
            64, 3, 1, 1], 'pool1_stage1': [2, 2, 0], 'conv2_1': [64, 128, 3,
            1, 1], 'conv2_2': [128, 128, 3, 1, 1], 'pool2_stage1': [2, 2, 0
            ], 'conv3_1': [128, 256, 3, 1, 1], 'conv3_2': [256, 256, 3, 1, 
            1], 'conv3_3': [256, 256, 3, 1, 1], 'conv3_4': [256, 256, 3, 1,
            1], 'pool3_stage1': [2, 2, 0], 'conv4_1': [256, 512, 3, 1, 1],
            'conv4_2': [512, 512, 3, 1, 1], 'conv4_3_CPM': [512, 256, 3, 1,
            1], 'conv4_4_CPM': [256, 128, 3, 1, 1]})
        block1_1 = OrderedDict({'conv5_1_CPM_L1': [128, 128, 3, 1, 1],
            'conv5_2_CPM_L1': [128, 128, 3, 1, 1], 'conv5_3_CPM_L1': [128, 
            128, 3, 1, 1], 'conv5_4_CPM_L1': [128, 512, 1, 1, 0],
            'conv5_5_CPM_L1': [512, 38, 1, 1, 0]})
        block1_2 = OrderedDict({'conv5_1_CPM_L2': [128, 128, 3, 1, 1],
            'conv5_2_CPM_L2': [128, 128, 3, 1, 1], 'conv5_3_CPM_L2': [128, 
            128, 3, 1, 1], 'conv5_4_CPM_L2': [128, 512, 1, 1, 0],
            'conv5_5_CPM_L2': [512, 19, 1, 1, 0]})
        blocks['block1_1'] = block1_1
        blocks['block1_2'] = block1_2
        self.model0 = make_layers(block0, no_relu_layers)
        for i in range(2, 7):
            blocks['block%d_1' % i] = OrderedDict({('Mconv1_stage%d_L1' % i
                ): [185, 128, 7, 1, 3], ('Mconv2_stage%d_L1' % i): [128, 
                128, 7, 1, 3], ('Mconv3_stage%d_L1' % i): [128, 128, 7, 1, 
                3], ('Mconv4_stage%d_L1' % i): [128, 128, 7, 1, 3], (
                'Mconv5_stage%d_L1' % i): [128, 128, 7, 1, 3], (
                'Mconv6_stage%d_L1' % i): [128, 128, 1, 1, 0], (
                'Mconv7_stage%d_L1' % i): [128, 38, 1, 1, 0]})
            blocks['block%d_2' % i] = OrderedDict({('Mconv1_stage%d_L2' % i
                ): [185, 128, 7, 1, 3], ('Mconv2_stage%d_L2' % i): [128, 
                128, 7, 1, 3], ('Mconv3_stage%d_L2' % i): [128, 128, 7, 1, 
                3], ('Mconv4_stage%d_L2' % i): [128, 128, 7, 1, 3], (
                'Mconv5_stage%d_L2' % i): [128, 128, 7, 1, 3], (
                'Mconv6_stage%d_L2' % i): [128, 128, 1, 1, 0], (
                'Mconv7_stage%d_L2' % i): [128, 19, 1, 1, 0]})
        for k in blocks.keys():
            blocks[k] = make_layers(blocks[k], no_relu_layers)
        self.model1_1 = blocks['block1_1']
        self.model2_1 = blocks['block2_1']
        self.model3_1 = blocks['block3_1']
        self.model4_1 = blocks['block4_1']
        self.model5_1 = blocks['block5_1']
        self.model6_1 = blocks['block6_1']
        self.model1_2 = blocks['block1_2']
        self.model2_2 = blocks['block2_2']
        self.model3_2 = blocks['block3_2']
        self.model4_2 = blocks['block4_2']
        self.model5_2 = blocks['block5_2']
        self.model6_2 = blocks['block6_2']

    def forward(self, input_0):
        primals_1 = self.model0.conv1_1.weight
        primals_2 = self.model0.conv1_1.bias
        primals_4 = self.model0.conv1_2.weight
        primals_5 = self.model0.conv1_2.bias
        primals_6 = self.model0.conv2_1.weight
        primals_7 = self.model0.conv2_1.bias
        primals_8 = self.model0.conv2_2.weight
        primals_9 = self.model0.conv2_2.bias
        primals_10 = self.model0.conv3_1.weight
        primals_11 = self.model0.conv3_1.bias
        primals_12 = self.model0.conv3_2.weight
        primals_13 = self.model0.conv3_2.bias
        primals_14 = self.model0.conv3_3.weight
        primals_15 = self.model0.conv3_3.bias
        primals_16 = self.model0.conv3_4.weight
        primals_17 = self.model0.conv3_4.bias
        primals_18 = self.model0.conv4_1.weight
        primals_19 = self.model0.conv4_1.bias
        primals_20 = self.model0.conv4_2.weight
        primals_21 = self.model0.conv4_2.bias
        primals_22 = self.model0.conv4_3_CPM.weight
        primals_23 = self.model0.conv4_3_CPM.bias
        primals_24 = self.model0.conv4_4_CPM.weight
        primals_25 = self.model0.conv4_4_CPM.bias
        primals_26 = self.model1_1.conv5_1_CPM_L1.weight
        primals_27 = self.model1_1.conv5_1_CPM_L1.bias
        primals_28 = self.model1_1.conv5_2_CPM_L1.weight
        primals_29 = self.model1_1.conv5_2_CPM_L1.bias
        primals_30 = self.model1_1.conv5_3_CPM_L1.weight
        primals_31 = self.model1_1.conv5_3_CPM_L1.bias
        primals_32 = self.model1_1.conv5_4_CPM_L1.weight
        primals_33 = self.model1_1.conv5_4_CPM_L1.bias
        primals_34 = self.model1_1.conv5_5_CPM_L1.weight
        primals_35 = self.model1_1.conv5_5_CPM_L1.bias
        primals_46 = self.model2_1.Mconv1_stage2_L1.weight
        primals_37 = self.model2_1.Mconv1_stage2_L1.bias
        primals_48 = self.model2_1.Mconv2_stage2_L1.weight
        primals_39 = self.model2_1.Mconv2_stage2_L1.bias
        primals_50 = self.model2_1.Mconv3_stage2_L1.weight
        primals_41 = self.model2_1.Mconv3_stage2_L1.bias
        primals_52 = self.model2_1.Mconv4_stage2_L1.weight
        primals_47 = self.model2_1.Mconv4_stage2_L1.bias
        primals_54 = self.model2_1.Mconv5_stage2_L1.weight
        primals_49 = self.model2_1.Mconv5_stage2_L1.bias
        primals_56 = self.model2_1.Mconv6_stage2_L1.weight
        primals_51 = self.model2_1.Mconv6_stage2_L1.bias
        primals_58 = self.model2_1.Mconv7_stage2_L1.weight
        primals_59 = self.model2_1.Mconv7_stage2_L1.bias
        primals_60 = self.model3_1.Mconv1_stage3_L1.weight
        primals_53 = self.model3_1.Mconv1_stage3_L1.bias
        primals_62 = self.model3_1.Mconv2_stage3_L1.weight
        primals_55 = self.model3_1.Mconv2_stage3_L1.bias
        primals_64 = self.model3_1.Mconv3_stage3_L1.weight
        primals_57 = self.model3_1.Mconv3_stage3_L1.bias
        primals_66 = self.model3_1.Mconv4_stage3_L1.weight
        primals_61 = self.model3_1.Mconv4_stage3_L1.bias
        primals_68 = self.model3_1.Mconv5_stage3_L1.weight
        primals_63 = self.model3_1.Mconv5_stage3_L1.bias
        primals_70 = self.model3_1.Mconv6_stage3_L1.weight
        primals_65 = self.model3_1.Mconv6_stage3_L1.bias
        primals_86 = self.model3_1.Mconv7_stage3_L1.weight
        primals_87 = self.model3_1.Mconv7_stage3_L1.bias
        primals_74 = self.model4_1.Mconv1_stage4_L1.weight
        primals_67 = self.model4_1.Mconv1_stage4_L1.bias
        primals_76 = self.model4_1.Mconv2_stage4_L1.weight
        primals_69 = self.model4_1.Mconv2_stage4_L1.bias
        primals_78 = self.model4_1.Mconv3_stage4_L1.weight
        primals_71 = self.model4_1.Mconv3_stage4_L1.bias
        primals_80 = self.model4_1.Mconv4_stage4_L1.weight
        primals_75 = self.model4_1.Mconv4_stage4_L1.bias
        primals_82 = self.model4_1.Mconv5_stage4_L1.weight
        primals_77 = self.model4_1.Mconv5_stage4_L1.bias
        primals_84 = self.model4_1.Mconv6_stage4_L1.weight
        primals_79 = self.model4_1.Mconv6_stage4_L1.bias
        primals_114 = self.model4_1.Mconv7_stage4_L1.weight
        primals_115 = self.model4_1.Mconv7_stage4_L1.bias
        primals_88 = self.model5_1.Mconv1_stage5_L1.weight
        primals_81 = self.model5_1.Mconv1_stage5_L1.bias
        primals_90 = self.model5_1.Mconv2_stage5_L1.weight
        primals_83 = self.model5_1.Mconv2_stage5_L1.bias
        primals_92 = self.model5_1.Mconv3_stage5_L1.weight
        primals_85 = self.model5_1.Mconv3_stage5_L1.bias
        primals_94 = self.model5_1.Mconv4_stage5_L1.weight
        primals_89 = self.model5_1.Mconv4_stage5_L1.bias
        primals_96 = self.model5_1.Mconv5_stage5_L1.weight
        primals_91 = self.model5_1.Mconv5_stage5_L1.bias
        primals_98 = self.model5_1.Mconv6_stage5_L1.weight
        primals_93 = self.model5_1.Mconv6_stage5_L1.bias
        primals_142 = self.model5_1.Mconv7_stage5_L1.weight
        primals_143 = self.model5_1.Mconv7_stage5_L1.bias
        primals_102 = self.model6_1.Mconv1_stage6_L1.weight
        primals_95 = self.model6_1.Mconv1_stage6_L1.bias
        primals_104 = self.model6_1.Mconv2_stage6_L1.weight
        primals_97 = self.model6_1.Mconv2_stage6_L1.bias
        primals_106 = self.model6_1.Mconv3_stage6_L1.weight
        primals_99 = self.model6_1.Mconv3_stage6_L1.bias
        primals_108 = self.model6_1.Mconv4_stage6_L1.weight
        primals_103 = self.model6_1.Mconv4_stage6_L1.bias
        primals_110 = self.model6_1.Mconv5_stage6_L1.weight
        primals_105 = self.model6_1.Mconv5_stage6_L1.bias
        primals_112 = self.model6_1.Mconv6_stage6_L1.weight
        primals_107 = self.model6_1.Mconv6_stage6_L1.bias
        primals_170 = self.model6_1.Mconv7_stage6_L1.weight
        primals_171 = self.model6_1.Mconv7_stage6_L1.bias
        primals_36 = self.model1_2.conv5_1_CPM_L2.weight
        primals_109 = self.model1_2.conv5_1_CPM_L2.bias
        primals_38 = self.model1_2.conv5_2_CPM_L2.weight
        primals_111 = self.model1_2.conv5_2_CPM_L2.bias
        primals_40 = self.model1_2.conv5_3_CPM_L2.weight
        primals_113 = self.model1_2.conv5_3_CPM_L2.bias
        primals_42 = self.model1_2.conv5_4_CPM_L2.weight
        primals_43 = self.model1_2.conv5_4_CPM_L2.bias
        primals_44 = self.model1_2.conv5_5_CPM_L2.weight
        primals_45 = self.model1_2.conv5_5_CPM_L2.bias
        primals_116 = self.model2_2.Mconv1_stage2_L2.weight
        primals_117 = self.model2_2.Mconv1_stage2_L2.bias
        primals_118 = self.model2_2.Mconv2_stage2_L2.weight
        primals_119 = self.model2_2.Mconv2_stage2_L2.bias
        primals_120 = self.model2_2.Mconv3_stage2_L2.weight
        primals_121 = self.model2_2.Mconv3_stage2_L2.bias
        primals_122 = self.model2_2.Mconv4_stage2_L2.weight
        primals_123 = self.model2_2.Mconv4_stage2_L2.bias
        primals_124 = self.model2_2.Mconv5_stage2_L2.weight
        primals_125 = self.model2_2.Mconv5_stage2_L2.bias
        primals_126 = self.model2_2.Mconv6_stage2_L2.weight
        primals_127 = self.model2_2.Mconv6_stage2_L2.bias
        primals_72 = self.model2_2.Mconv7_stage2_L2.weight
        primals_73 = self.model2_2.Mconv7_stage2_L2.bias
        primals_130 = self.model3_2.Mconv1_stage3_L2.weight
        primals_131 = self.model3_2.Mconv1_stage3_L2.bias
        primals_132 = self.model3_2.Mconv2_stage3_L2.weight
        primals_133 = self.model3_2.Mconv2_stage3_L2.bias
        primals_134 = self.model3_2.Mconv3_stage3_L2.weight
        primals_135 = self.model3_2.Mconv3_stage3_L2.bias
        primals_136 = self.model3_2.Mconv4_stage3_L2.weight
        primals_137 = self.model3_2.Mconv4_stage3_L2.bias
        primals_138 = self.model3_2.Mconv5_stage3_L2.weight
        primals_139 = self.model3_2.Mconv5_stage3_L2.bias
        primals_140 = self.model3_2.Mconv6_stage3_L2.weight
        primals_141 = self.model3_2.Mconv6_stage3_L2.bias
        primals_100 = self.model3_2.Mconv7_stage3_L2.weight
        primals_101 = self.model3_2.Mconv7_stage3_L2.bias
        primals_144 = self.model4_2.Mconv1_stage4_L2.weight
        primals_145 = self.model4_2.Mconv1_stage4_L2.bias
        primals_146 = self.model4_2.Mconv2_stage4_L2.weight
        primals_147 = self.model4_2.Mconv2_stage4_L2.bias
        primals_148 = self.model4_2.Mconv3_stage4_L2.weight
        primals_149 = self.model4_2.Mconv3_stage4_L2.bias
        primals_150 = self.model4_2.Mconv4_stage4_L2.weight
        primals_151 = self.model4_2.Mconv4_stage4_L2.bias
        primals_152 = self.model4_2.Mconv5_stage4_L2.weight
        primals_153 = self.model4_2.Mconv5_stage4_L2.bias
        primals_154 = self.model4_2.Mconv6_stage4_L2.weight
        primals_155 = self.model4_2.Mconv6_stage4_L2.bias
        primals_128 = self.model4_2.Mconv7_stage4_L2.weight
        primals_129 = self.model4_2.Mconv7_stage4_L2.bias
        primals_158 = self.model5_2.Mconv1_stage5_L2.weight
        primals_159 = self.model5_2.Mconv1_stage5_L2.bias
        primals_160 = self.model5_2.Mconv2_stage5_L2.weight
        primals_161 = self.model5_2.Mconv2_stage5_L2.bias
        primals_162 = self.model5_2.Mconv3_stage5_L2.weight
        primals_163 = self.model5_2.Mconv3_stage5_L2.bias
        primals_164 = self.model5_2.Mconv4_stage5_L2.weight
        primals_165 = self.model5_2.Mconv4_stage5_L2.bias
        primals_166 = self.model5_2.Mconv5_stage5_L2.weight
        primals_167 = self.model5_2.Mconv5_stage5_L2.bias
        primals_168 = self.model5_2.Mconv6_stage5_L2.weight
        primals_169 = self.model5_2.Mconv6_stage5_L2.bias
        primals_156 = self.model5_2.Mconv7_stage5_L2.weight
        primals_157 = self.model5_2.Mconv7_stage5_L2.bias
        primals_172 = self.model6_2.Mconv1_stage6_L2.weight
        primals_173 = self.model6_2.Mconv1_stage6_L2.bias
        primals_174 = self.model6_2.Mconv2_stage6_L2.weight
        primals_175 = self.model6_2.Mconv2_stage6_L2.bias
        primals_176 = self.model6_2.Mconv3_stage6_L2.weight
        primals_177 = self.model6_2.Mconv3_stage6_L2.bias
        primals_178 = self.model6_2.Mconv4_stage6_L2.weight
        primals_179 = self.model6_2.Mconv4_stage6_L2.bias
        primals_180 = self.model6_2.Mconv5_stage6_L2.weight
        primals_181 = self.model6_2.Mconv5_stage6_L2.bias
        primals_182 = self.model6_2.Mconv6_stage6_L2.weight
        primals_183 = self.model6_2.Mconv6_stage6_L2.bias
        primals_184 = self.model6_2.Mconv7_stage6_L2.weight
        primals_185 = self.model6_2.Mconv7_stage6_L2.bias
        primals_3 = input_0
        output = call([primals_1, primals_2, primals_3, primals_4,
            primals_5, primals_6, primals_7, primals_8, primals_9,
            primals_10, primals_11, primals_12, primals_13, primals_14,
            primals_15, primals_16, primals_17, primals_18, primals_19,
            primals_20, primals_21, primals_22, primals_23, primals_24,
            primals_25, primals_26, primals_27, primals_28, primals_29,
            primals_30, primals_31, primals_32, primals_33, primals_34,
            primals_35, primals_36, primals_37, primals_38, primals_39,
            primals_40, primals_41, primals_42, primals_43, primals_44,
            primals_45, primals_46, primals_47, primals_48, primals_49,
            primals_50, primals_51, primals_52, primals_53, primals_54,
            primals_55, primals_56, primals_57, primals_58, primals_59,
            primals_60, primals_61, primals_62, primals_63, primals_64,
            primals_65, primals_66, primals_67, primals_68, primals_69,
            primals_70, primals_71, primals_72, primals_73, primals_74,
            primals_75, primals_76, primals_77, primals_78, primals_79,
            primals_80, primals_81, primals_82, primals_83, primals_84,
            primals_85, primals_86, primals_87, primals_88, primals_89,
            primals_90, primals_91, primals_92, primals_93, primals_94,
            primals_95, primals_96, primals_97, primals_98, primals_99,
            primals_100, primals_101, primals_102, primals_103, primals_104,
            primals_105, primals_106, primals_107, primals_108, primals_109,
            primals_110, primals_111, primals_112, primals_113, primals_114,
            primals_115, primals_116, primals_117, primals_118, primals_119,
            primals_120, primals_121, primals_122, primals_123, primals_124,
            primals_125, primals_126, primals_127, primals_128, primals_129,
            primals_130, primals_131, primals_132, primals_133, primals_134,
            primals_135, primals_136, primals_137, primals_138, primals_139,
            primals_140, primals_141, primals_142, primals_143, primals_144,
            primals_145, primals_146, primals_147, primals_148, primals_149,
            primals_150, primals_151, primals_152, primals_153, primals_154,
            primals_155, primals_156, primals_157, primals_158, primals_159,
            primals_160, primals_161, primals_162, primals_163, primals_164,
            primals_165, primals_166, primals_167, primals_168, primals_169,
            primals_170, primals_171, primals_172, primals_173, primals_174,
            primals_175, primals_176, primals_177, primals_178, primals_179,
            primals_180, primals_181, primals_182, primals_183, primals_184,
            primals_185])
        return output[0], output[1]
