# 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_4/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_4/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_4/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_4/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_4/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_4/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_4/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_4/inductor_cache/ov/cov3g4rc4rmbgih23oi4qbun3myxq5x4l4spx5ngdmvrw7mfidzw.py
# Topologically Sorted Source Nodes: [input_32, input_33], Original ATen: [aten.convolution, aten.relu]
# Source node to ATen node mapping:
#   input_32 => convolution_14
#   input_33 => relu_14
# Graph fragment:
#   %convolution_14 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_13, %primals_30, %primals_31, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %relu_14 : [num_users=7] = call_function[target=torch.ops.aten.relu.default](args = (%convolution_14,), 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=[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_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 = 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_4/inductor_cache/2l/c2lprdrvgsmpqu6muadzkrs3tpw6suweqvi5ahmro37gpfvqpt4p.py
# Topologically Sorted Source Nodes: [concat_stage2], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   concat_stage2 => cat
# Graph fragment:
#   %cat : [num_users=2] = call_function[target=torch.ops.aten.cat.default](args = ([%convolution_16, %relu_14], 1), kwargs = {})
triton_poi_fused_cat_8 = async_compile.triton('triton_poi_fused_cat_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=[65536], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*fp32', 3: '*fp32', 4: '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), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_cat_8', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 3, '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_8(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 38400
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = (xindex // 64) % 150
    x0 = xindex % 64
    x2 = (xindex // 9600)
    x3 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 22, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + (64*x1) + (1408*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], 150, tl.int64)
    tmp12 = tmp0 < tmp11
    tmp13 = tl.load(in_ptr2 + (x0 + (64*((-22) + x1)) + (8192*x2)), tmp10 & xmask, other=0.0)
    tmp14 = tl.where(tmp4, tmp9, tmp13)
    tl.store(out_ptr0 + (x3), tmp14, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_4/inductor_cache/cp/ccprgmy5vht7vkrfffuz22swcfmt7bnwizkv6emgzzxylgu2r226.py
# Topologically Sorted Source Nodes: [input_101], Original ATen: [aten.convolution]
# Source node to ATen node mapping:
#   input_101 => convolution_51
# Graph fragment:
#   %convolution_51 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%relu_45, %primals_104, %primals_105, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
triton_poi_fused_convolution_9 = async_compile.triton('triton_poi_fused_convolution_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=[8192], 
    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_9', '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_9(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 5632
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 64) % 22
    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')


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 = 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, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_23, (512, ), (1, ))
    assert_size_stride(primals_24, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_25, (512, ), (1, ))
    assert_size_stride(primals_26, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_27, (512, ), (1, ))
    assert_size_stride(primals_28, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_29, (512, ), (1, ))
    assert_size_stride(primals_30, (128, 512, 3, 3), (4608, 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, (22, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_35, (22, ), (1, ))
    assert_size_stride(primals_36, (128, 150, 7, 7), (7350, 49, 7, 1))
    assert_size_stride(primals_37, (128, ), (1, ))
    assert_size_stride(primals_38, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_39, (128, ), (1, ))
    assert_size_stride(primals_40, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_41, (128, ), (1, ))
    assert_size_stride(primals_42, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_43, (128, ), (1, ))
    assert_size_stride(primals_44, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_45, (128, ), (1, ))
    assert_size_stride(primals_46, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_47, (128, ), (1, ))
    assert_size_stride(primals_48, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_49, (22, ), (1, ))
    assert_size_stride(primals_50, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_57, (128, ), (1, ))
    assert_size_stride(primals_58, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_59, (128, ), (1, ))
    assert_size_stride(primals_60, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_61, (128, ), (1, ))
    assert_size_stride(primals_62, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_63, (22, ), (1, ))
    assert_size_stride(primals_64, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_71, (128, ), (1, ))
    assert_size_stride(primals_72, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_73, (128, ), (1, ))
    assert_size_stride(primals_74, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_75, (128, ), (1, ))
    assert_size_stride(primals_76, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_77, (22, ), (1, ))
    assert_size_stride(primals_78, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_85, (128, ), (1, ))
    assert_size_stride(primals_86, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_87, (128, ), (1, ))
    assert_size_stride(primals_88, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_89, (128, ), (1, ))
    assert_size_stride(primals_90, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_91, (22, ), (1, ))
    assert_size_stride(primals_92, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_99, (128, ), (1, ))
    assert_size_stride(primals_100, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_101, (128, ), (1, ))
    assert_size_stride(primals_102, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_103, (128, ), (1, ))
    assert_size_stride(primals_104, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_105, (22, ), (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, 512, 8, 8), (32768, 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_6.run(buf27, primals_23, 131072, grid=grid(131072), 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, 512, 8, 8), (32768, 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_6.run(buf29, primals_25, 131072, grid=grid(131072), 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, 512, 8, 8), (32768, 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_6.run(buf31, primals_27, 131072, grid=grid(131072), 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, 512, 8, 8), (32768, 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_6.run(buf33, primals_29, 131072, grid=grid(131072), 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_7.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, 22, 8, 8), (1408, 64, 8, 1))
        buf39 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [concat_stage2], Original ATen: [aten.cat]
        triton_poi_fused_cat_8.run(buf38, primals_35, buf35, buf39, 38400, grid=grid(38400), stream=stream0)
        del buf38
        del primals_35
        # Topologically Sorted Source Nodes: [input_37], Original ATen: [aten.convolution]
        buf40 = extern_kernels.convolution(buf39, primals_36, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf40, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf41 = buf40; del buf40  # reuse
        # Topologically Sorted Source Nodes: [input_37, input_38], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf41, primals_37, 32768, grid=grid(32768), stream=stream0)
        del primals_37
        # Topologically Sorted Source Nodes: [input_39], Original ATen: [aten.convolution]
        buf42 = extern_kernels.convolution(buf41, primals_38, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf42, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf43 = buf42; del buf42  # reuse
        # Topologically Sorted Source Nodes: [input_39, input_40], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf43, primals_39, 32768, grid=grid(32768), stream=stream0)
        del primals_39
        # Topologically Sorted Source Nodes: [input_41], Original ATen: [aten.convolution]
        buf44 = extern_kernels.convolution(buf43, primals_40, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf44, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf45 = buf44; del buf44  # reuse
        # Topologically Sorted Source Nodes: [input_41, input_42], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf45, primals_41, 32768, grid=grid(32768), stream=stream0)
        del primals_41
        # Topologically Sorted Source Nodes: [input_43], Original ATen: [aten.convolution]
        buf46 = extern_kernels.convolution(buf45, primals_42, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf46, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf47 = buf46; del buf46  # reuse
        # Topologically Sorted Source Nodes: [input_43, input_44], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf47, primals_43, 32768, grid=grid(32768), stream=stream0)
        del primals_43
        # Topologically Sorted Source Nodes: [input_45], Original ATen: [aten.convolution]
        buf48 = extern_kernels.convolution(buf47, primals_44, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf48, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf49 = buf48; del buf48  # reuse
        # Topologically Sorted Source Nodes: [input_45, input_46], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf49, primals_45, 32768, grid=grid(32768), stream=stream0)
        del primals_45
        # Topologically Sorted Source Nodes: [input_47], Original ATen: [aten.convolution]
        buf50 = extern_kernels.convolution(buf49, primals_46, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf50, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf51 = buf50; del buf50  # reuse
        # Topologically Sorted Source Nodes: [input_47, input_48], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf51, primals_47, 32768, grid=grid(32768), stream=stream0)
        del primals_47
        # Topologically Sorted Source Nodes: [input_49], Original ATen: [aten.convolution]
        buf52 = extern_kernels.convolution(buf51, primals_48, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf52, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf53 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [concat_stage3], Original ATen: [aten.cat]
        triton_poi_fused_cat_8.run(buf52, primals_49, buf35, buf53, 38400, grid=grid(38400), stream=stream0)
        del buf52
        del primals_49
        # Topologically Sorted Source Nodes: [input_50], Original ATen: [aten.convolution]
        buf54 = extern_kernels.convolution(buf53, primals_50, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf54, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf55 = buf54; del buf54  # reuse
        # Topologically Sorted Source Nodes: [input_50, input_51], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf55, primals_51, 32768, grid=grid(32768), stream=stream0)
        del primals_51
        # Topologically Sorted Source Nodes: [input_52], Original ATen: [aten.convolution]
        buf56 = extern_kernels.convolution(buf55, primals_52, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf56, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf57 = buf56; del buf56  # reuse
        # Topologically Sorted Source Nodes: [input_52, input_53], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf57, primals_53, 32768, grid=grid(32768), stream=stream0)
        del primals_53
        # Topologically Sorted Source Nodes: [input_54], Original ATen: [aten.convolution]
        buf58 = extern_kernels.convolution(buf57, primals_54, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf58, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf59 = buf58; del buf58  # reuse
        # Topologically Sorted Source Nodes: [input_54, input_55], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf59, primals_55, 32768, grid=grid(32768), stream=stream0)
        del primals_55
        # Topologically Sorted Source Nodes: [input_56], Original ATen: [aten.convolution]
        buf60 = extern_kernels.convolution(buf59, primals_56, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf60, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf61 = buf60; del buf60  # reuse
        # Topologically Sorted Source Nodes: [input_56, input_57], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf61, primals_57, 32768, grid=grid(32768), stream=stream0)
        del primals_57
        # Topologically Sorted Source Nodes: [input_58], Original ATen: [aten.convolution]
        buf62 = extern_kernels.convolution(buf61, primals_58, 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_58, input_59], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf63, primals_59, 32768, grid=grid(32768), stream=stream0)
        del primals_59
        # Topologically Sorted Source Nodes: [input_60], Original ATen: [aten.convolution]
        buf64 = extern_kernels.convolution(buf63, primals_60, stride=(1, 1), padding=(0, 0), 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_60, input_61], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf65, primals_61, 32768, grid=grid(32768), stream=stream0)
        del primals_61
        # Topologically Sorted Source Nodes: [input_62], Original ATen: [aten.convolution]
        buf66 = extern_kernels.convolution(buf65, primals_62, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf66, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf67 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [concat_stage4], Original ATen: [aten.cat]
        triton_poi_fused_cat_8.run(buf66, primals_63, buf35, buf67, 38400, grid=grid(38400), stream=stream0)
        del buf66
        del primals_63
        # Topologically Sorted Source Nodes: [input_63], Original ATen: [aten.convolution]
        buf68 = extern_kernels.convolution(buf67, primals_64, 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_63, input_64], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf69, primals_65, 32768, grid=grid(32768), stream=stream0)
        del primals_65
        # Topologically Sorted Source Nodes: [input_65], Original ATen: [aten.convolution]
        buf70 = extern_kernels.convolution(buf69, primals_66, 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_65, input_66], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf71, primals_67, 32768, grid=grid(32768), stream=stream0)
        del primals_67
        # Topologically Sorted Source Nodes: [input_67], Original ATen: [aten.convolution]
        buf72 = extern_kernels.convolution(buf71, primals_68, stride=(1, 1), padding=(3, 3), 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_67, input_68], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf73, primals_69, 32768, grid=grid(32768), stream=stream0)
        del primals_69
        # Topologically Sorted Source Nodes: [input_69], Original ATen: [aten.convolution]
        buf74 = extern_kernels.convolution(buf73, primals_70, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf75 = buf74; del buf74  # reuse
        # Topologically Sorted Source Nodes: [input_69, input_70], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf75, primals_71, 32768, grid=grid(32768), stream=stream0)
        del primals_71
        # Topologically Sorted Source Nodes: [input_71], Original ATen: [aten.convolution]
        buf76 = extern_kernels.convolution(buf75, primals_72, 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_71, input_72], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf77, primals_73, 32768, grid=grid(32768), stream=stream0)
        del primals_73
        # Topologically Sorted Source Nodes: [input_73], Original ATen: [aten.convolution]
        buf78 = extern_kernels.convolution(buf77, primals_74, stride=(1, 1), padding=(0, 0), 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_73, input_74], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf79, primals_75, 32768, grid=grid(32768), stream=stream0)
        del primals_75
        # Topologically Sorted Source Nodes: [input_75], Original ATen: [aten.convolution]
        buf80 = extern_kernels.convolution(buf79, primals_76, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf81 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [concat_stage5], Original ATen: [aten.cat]
        triton_poi_fused_cat_8.run(buf80, primals_77, buf35, buf81, 38400, grid=grid(38400), stream=stream0)
        del buf80
        del primals_77
        # Topologically Sorted Source Nodes: [input_76], Original ATen: [aten.convolution]
        buf82 = extern_kernels.convolution(buf81, primals_78, 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_76, input_77], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf83, primals_79, 32768, grid=grid(32768), stream=stream0)
        del primals_79
        # Topologically Sorted Source Nodes: [input_78], Original ATen: [aten.convolution]
        buf84 = extern_kernels.convolution(buf83, primals_80, 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_78, input_79], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf85, primals_81, 32768, grid=grid(32768), stream=stream0)
        del primals_81
        # Topologically Sorted Source Nodes: [input_80], Original ATen: [aten.convolution]
        buf86 = extern_kernels.convolution(buf85, primals_82, stride=(1, 1), padding=(3, 3), 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_80, input_81], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf87, primals_83, 32768, grid=grid(32768), stream=stream0)
        del primals_83
        # Topologically Sorted Source Nodes: [input_82], Original ATen: [aten.convolution]
        buf88 = extern_kernels.convolution(buf87, primals_84, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf88, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf89 = buf88; del buf88  # reuse
        # Topologically Sorted Source Nodes: [input_82, input_83], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf89, primals_85, 32768, grid=grid(32768), stream=stream0)
        del primals_85
        # Topologically Sorted Source Nodes: [input_84], Original ATen: [aten.convolution]
        buf90 = extern_kernels.convolution(buf89, primals_86, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf90, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf91 = buf90; del buf90  # reuse
        # Topologically Sorted Source Nodes: [input_84, input_85], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf91, primals_87, 32768, grid=grid(32768), stream=stream0)
        del primals_87
        # Topologically Sorted Source Nodes: [input_86], Original ATen: [aten.convolution]
        buf92 = extern_kernels.convolution(buf91, primals_88, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf92, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf93 = buf92; del buf92  # reuse
        # Topologically Sorted Source Nodes: [input_86, input_87], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf93, primals_89, 32768, grid=grid(32768), stream=stream0)
        del primals_89
        # Topologically Sorted Source Nodes: [input_88], Original ATen: [aten.convolution]
        buf94 = extern_kernels.convolution(buf93, primals_90, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf94, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf95 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.float32)
        # Topologically Sorted Source Nodes: [concat_stage6], Original ATen: [aten.cat]
        triton_poi_fused_cat_8.run(buf94, primals_91, buf35, buf95, 38400, grid=grid(38400), stream=stream0)
        del buf94
        del primals_91
        # Topologically Sorted Source Nodes: [input_89], Original ATen: [aten.convolution]
        buf96 = extern_kernels.convolution(buf95, primals_92, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf96, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf97 = buf96; del buf96  # reuse
        # Topologically Sorted Source Nodes: [input_89, input_90], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf97, primals_93, 32768, grid=grid(32768), stream=stream0)
        del primals_93
        # Topologically Sorted Source Nodes: [input_91], Original ATen: [aten.convolution]
        buf98 = extern_kernels.convolution(buf97, primals_94, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf98, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf99 = buf98; del buf98  # reuse
        # Topologically Sorted Source Nodes: [input_91, input_92], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf99, primals_95, 32768, grid=grid(32768), stream=stream0)
        del primals_95
        # Topologically Sorted Source Nodes: [input_93], Original ATen: [aten.convolution]
        buf100 = extern_kernels.convolution(buf99, primals_96, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf100, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf101 = buf100; del buf100  # reuse
        # Topologically Sorted Source Nodes: [input_93, input_94], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf101, primals_97, 32768, grid=grid(32768), stream=stream0)
        del primals_97
        # Topologically Sorted Source Nodes: [input_95], Original ATen: [aten.convolution]
        buf102 = extern_kernels.convolution(buf101, primals_98, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf102, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf103 = buf102; del buf102  # reuse
        # Topologically Sorted Source Nodes: [input_95, input_96], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf103, primals_99, 32768, grid=grid(32768), stream=stream0)
        del primals_99
        # Topologically Sorted Source Nodes: [input_97], Original ATen: [aten.convolution]
        buf104 = extern_kernels.convolution(buf103, primals_100, stride=(1, 1), padding=(3, 3), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf104, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf105 = buf104; del buf104  # reuse
        # Topologically Sorted Source Nodes: [input_97, input_98], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf105, primals_101, 32768, grid=grid(32768), stream=stream0)
        del primals_101
        # Topologically Sorted Source Nodes: [input_99], Original ATen: [aten.convolution]
        buf106 = extern_kernels.convolution(buf105, primals_102, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf106, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf107 = buf106; del buf106  # reuse
        # Topologically Sorted Source Nodes: [input_99, input_100], Original ATen: [aten.convolution, aten.relu]
        triton_poi_fused_convolution_relu_7.run(buf107, primals_103, 32768, grid=grid(32768), stream=stream0)
        del primals_103
        # Topologically Sorted Source Nodes: [input_101], Original ATen: [aten.convolution]
        buf108 = extern_kernels.convolution(buf107, primals_104, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf108, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf109 = buf108; del buf108  # reuse
        # Topologically Sorted Source Nodes: [input_101], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_9.run(buf109, primals_105, 5632, grid=grid(5632), stream=stream0)
        del primals_105
    return (buf109, 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, buf1, buf3, buf4, buf5, buf7, buf9, buf10, buf11, buf13, buf15, buf17, buf19, buf20, buf21, buf23, buf25, buf27, buf29, buf31, buf33, buf35, buf37, buf39, buf41, buf43, buf45, buf47, buf49, buf51, buf53, buf55, buf57, buf59, buf61, buf63, buf65, buf67, buf69, buf71, buf73, buf75, buf77, buf79, buf81, buf83, buf85, buf87, buf89, buf91, buf93, buf95, buf97, buf99, buf101, buf103, buf105, buf107, )


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((512, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_23 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_24 = rand_strided((512, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_25 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_26 = rand_strided((512, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_27 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_28 = rand_strided((512, 512, 3, 3), (4608, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_29 = rand_strided((512, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_30 = rand_strided((128, 512, 3, 3), (4608, 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((22, 512, 1, 1), (512, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_35 = rand_strided((22, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_36 = rand_strided((128, 150, 7, 7), (7350, 49, 7, 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, 7, 7), (6272, 49, 7, 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, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_41 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_42 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_43 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_44 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_45 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_46 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_47 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_48 = rand_strided((22, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_49 = rand_strided((22, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_50 = rand_strided((128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_57 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_58 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_59 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_60 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_61 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_62 = rand_strided((22, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_63 = rand_strided((22, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_64 = rand_strided((128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_71 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_72 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_73 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_74 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_75 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_76 = rand_strided((22, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_77 = rand_strided((22, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_78 = rand_strided((128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_85 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_86 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_87 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_88 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_89 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_90 = rand_strided((22, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_91 = rand_strided((22, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_92 = rand_strided((128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_99 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_100 = rand_strided((128, 128, 7, 7), (6272, 49, 7, 1), device='cuda:0', dtype=torch.float32)
    primals_101 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_102 = rand_strided((128, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_103 = rand_strided((128, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_104 = rand_strided((22, 128, 1, 1), (128, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_105 = rand_strided((22, ), (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])
    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
from collections import OrderedDict
import torch.nn as nn


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 handpose_model(nn.Module):

    def __init__(self):
        super(handpose_model, self).__init__()
        no_relu_layers = ['conv6_2_CPM', 'Mconv7_stage2', 'Mconv7_stage3',
            'Mconv7_stage4', 'Mconv7_stage5', 'Mconv7_stage6']
        block1_0 = 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', [512, 512, 3, 1, 1]), ('conv4_4', [512, 512,
            3, 1, 1]), ('conv5_1', [512, 512, 3, 1, 1]), ('conv5_2', [512, 
            512, 3, 1, 1]), ('conv5_3_CPM', [512, 128, 3, 1, 1])])
        block1_1 = OrderedDict([('conv6_1_CPM', [128, 512, 1, 1, 0]), (
            'conv6_2_CPM', [512, 22, 1, 1, 0])])
        blocks = {}
        blocks['block1_0'] = block1_0
        blocks['block1_1'] = block1_1
        for i in range(2, 7):
            blocks['block%d' % i] = OrderedDict([('Mconv1_stage%d' % i, [
                150, 128, 7, 1, 3]), ('Mconv2_stage%d' % i, [128, 128, 7, 1,
                3]), ('Mconv3_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv4_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv5_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv6_stage%d' % i, [128, 128, 1, 1, 0]), (
                'Mconv7_stage%d' % i, [128, 22, 1, 1, 0])])
        for k in blocks.keys():
            blocks[k] = make_layers(blocks[k], no_relu_layers)
        self.model1_0 = blocks['block1_0']
        self.model1_1 = blocks['block1_1']
        self.model2 = blocks['block2']
        self.model3 = blocks['block3']
        self.model4 = blocks['block4']
        self.model5 = blocks['block5']
        self.model6 = blocks['block6']

    def forward(self, x):
        out1_0 = self.model1_0(x)
        out1_1 = self.model1_1(out1_0)
        concat_stage2 = torch.cat([out1_1, out1_0], 1)
        out_stage2 = self.model2(concat_stage2)
        concat_stage3 = torch.cat([out_stage2, out1_0], 1)
        out_stage3 = self.model3(concat_stage3)
        concat_stage4 = torch.cat([out_stage3, out1_0], 1)
        out_stage4 = self.model4(concat_stage4)
        concat_stage5 = torch.cat([out_stage4, out1_0], 1)
        out_stage5 = self.model5(concat_stage5)
        concat_stage6 = torch.cat([out_stage5, out1_0], 1)
        out_stage6 = self.model6(concat_stage6)
        return out_stage6


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
from collections import OrderedDict
import torch.nn as nn
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 % 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_8(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 38400
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 64 % 150
    x0 = xindex % 64
    x2 = xindex // 9600
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 22, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 64 * x1 + 1408 * 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
    tl.full([1], 150, tl.int64)
    tmp13 = tl.load(in_ptr2 + (x0 + 64 * (-22 + x1) + 8192 * x2), tmp10 &
        xmask, other=0.0)
    tmp14 = tl.where(tmp4, tmp9, tmp13)
    tl.store(out_ptr0 + x3, tmp14, xmask)


@triton.jit
def triton_poi_fused_convolution_9(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 5632
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 64 % 22
    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)


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) = 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, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_23, (512,), (1,))
    assert_size_stride(primals_24, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_25, (512,), (1,))
    assert_size_stride(primals_26, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_27, (512,), (1,))
    assert_size_stride(primals_28, (512, 512, 3, 3), (4608, 9, 3, 1))
    assert_size_stride(primals_29, (512,), (1,))
    assert_size_stride(primals_30, (128, 512, 3, 3), (4608, 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, (22, 512, 1, 1), (512, 1, 1, 1))
    assert_size_stride(primals_35, (22,), (1,))
    assert_size_stride(primals_36, (128, 150, 7, 7), (7350, 49, 7, 1))
    assert_size_stride(primals_37, (128,), (1,))
    assert_size_stride(primals_38, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_39, (128,), (1,))
    assert_size_stride(primals_40, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_41, (128,), (1,))
    assert_size_stride(primals_42, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_43, (128,), (1,))
    assert_size_stride(primals_44, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_45, (128,), (1,))
    assert_size_stride(primals_46, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_47, (128,), (1,))
    assert_size_stride(primals_48, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_49, (22,), (1,))
    assert_size_stride(primals_50, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_57, (128,), (1,))
    assert_size_stride(primals_58, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_59, (128,), (1,))
    assert_size_stride(primals_60, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_61, (128,), (1,))
    assert_size_stride(primals_62, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_63, (22,), (1,))
    assert_size_stride(primals_64, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_71, (128,), (1,))
    assert_size_stride(primals_72, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_73, (128,), (1,))
    assert_size_stride(primals_74, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_75, (128,), (1,))
    assert_size_stride(primals_76, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_77, (22,), (1,))
    assert_size_stride(primals_78, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_85, (128,), (1,))
    assert_size_stride(primals_86, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_87, (128,), (1,))
    assert_size_stride(primals_88, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_89, (128,), (1,))
    assert_size_stride(primals_90, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_91, (22,), (1,))
    assert_size_stride(primals_92, (128, 150, 7, 7), (7350, 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, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_99, (128,), (1,))
    assert_size_stride(primals_100, (128, 128, 7, 7), (6272, 49, 7, 1))
    assert_size_stride(primals_101, (128,), (1,))
    assert_size_stride(primals_102, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_103, (128,), (1,))
    assert_size_stride(primals_104, (22, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_105, (22,), (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=1024, num_warps=4, 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=1024, num_warps=4, 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=512, num_warps=8, 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=512, num_warps=8, 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=1024, num_warps=4, 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=1024, num_warps=4, 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=1024, num_warps=4, 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=1024, num_warps=4, 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=512, num_warps=8, 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=512, num_warps=8, 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, 512, 8, 8), (32768, 64, 8, 1))
        buf27 = buf26
        del buf26
        triton_poi_fused_convolution_relu_6[grid(131072)](buf27, primals_23,
            131072, XBLOCK=512, num_warps=8, 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, 512, 8, 8), (32768, 64, 8, 1))
        buf29 = buf28
        del buf28
        triton_poi_fused_convolution_relu_6[grid(131072)](buf29, primals_25,
            131072, XBLOCK=512, num_warps=8, 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, 512, 8, 8), (32768, 64, 8, 1))
        buf31 = buf30
        del buf30
        triton_poi_fused_convolution_relu_6[grid(131072)](buf31, primals_27,
            131072, XBLOCK=512, num_warps=8, 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, 512, 8, 8), (32768, 64, 8, 1))
        buf33 = buf32
        del buf32
        triton_poi_fused_convolution_relu_6[grid(131072)](buf33, primals_29,
            131072, XBLOCK=512, num_warps=8, 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_7[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=512, num_warps=8, 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, 22, 8, 8), (1408, 64, 8, 1))
        buf39 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.
            float32)
        triton_poi_fused_cat_8[grid(38400)](buf38, primals_35, buf35, buf39,
            38400, XBLOCK=512, num_warps=4, num_stages=1)
        del buf38
        del primals_35
        buf40 = extern_kernels.convolution(buf39, primals_36, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf40, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf41 = buf40
        del buf40
        triton_poi_fused_convolution_relu_7[grid(32768)](buf41, primals_37,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_37
        buf42 = extern_kernels.convolution(buf41, primals_38, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf42, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf43 = buf42
        del buf42
        triton_poi_fused_convolution_relu_7[grid(32768)](buf43, primals_39,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_39
        buf44 = extern_kernels.convolution(buf43, primals_40, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf44, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf45 = buf44
        del buf44
        triton_poi_fused_convolution_relu_7[grid(32768)](buf45, primals_41,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_41
        buf46 = extern_kernels.convolution(buf45, primals_42, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf46, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf47 = buf46
        del buf46
        triton_poi_fused_convolution_relu_7[grid(32768)](buf47, primals_43,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_43
        buf48 = extern_kernels.convolution(buf47, primals_44, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf48, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf49 = buf48
        del buf48
        triton_poi_fused_convolution_relu_7[grid(32768)](buf49, primals_45,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_45
        buf50 = extern_kernels.convolution(buf49, primals_46, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf50, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf51 = buf50
        del buf50
        triton_poi_fused_convolution_relu_7[grid(32768)](buf51, primals_47,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_47
        buf52 = extern_kernels.convolution(buf51, primals_48, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf52, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf53 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.
            float32)
        triton_poi_fused_cat_8[grid(38400)](buf52, primals_49, buf35, buf53,
            38400, XBLOCK=512, num_warps=4, num_stages=1)
        del buf52
        del primals_49
        buf54 = extern_kernels.convolution(buf53, primals_50, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf54, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf55 = buf54
        del buf54
        triton_poi_fused_convolution_relu_7[grid(32768)](buf55, primals_51,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_51
        buf56 = extern_kernels.convolution(buf55, primals_52, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf56, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf57 = buf56
        del buf56
        triton_poi_fused_convolution_relu_7[grid(32768)](buf57, primals_53,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_53
        buf58 = extern_kernels.convolution(buf57, primals_54, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf58, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf59 = buf58
        del buf58
        triton_poi_fused_convolution_relu_7[grid(32768)](buf59, primals_55,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_55
        buf60 = extern_kernels.convolution(buf59, primals_56, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf60, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf61 = buf60
        del buf60
        triton_poi_fused_convolution_relu_7[grid(32768)](buf61, primals_57,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_57
        buf62 = extern_kernels.convolution(buf61, primals_58, 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_7[grid(32768)](buf63, primals_59,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_59
        buf64 = extern_kernels.convolution(buf63, primals_60, stride=(1, 1),
            padding=(0, 0), 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_7[grid(32768)](buf65, primals_61,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_61
        buf66 = extern_kernels.convolution(buf65, primals_62, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf66, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf67 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.
            float32)
        triton_poi_fused_cat_8[grid(38400)](buf66, primals_63, buf35, buf67,
            38400, XBLOCK=512, num_warps=4, num_stages=1)
        del buf66
        del primals_63
        buf68 = extern_kernels.convolution(buf67, primals_64, 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_7[grid(32768)](buf69, primals_65,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_65
        buf70 = extern_kernels.convolution(buf69, primals_66, 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_7[grid(32768)](buf71, primals_67,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_67
        buf72 = extern_kernels.convolution(buf71, primals_68, stride=(1, 1),
            padding=(3, 3), 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_7[grid(32768)](buf73, primals_69,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_69
        buf74 = extern_kernels.convolution(buf73, primals_70, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf75 = buf74
        del buf74
        triton_poi_fused_convolution_relu_7[grid(32768)](buf75, primals_71,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_71
        buf76 = extern_kernels.convolution(buf75, primals_72, 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_7[grid(32768)](buf77, primals_73,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_73
        buf78 = extern_kernels.convolution(buf77, primals_74, stride=(1, 1),
            padding=(0, 0), 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_7[grid(32768)](buf79, primals_75,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_75
        buf80 = extern_kernels.convolution(buf79, primals_76, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf81 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.
            float32)
        triton_poi_fused_cat_8[grid(38400)](buf80, primals_77, buf35, buf81,
            38400, XBLOCK=512, num_warps=4, num_stages=1)
        del buf80
        del primals_77
        buf82 = extern_kernels.convolution(buf81, primals_78, 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_7[grid(32768)](buf83, primals_79,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_79
        buf84 = extern_kernels.convolution(buf83, primals_80, 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_7[grid(32768)](buf85, primals_81,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_81
        buf86 = extern_kernels.convolution(buf85, primals_82, stride=(1, 1),
            padding=(3, 3), 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_7[grid(32768)](buf87, primals_83,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_83
        buf88 = extern_kernels.convolution(buf87, primals_84, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf88, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf89 = buf88
        del buf88
        triton_poi_fused_convolution_relu_7[grid(32768)](buf89, primals_85,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_85
        buf90 = extern_kernels.convolution(buf89, primals_86, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf90, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf91 = buf90
        del buf90
        triton_poi_fused_convolution_relu_7[grid(32768)](buf91, primals_87,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_87
        buf92 = extern_kernels.convolution(buf91, primals_88, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf92, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf93 = buf92
        del buf92
        triton_poi_fused_convolution_relu_7[grid(32768)](buf93, primals_89,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_89
        buf94 = extern_kernels.convolution(buf93, primals_90, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf94, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf95 = empty_strided_cuda((4, 150, 8, 8), (9600, 64, 8, 1), torch.
            float32)
        triton_poi_fused_cat_8[grid(38400)](buf94, primals_91, buf35, buf95,
            38400, XBLOCK=512, num_warps=4, num_stages=1)
        del buf94
        del primals_91
        buf96 = extern_kernels.convolution(buf95, primals_92, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf96, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf97 = buf96
        del buf96
        triton_poi_fused_convolution_relu_7[grid(32768)](buf97, primals_93,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_93
        buf98 = extern_kernels.convolution(buf97, primals_94, stride=(1, 1),
            padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf98, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf99 = buf98
        del buf98
        triton_poi_fused_convolution_relu_7[grid(32768)](buf99, primals_95,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_95
        buf100 = extern_kernels.convolution(buf99, primals_96, stride=(1, 1
            ), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf100, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf101 = buf100
        del buf100
        triton_poi_fused_convolution_relu_7[grid(32768)](buf101, primals_97,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_97
        buf102 = extern_kernels.convolution(buf101, primals_98, stride=(1, 
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf102, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf103 = buf102
        del buf102
        triton_poi_fused_convolution_relu_7[grid(32768)](buf103, primals_99,
            32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_99
        buf104 = extern_kernels.convolution(buf103, primals_100, stride=(1,
            1), padding=(3, 3), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf104, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf105 = buf104
        del buf104
        triton_poi_fused_convolution_relu_7[grid(32768)](buf105,
            primals_101, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_101
        buf106 = extern_kernels.convolution(buf105, primals_102, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf106, (4, 128, 8, 8), (8192, 64, 8, 1))
        buf107 = buf106
        del buf106
        triton_poi_fused_convolution_relu_7[grid(32768)](buf107,
            primals_103, 32768, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_103
        buf108 = extern_kernels.convolution(buf107, primals_104, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf108, (4, 22, 8, 8), (1408, 64, 8, 1))
        buf109 = buf108
        del buf108
        triton_poi_fused_convolution_9[grid(5632)](buf109, primals_105, 
            5632, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_105
    return (buf109, 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, buf1, buf3, buf4, buf5, buf7,
        buf9, buf10, buf11, buf13, buf15, buf17, buf19, buf20, buf21, buf23,
        buf25, buf27, buf29, buf31, buf33, buf35, buf37, buf39, buf41,
        buf43, buf45, buf47, buf49, buf51, buf53, buf55, buf57, buf59,
        buf61, buf63, buf65, buf67, buf69, buf71, buf73, buf75, buf77,
        buf79, buf81, buf83, buf85, buf87, buf89, buf91, buf93, buf95,
        buf97, buf99, buf101, buf103, buf105, buf107)


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 handpose_modelNew(nn.Module):

    def __init__(self):
        super(handpose_modelNew, self).__init__()
        no_relu_layers = ['conv6_2_CPM', 'Mconv7_stage2', 'Mconv7_stage3',
            'Mconv7_stage4', 'Mconv7_stage5', 'Mconv7_stage6']
        block1_0 = 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', [512, 512, 3, 1, 1]), ('conv4_4', [512, 512,
            3, 1, 1]), ('conv5_1', [512, 512, 3, 1, 1]), ('conv5_2', [512, 
            512, 3, 1, 1]), ('conv5_3_CPM', [512, 128, 3, 1, 1])])
        block1_1 = OrderedDict([('conv6_1_CPM', [128, 512, 1, 1, 0]), (
            'conv6_2_CPM', [512, 22, 1, 1, 0])])
        blocks = {}
        blocks['block1_0'] = block1_0
        blocks['block1_1'] = block1_1
        for i in range(2, 7):
            blocks['block%d' % i] = OrderedDict([('Mconv1_stage%d' % i, [
                150, 128, 7, 1, 3]), ('Mconv2_stage%d' % i, [128, 128, 7, 1,
                3]), ('Mconv3_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv4_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv5_stage%d' % i, [128, 128, 7, 1, 3]), (
                'Mconv6_stage%d' % i, [128, 128, 1, 1, 0]), (
                'Mconv7_stage%d' % i, [128, 22, 1, 1, 0])])
        for k in blocks.keys():
            blocks[k] = make_layers(blocks[k], no_relu_layers)
        self.model1_0 = blocks['block1_0']
        self.model1_1 = blocks['block1_1']
        self.model2 = blocks['block2']
        self.model3 = blocks['block3']
        self.model4 = blocks['block4']
        self.model5 = blocks['block5']
        self.model6 = blocks['block6']

    def forward(self, input_0):
        primals_1 = self.model1_0.conv1_1.weight
        primals_2 = self.model1_0.conv1_1.bias
        primals_4 = self.model1_0.conv1_2.weight
        primals_5 = self.model1_0.conv1_2.bias
        primals_6 = self.model1_0.conv2_1.weight
        primals_7 = self.model1_0.conv2_1.bias
        primals_8 = self.model1_0.conv2_2.weight
        primals_9 = self.model1_0.conv2_2.bias
        primals_10 = self.model1_0.conv3_1.weight
        primals_11 = self.model1_0.conv3_1.bias
        primals_12 = self.model1_0.conv3_2.weight
        primals_13 = self.model1_0.conv3_2.bias
        primals_14 = self.model1_0.conv3_3.weight
        primals_15 = self.model1_0.conv3_3.bias
        primals_16 = self.model1_0.conv3_4.weight
        primals_17 = self.model1_0.conv3_4.bias
        primals_18 = self.model1_0.conv4_1.weight
        primals_19 = self.model1_0.conv4_1.bias
        primals_20 = self.model1_0.conv4_2.weight
        primals_21 = self.model1_0.conv4_2.bias
        primals_22 = self.model1_0.conv4_3.weight
        primals_23 = self.model1_0.conv4_3.bias
        primals_24 = self.model1_0.conv4_4.weight
        primals_25 = self.model1_0.conv4_4.bias
        primals_26 = self.model1_0.conv5_1.weight
        primals_27 = self.model1_0.conv5_1.bias
        primals_28 = self.model1_0.conv5_2.weight
        primals_29 = self.model1_0.conv5_2.bias
        primals_30 = self.model1_0.conv5_3_CPM.weight
        primals_31 = self.model1_0.conv5_3_CPM.bias
        primals_32 = self.model1_1.conv6_1_CPM.weight
        primals_33 = self.model1_1.conv6_1_CPM.bias
        primals_34 = self.model1_1.conv6_2_CPM.weight
        primals_35 = self.model1_1.conv6_2_CPM.bias
        primals_36 = self.model2.Mconv1_stage2.weight
        primals_37 = self.model2.Mconv1_stage2.bias
        primals_38 = self.model2.Mconv2_stage2.weight
        primals_39 = self.model2.Mconv2_stage2.bias
        primals_40 = self.model2.Mconv3_stage2.weight
        primals_41 = self.model2.Mconv3_stage2.bias
        primals_42 = self.model2.Mconv4_stage2.weight
        primals_43 = self.model2.Mconv4_stage2.bias
        primals_44 = self.model2.Mconv5_stage2.weight
        primals_45 = self.model2.Mconv5_stage2.bias
        primals_46 = self.model2.Mconv6_stage2.weight
        primals_47 = self.model2.Mconv6_stage2.bias
        primals_48 = self.model2.Mconv7_stage2.weight
        primals_49 = self.model2.Mconv7_stage2.bias
        primals_50 = self.model3.Mconv1_stage3.weight
        primals_51 = self.model3.Mconv1_stage3.bias
        primals_52 = self.model3.Mconv2_stage3.weight
        primals_53 = self.model3.Mconv2_stage3.bias
        primals_54 = self.model3.Mconv3_stage3.weight
        primals_55 = self.model3.Mconv3_stage3.bias
        primals_56 = self.model3.Mconv4_stage3.weight
        primals_57 = self.model3.Mconv4_stage3.bias
        primals_58 = self.model3.Mconv5_stage3.weight
        primals_59 = self.model3.Mconv5_stage3.bias
        primals_60 = self.model3.Mconv6_stage3.weight
        primals_61 = self.model3.Mconv6_stage3.bias
        primals_62 = self.model3.Mconv7_stage3.weight
        primals_63 = self.model3.Mconv7_stage3.bias
        primals_64 = self.model4.Mconv1_stage4.weight
        primals_65 = self.model4.Mconv1_stage4.bias
        primals_66 = self.model4.Mconv2_stage4.weight
        primals_67 = self.model4.Mconv2_stage4.bias
        primals_68 = self.model4.Mconv3_stage4.weight
        primals_69 = self.model4.Mconv3_stage4.bias
        primals_70 = self.model4.Mconv4_stage4.weight
        primals_71 = self.model4.Mconv4_stage4.bias
        primals_72 = self.model4.Mconv5_stage4.weight
        primals_73 = self.model4.Mconv5_stage4.bias
        primals_74 = self.model4.Mconv6_stage4.weight
        primals_75 = self.model4.Mconv6_stage4.bias
        primals_76 = self.model4.Mconv7_stage4.weight
        primals_77 = self.model4.Mconv7_stage4.bias
        primals_78 = self.model5.Mconv1_stage5.weight
        primals_79 = self.model5.Mconv1_stage5.bias
        primals_80 = self.model5.Mconv2_stage5.weight
        primals_81 = self.model5.Mconv2_stage5.bias
        primals_82 = self.model5.Mconv3_stage5.weight
        primals_83 = self.model5.Mconv3_stage5.bias
        primals_84 = self.model5.Mconv4_stage5.weight
        primals_85 = self.model5.Mconv4_stage5.bias
        primals_86 = self.model5.Mconv5_stage5.weight
        primals_87 = self.model5.Mconv5_stage5.bias
        primals_88 = self.model5.Mconv6_stage5.weight
        primals_89 = self.model5.Mconv6_stage5.bias
        primals_90 = self.model5.Mconv7_stage5.weight
        primals_91 = self.model5.Mconv7_stage5.bias
        primals_92 = self.model6.Mconv1_stage6.weight
        primals_93 = self.model6.Mconv1_stage6.bias
        primals_94 = self.model6.Mconv2_stage6.weight
        primals_95 = self.model6.Mconv2_stage6.bias
        primals_96 = self.model6.Mconv3_stage6.weight
        primals_97 = self.model6.Mconv3_stage6.bias
        primals_98 = self.model6.Mconv4_stage6.weight
        primals_99 = self.model6.Mconv4_stage6.bias
        primals_100 = self.model6.Mconv5_stage6.weight
        primals_101 = self.model6.Mconv5_stage6.bias
        primals_102 = self.model6.Mconv6_stage6.weight
        primals_103 = self.model6.Mconv6_stage6.bias
        primals_104 = self.model6.Mconv7_stage6.weight
        primals_105 = self.model6.Mconv7_stage6.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])
        return output[0]
