# 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_7/inductor_cache/4s/c4shpza3w2x6smnond437qr5xjawce63dxxrkoendepulf3powr2.py
# Topologically Sorted Source Nodes: [input_1, input_2], Original ATen: [aten.convolution, aten._prelu_kernel]
# Source node to ATen node mapping:
#   input_1 => convolution
#   input_2 => gt, mul, where
# Graph fragment:
#   %convolution : [num_users=4] = 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 = {})
#   %gt : [num_users=1] = call_function[target=torch.ops.aten.gt.Scalar](args = (%convolution, 0), kwargs = {})
#   %mul : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%view, %convolution), kwargs = {})
#   %where : [num_users=3] = call_function[target=torch.ops.aten.where.self](args = (%gt, %convolution, %mul), kwargs = {})
triton_poi_fused__prelu_kernel_convolution_0 = async_compile.triton('triton_poi_fused__prelu_kernel_convolution_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=[8192], 
    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__prelu_kernel_convolution_0', 'mutated_arg_names': ['in_out_ptr0'], '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__prelu_kernel_convolution_0(in_out_ptr0, in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 6144
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 16) % 96
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + (x3), tmp2, None)
    tl.store(out_ptr0 + (x3), tmp7, None)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/6u/c6uipwl3edw55eg25a2tdrei2ze57knqjuw4iammxf6xwqiwxef7.py
# Topologically Sorted Source Nodes: [input_5], Original ATen: [aten.convolution]
# Source node to ATen node mapping:
#   input_5 => convolution_2
# Graph fragment:
#   %convolution_2 : [num_users=4] = call_function[target=torch.ops.aten.convolution.default](args = (%where_1, %primals_8, %primals_9, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
triton_poi_fused_convolution_1 = async_compile.triton('triton_poi_fused_convolution_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=[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_1', '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_1(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 6144
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x3 = xindex
    x1 = (xindex // 16) % 96
    tmp0 = tl.load(in_out_ptr0 + (x3), None)
    tmp1 = tl.load(in_ptr0 + (x1), None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + (x3), tmp2, None)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/qj/cqjgnkoee4mry62wexljuvrqjqh5nmfvfgx4olkf2lkyeroqeapg.py
# Topologically Sorted Source Nodes: [out], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   out => cat
# Graph fragment:
#   %cat : [num_users=2] = call_function[target=torch.ops.aten.cat.default](args = ([%where, %where_1, %where_2], 1), kwargs = {})
triton_poi_fused_cat_2 = async_compile.triton('triton_poi_fused_cat_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=[32768], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*fp32', 3: '*fp32', 4: '*fp32', 5: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3, 4, 5), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_cat_2', '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_cat_2(in_ptr0, in_ptr1, in_ptr2, in_ptr3, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 18432
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = tl.full([XBLOCK], True, tl.int1)
    x1 = (xindex // 16) % 288
    x0 = xindex % 16
    x2 = (xindex // 4608)
    x3 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 96, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + (16*x1) + (1536*x2)), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 192, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (x0 + (16*((-96) + x1)) + (1536*x2)), tmp9, other=0.0)
    tmp11 = tmp0 >= tmp7
    tmp12 = tl.full([1], 288, tl.int64)
    tmp13 = tmp0 < tmp12
    tmp14 = tl.load(in_ptr2 + (x0 + (16*((-192) + x1)) + (1536*x2)), tmp11, other=0.0)
    tmp15 = 0.0
    tmp16 = tmp14 > tmp15
    tmp17 = tl.load(in_ptr3 + ((-192) + x1), tmp11, eviction_policy='evict_last', other=0.0)
    tmp18 = tmp17 * tmp14
    tmp19 = tl.where(tmp16, tmp14, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp11, tmp19, tmp20)
    tmp22 = tl.where(tmp9, tmp10, tmp21)
    tmp23 = tl.where(tmp4, tmp5, tmp22)
    tl.store(out_ptr0 + (x3), tmp23, None)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/dz/cdzdzjbmnoov6dzfvnkby3cyo2iugwp6b5vxmnrlf5qvsdsoqruo.py
# Topologically Sorted Source Nodes: [input_31, input_32], Original ATen: [aten.convolution, aten._prelu_kernel]
# Source node to ATen node mapping:
#   input_31 => convolution_15
#   input_32 => gt_15, mul_15, where_15
# Graph fragment:
#   %convolution_15 : [num_users=4] = call_function[target=torch.ops.aten.convolution.default](args = (%cat_4, %primals_47, %primals_48, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
#   %gt_15 : [num_users=1] = call_function[target=torch.ops.aten.gt.Scalar](args = (%convolution_15, 0), kwargs = {})
#   %mul_15 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%view_15, %convolution_15), kwargs = {})
#   %where_15 : [num_users=2] = call_function[target=torch.ops.aten.where.self](args = (%gt_15, %convolution_15, %mul_15), kwargs = {})
triton_poi_fused__prelu_kernel_convolution_3 = async_compile.triton('triton_poi_fused__prelu_kernel_convolution_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=[512], 
    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__prelu_kernel_convolution_3', 'mutated_arg_names': ['in_out_ptr0'], '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__prelu_kernel_convolution_3(in_out_ptr0, in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 512
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 16) % 8
    tmp0 = tl.load(in_out_ptr0 + (x3), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + (x3), tmp2, xmask)
    tl.store(out_ptr0 + (x3), tmp7, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/hr/chry3xppwp5bniw3d3lahl3d3vqmyzphj3u55wsnqylmzluqi555.py
# Topologically Sorted Source Nodes: [x], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   x => cat_5
# Graph fragment:
#   %cat_5 : [num_users=2] = call_function[target=torch.ops.aten.cat.default](args = ([%primals_3, %convolution_16], 1), kwargs = {})
triton_poi_fused_cat_4 = async_compile.triton('triton_poi_fused_cat_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=[512], 
    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_4', '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_4(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 512
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = (xindex // 16) % 8
    x0 = xindex % 16
    x2 = (xindex // 128)
    x3 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + (16*x1) + (64*x2)), tmp4 & xmask, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 8, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tl.load(in_ptr1 + (x0 + (16*((-4) + x1)) + (64*x2)), tmp6 & xmask, other=0.0)
    tmp10 = tl.load(in_ptr2 + ((-4) + x1), tmp6 & xmask, eviction_policy='evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + (x3), tmp14, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/ie/ciefsncpfrhpitcubu6g5kncfiv2ggi5tll7qllaeu2wbfivltuw.py
# Topologically Sorted Source Nodes: [input_34, input_35], Original ATen: [aten.convolution, aten._prelu_kernel]
# Source node to ATen node mapping:
#   input_34 => convolution_17
#   input_35 => gt_16, mul_16, where_16
# Graph fragment:
#   %convolution_17 : [num_users=4] = call_function[target=torch.ops.aten.convolution.default](args = (%cat_5, %primals_52, %primals_53, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
#   %gt_16 : [num_users=1] = call_function[target=torch.ops.aten.gt.Scalar](args = (%convolution_17, 0), kwargs = {})
#   %mul_16 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%view_16, %convolution_17), kwargs = {})
#   %where_16 : [num_users=3] = call_function[target=torch.ops.aten.where.self](args = (%gt_16, %convolution_17, %mul_16), kwargs = {})
triton_poi_fused__prelu_kernel_convolution_5 = async_compile.triton('triton_poi_fused__prelu_kernel_convolution_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=[256], 
    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__prelu_kernel_convolution_5', 'mutated_arg_names': ['in_out_ptr0'], '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__prelu_kernel_convolution_5(in_out_ptr0, in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 16) % 4
    tmp0 = tl.load(in_out_ptr0 + (x3), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + (x3), tmp2, xmask)
    tl.store(out_ptr0 + (x3), tmp7, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/kg/ckgzqia26vn3v7x3apvntzstonjsgd3pomd6nly5yomjycxxg5jc.py
# Topologically Sorted Source Nodes: [input_38], Original ATen: [aten.convolution]
# Source node to ATen node mapping:
#   input_38 => convolution_19
# Graph fragment:
#   %convolution_19 : [num_users=4] = call_function[target=torch.ops.aten.convolution.default](args = (%where_17, %primals_58, %primals_59, [1, 1], [1, 1], [1, 1], False, [0, 0], 1), kwargs = {})
triton_poi_fused_convolution_6 = async_compile.triton('triton_poi_fused_convolution_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=[256], 
    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_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_6(in_out_ptr0, in_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 16) % 4
    tmp0 = tl.load(in_out_ptr0 + (x3), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + (x3), tmp2, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/bp/cbpfpictss7xdvt3z7xgqt2rjd7wyrwjm3suz23gs42mjniqhijs.py
# Topologically Sorted Source Nodes: [out_5], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   out_5 => cat_6
# Graph fragment:
#   %cat_6 : [num_users=2] = call_function[target=torch.ops.aten.cat.default](args = ([%where_16, %where_17, %where_18], 1), kwargs = {})
triton_poi_fused_cat_7 = async_compile.triton('triton_poi_fused_cat_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=[1024], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*fp32', 3: '*fp32', 4: '*fp32', 5: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3, 4, 5), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_cat_7', '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_cat_7(in_ptr0, in_ptr1, in_ptr2, in_ptr3, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 768
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = (xindex // 16) % 12
    x0 = xindex % 16
    x2 = (xindex // 192)
    x3 = xindex
    tmp0 = x1
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + (16*x1) + (64*x2)), tmp4 & xmask, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 8, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (x0 + (16*((-4) + x1)) + (64*x2)), tmp9 & xmask, other=0.0)
    tmp11 = tmp0 >= tmp7
    tmp12 = tl.full([1], 12, tl.int64)
    tmp13 = tmp0 < tmp12
    tmp14 = tl.load(in_ptr2 + (x0 + (16*((-8) + x1)) + (64*x2)), tmp11 & xmask, other=0.0)
    tmp15 = 0.0
    tmp16 = tmp14 > tmp15
    tmp17 = tl.load(in_ptr3 + ((-8) + x1), tmp11 & xmask, eviction_policy='evict_last', other=0.0)
    tmp18 = tmp17 * tmp14
    tmp19 = tl.where(tmp16, tmp14, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp11, tmp19, tmp20)
    tmp22 = tl.where(tmp9, tmp10, tmp21)
    tmp23 = tl.where(tmp4, tmp5, tmp22)
    tl.store(out_ptr0 + (x3), tmp23, xmask)
''', device_str='cuda')


# kernel path: runs/run_shard_7/inductor_cache/l4/cl4ns2lerodjhdybkbaug54sjgpvfoad4ffsvmsbcqpkqaenpbl2.py
# Topologically Sorted Source Nodes: [input_64, input_65], Original ATen: [aten.convolution, aten._prelu_kernel]
# Source node to ATen node mapping:
#   input_64 => convolution_32
#   input_65 => gt_31, mul_31, where_31
# Graph fragment:
#   %convolution_32 : [num_users=4] = call_function[target=torch.ops.aten.convolution.default](args = (%cat_10, %primals_97, %primals_98, [1, 1], [0, 0], [1, 1], False, [0, 0], 1), kwargs = {})
#   %gt_31 : [num_users=1] = call_function[target=torch.ops.aten.gt.Scalar](args = (%convolution_32, 0), kwargs = {})
#   %mul_31 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%view_31, %convolution_32), kwargs = {})
#   %where_31 : [num_users=2] = call_function[target=torch.ops.aten.where.self](args = (%gt_31, %convolution_32, %mul_31), kwargs = {})
triton_poi_fused__prelu_kernel_convolution_8 = async_compile.triton('triton_poi_fused__prelu_kernel_convolution_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=[1024], 
    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__prelu_kernel_convolution_8', 'mutated_arg_names': ['in_out_ptr0'], '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__prelu_kernel_convolution_8(in_out_ptr0, in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 1024
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = (xindex // 16) % 16
    tmp0 = tl.load(in_out_ptr0 + (x3), xmask)
    tmp1 = tl.load(in_ptr0 + (x1), xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + (x1), xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + (x3), tmp2, xmask)
    tl.store(out_ptr0 + (x3), tmp7, xmask)
''', device_str='cuda')


async_compile.wait(globals())
del async_compile

def call(args):
    primals_1, primals_2, primals_3, primals_4, primals_5, primals_6, primals_7, primals_8, primals_9, primals_10, primals_11, primals_12, primals_13, primals_14, primals_15, primals_16, primals_17, primals_18, primals_19, primals_20, primals_21, primals_22, primals_23, primals_24, primals_25, primals_26, primals_27, primals_28, primals_29, primals_30, primals_31, primals_32, primals_33, primals_34, primals_35, primals_36, primals_37, primals_38, primals_39, primals_40, primals_41, primals_42, primals_43, primals_44, primals_45, primals_46, primals_47, primals_48, primals_49, primals_50, primals_51, primals_52, primals_53, primals_54, primals_55, primals_56, primals_57, primals_58, primals_59, primals_60, primals_61, primals_62, primals_63, primals_64, primals_65, primals_66, primals_67, primals_68, primals_69, primals_70, primals_71, primals_72, primals_73, primals_74, primals_75, primals_76, primals_77, primals_78, primals_79, primals_80, primals_81, primals_82, primals_83, primals_84, primals_85, primals_86, primals_87, primals_88, primals_89, primals_90, primals_91, primals_92, primals_93, primals_94, primals_95, primals_96, primals_97, primals_98, primals_99, primals_100, primals_101, primals_102, primals_103, primals_104, primals_105, primals_106, primals_107, primals_108, primals_109, primals_110, primals_111, primals_112, primals_113, primals_114, primals_115, primals_116, primals_117, primals_118, primals_119, primals_120, primals_121, primals_122, primals_123, primals_124, primals_125, primals_126, primals_127, primals_128, primals_129, primals_130, primals_131, primals_132, primals_133, primals_134, primals_135, primals_136, primals_137, primals_138, primals_139, primals_140, primals_141, primals_142, primals_143, primals_144, primals_145, primals_146, primals_147, primals_148, primals_149, primals_150, primals_151, primals_152, primals_153, primals_154, primals_155, primals_156, primals_157, primals_158, primals_159, primals_160, primals_161, primals_162, primals_163, primals_164, primals_165, primals_166, primals_167, primals_168, primals_169, primals_170, primals_171, primals_172, primals_173, primals_174, primals_175, primals_176, primals_177, primals_178, primals_179, primals_180, primals_181, primals_182, primals_183, primals_184, primals_185, primals_186, primals_187, primals_188, primals_189, primals_190, primals_191, primals_192, primals_193, primals_194, primals_195, primals_196, primals_197, primals_198, primals_199, primals_200, primals_201 = args
    args.clear()
    assert_size_stride(primals_1, (96, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_2, (96, ), (1, ))
    assert_size_stride(primals_3, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_4, (96, ), (1, ))
    assert_size_stride(primals_5, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_6, (96, ), (1, ))
    assert_size_stride(primals_7, (96, ), (1, ))
    assert_size_stride(primals_8, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_9, (96, ), (1, ))
    assert_size_stride(primals_10, (96, ), (1, ))
    assert_size_stride(primals_11, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_12, (96, ), (1, ))
    assert_size_stride(primals_13, (96, ), (1, ))
    assert_size_stride(primals_14, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_15, (96, ), (1, ))
    assert_size_stride(primals_16, (96, ), (1, ))
    assert_size_stride(primals_17, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_18, (96, ), (1, ))
    assert_size_stride(primals_19, (96, ), (1, ))
    assert_size_stride(primals_20, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_21, (96, ), (1, ))
    assert_size_stride(primals_22, (96, ), (1, ))
    assert_size_stride(primals_23, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_24, (96, ), (1, ))
    assert_size_stride(primals_25, (96, ), (1, ))
    assert_size_stride(primals_26, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_27, (96, ), (1, ))
    assert_size_stride(primals_28, (96, ), (1, ))
    assert_size_stride(primals_29, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_30, (96, ), (1, ))
    assert_size_stride(primals_31, (96, ), (1, ))
    assert_size_stride(primals_32, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_33, (96, ), (1, ))
    assert_size_stride(primals_34, (96, ), (1, ))
    assert_size_stride(primals_35, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_36, (96, ), (1, ))
    assert_size_stride(primals_37, (96, ), (1, ))
    assert_size_stride(primals_38, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_39, (96, ), (1, ))
    assert_size_stride(primals_40, (96, ), (1, ))
    assert_size_stride(primals_41, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_42, (96, ), (1, ))
    assert_size_stride(primals_43, (96, ), (1, ))
    assert_size_stride(primals_44, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_45, (96, ), (1, ))
    assert_size_stride(primals_46, (96, ), (1, ))
    assert_size_stride(primals_47, (8, 288, 1, 1), (288, 1, 1, 1))
    assert_size_stride(primals_48, (8, ), (1, ))
    assert_size_stride(primals_49, (8, ), (1, ))
    assert_size_stride(primals_50, (4, 8, 1, 1), (8, 1, 1, 1))
    assert_size_stride(primals_51, (4, ), (1, ))
    assert_size_stride(primals_52, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_53, (4, ), (1, ))
    assert_size_stride(primals_54, (4, ), (1, ))
    assert_size_stride(primals_55, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_56, (4, ), (1, ))
    assert_size_stride(primals_57, (4, ), (1, ))
    assert_size_stride(primals_58, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_59, (4, ), (1, ))
    assert_size_stride(primals_60, (4, ), (1, ))
    assert_size_stride(primals_61, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_62, (4, ), (1, ))
    assert_size_stride(primals_63, (4, ), (1, ))
    assert_size_stride(primals_64, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_65, (4, ), (1, ))
    assert_size_stride(primals_66, (4, ), (1, ))
    assert_size_stride(primals_67, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_68, (4, ), (1, ))
    assert_size_stride(primals_69, (4, ), (1, ))
    assert_size_stride(primals_70, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_71, (4, ), (1, ))
    assert_size_stride(primals_72, (4, ), (1, ))
    assert_size_stride(primals_73, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_74, (4, ), (1, ))
    assert_size_stride(primals_75, (4, ), (1, ))
    assert_size_stride(primals_76, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_77, (4, ), (1, ))
    assert_size_stride(primals_78, (4, ), (1, ))
    assert_size_stride(primals_79, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_80, (4, ), (1, ))
    assert_size_stride(primals_81, (4, ), (1, ))
    assert_size_stride(primals_82, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_83, (4, ), (1, ))
    assert_size_stride(primals_84, (4, ), (1, ))
    assert_size_stride(primals_85, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_86, (4, ), (1, ))
    assert_size_stride(primals_87, (4, ), (1, ))
    assert_size_stride(primals_88, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_89, (4, ), (1, ))
    assert_size_stride(primals_90, (4, ), (1, ))
    assert_size_stride(primals_91, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_92, (4, ), (1, ))
    assert_size_stride(primals_93, (4, ), (1, ))
    assert_size_stride(primals_94, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_95, (4, ), (1, ))
    assert_size_stride(primals_96, (4, ), (1, ))
    assert_size_stride(primals_97, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_98, (16, ), (1, ))
    assert_size_stride(primals_99, (16, ), (1, ))
    assert_size_stride(primals_100, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_101, (4, ), (1, ))
    assert_size_stride(primals_102, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_103, (4, ), (1, ))
    assert_size_stride(primals_104, (4, ), (1, ))
    assert_size_stride(primals_105, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_106, (4, ), (1, ))
    assert_size_stride(primals_107, (4, ), (1, ))
    assert_size_stride(primals_108, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_109, (4, ), (1, ))
    assert_size_stride(primals_110, (4, ), (1, ))
    assert_size_stride(primals_111, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_112, (4, ), (1, ))
    assert_size_stride(primals_113, (4, ), (1, ))
    assert_size_stride(primals_114, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_115, (4, ), (1, ))
    assert_size_stride(primals_116, (4, ), (1, ))
    assert_size_stride(primals_117, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_118, (4, ), (1, ))
    assert_size_stride(primals_119, (4, ), (1, ))
    assert_size_stride(primals_120, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_121, (4, ), (1, ))
    assert_size_stride(primals_122, (4, ), (1, ))
    assert_size_stride(primals_123, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_124, (4, ), (1, ))
    assert_size_stride(primals_125, (4, ), (1, ))
    assert_size_stride(primals_126, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_127, (4, ), (1, ))
    assert_size_stride(primals_128, (4, ), (1, ))
    assert_size_stride(primals_129, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_130, (4, ), (1, ))
    assert_size_stride(primals_131, (4, ), (1, ))
    assert_size_stride(primals_132, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_133, (4, ), (1, ))
    assert_size_stride(primals_134, (4, ), (1, ))
    assert_size_stride(primals_135, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_136, (4, ), (1, ))
    assert_size_stride(primals_137, (4, ), (1, ))
    assert_size_stride(primals_138, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_139, (4, ), (1, ))
    assert_size_stride(primals_140, (4, ), (1, ))
    assert_size_stride(primals_141, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_142, (4, ), (1, ))
    assert_size_stride(primals_143, (4, ), (1, ))
    assert_size_stride(primals_144, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_145, (4, ), (1, ))
    assert_size_stride(primals_146, (4, ), (1, ))
    assert_size_stride(primals_147, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_148, (16, ), (1, ))
    assert_size_stride(primals_149, (16, ), (1, ))
    assert_size_stride(primals_150, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_151, (4, ), (1, ))
    assert_size_stride(primals_152, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_153, (4, ), (1, ))
    assert_size_stride(primals_154, (4, ), (1, ))
    assert_size_stride(primals_155, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_156, (4, ), (1, ))
    assert_size_stride(primals_157, (4, ), (1, ))
    assert_size_stride(primals_158, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_159, (4, ), (1, ))
    assert_size_stride(primals_160, (4, ), (1, ))
    assert_size_stride(primals_161, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_162, (4, ), (1, ))
    assert_size_stride(primals_163, (4, ), (1, ))
    assert_size_stride(primals_164, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_165, (4, ), (1, ))
    assert_size_stride(primals_166, (4, ), (1, ))
    assert_size_stride(primals_167, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_168, (4, ), (1, ))
    assert_size_stride(primals_169, (4, ), (1, ))
    assert_size_stride(primals_170, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_171, (4, ), (1, ))
    assert_size_stride(primals_172, (4, ), (1, ))
    assert_size_stride(primals_173, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_174, (4, ), (1, ))
    assert_size_stride(primals_175, (4, ), (1, ))
    assert_size_stride(primals_176, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_177, (4, ), (1, ))
    assert_size_stride(primals_178, (4, ), (1, ))
    assert_size_stride(primals_179, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_180, (4, ), (1, ))
    assert_size_stride(primals_181, (4, ), (1, ))
    assert_size_stride(primals_182, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_183, (4, ), (1, ))
    assert_size_stride(primals_184, (4, ), (1, ))
    assert_size_stride(primals_185, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_186, (4, ), (1, ))
    assert_size_stride(primals_187, (4, ), (1, ))
    assert_size_stride(primals_188, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_189, (4, ), (1, ))
    assert_size_stride(primals_190, (4, ), (1, ))
    assert_size_stride(primals_191, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_192, (4, ), (1, ))
    assert_size_stride(primals_193, (4, ), (1, ))
    assert_size_stride(primals_194, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_195, (4, ), (1, ))
    assert_size_stride(primals_196, (4, ), (1, ))
    assert_size_stride(primals_197, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_198, (16, ), (1, ))
    assert_size_stride(primals_199, (16, ), (1, ))
    assert_size_stride(primals_200, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_201, (4, ), (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, 96, 4, 4), (1536, 16, 4, 1))
        buf1 = buf0; del buf0  # reuse
        buf2 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_1, input_2], Original ATen: [aten.convolution, aten._prelu_kernel]
        stream0 = get_raw_stream(0)
        triton_poi_fused__prelu_kernel_convolution_0.run(buf1, primals_2, primals_4, buf2, 6144, grid=grid(6144), stream=stream0)
        del primals_2
        # Topologically Sorted Source Nodes: [input_3], Original ATen: [aten.convolution]
        buf3 = extern_kernels.convolution(buf2, primals_5, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf3, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf4 = buf3; del buf3  # reuse
        buf5 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_3, input_4], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf4, primals_6, primals_7, buf5, 6144, grid=grid(6144), stream=stream0)
        del primals_6
        # Topologically Sorted Source Nodes: [input_5], Original ATen: [aten.convolution]
        buf6 = extern_kernels.convolution(buf5, primals_8, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf6, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf7 = buf6; del buf6  # reuse
        # Topologically Sorted Source Nodes: [input_5], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_1.run(buf7, primals_9, 6144, grid=grid(6144), stream=stream0)
        del primals_9
        buf8 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out], Original ATen: [aten.cat]
        triton_poi_fused_cat_2.run(buf2, buf5, buf7, primals_10, buf8, 18432, grid=grid(18432), stream=stream0)
        # Topologically Sorted Source Nodes: [input_7], Original ATen: [aten.convolution]
        buf9 = extern_kernels.convolution(buf8, primals_11, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf9, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf10 = buf9; del buf9  # reuse
        buf11 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_7, input_8], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf10, primals_12, primals_13, buf11, 6144, grid=grid(6144), stream=stream0)
        del primals_12
        # Topologically Sorted Source Nodes: [input_9], Original ATen: [aten.convolution]
        buf12 = extern_kernels.convolution(buf11, primals_14, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf12, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf13 = buf12; del buf12  # reuse
        buf14 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_9, input_10], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf13, primals_15, primals_16, buf14, 6144, grid=grid(6144), stream=stream0)
        del primals_15
        # Topologically Sorted Source Nodes: [input_11], Original ATen: [aten.convolution]
        buf15 = extern_kernels.convolution(buf14, primals_17, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf15, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf16 = buf15; del buf15  # reuse
        # Topologically Sorted Source Nodes: [input_11], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_1.run(buf16, primals_18, 6144, grid=grid(6144), stream=stream0)
        del primals_18
        buf17 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_1], Original ATen: [aten.cat]
        triton_poi_fused_cat_2.run(buf11, buf14, buf16, primals_19, buf17, 18432, grid=grid(18432), stream=stream0)
        # Topologically Sorted Source Nodes: [input_13], Original ATen: [aten.convolution]
        buf18 = extern_kernels.convolution(buf17, primals_20, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf19 = buf18; del buf18  # reuse
        buf20 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_13, input_14], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf19, primals_21, primals_22, buf20, 6144, grid=grid(6144), stream=stream0)
        del primals_21
        # Topologically Sorted Source Nodes: [input_15], Original ATen: [aten.convolution]
        buf21 = extern_kernels.convolution(buf20, primals_23, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf21, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf22 = buf21; del buf21  # reuse
        buf23 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_15, input_16], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf22, primals_24, primals_25, buf23, 6144, grid=grid(6144), stream=stream0)
        del primals_24
        # Topologically Sorted Source Nodes: [input_17], Original ATen: [aten.convolution]
        buf24 = extern_kernels.convolution(buf23, primals_26, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf24, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf25 = buf24; del buf24  # reuse
        # Topologically Sorted Source Nodes: [input_17], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_1.run(buf25, primals_27, 6144, grid=grid(6144), stream=stream0)
        del primals_27
        buf26 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_2], Original ATen: [aten.cat]
        triton_poi_fused_cat_2.run(buf20, buf23, buf25, primals_28, buf26, 18432, grid=grid(18432), stream=stream0)
        # Topologically Sorted Source Nodes: [input_19], Original ATen: [aten.convolution]
        buf27 = extern_kernels.convolution(buf26, primals_29, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf27, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf28 = buf27; del buf27  # reuse
        buf29 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_19, input_20], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf28, primals_30, primals_31, buf29, 6144, grid=grid(6144), stream=stream0)
        del primals_30
        # Topologically Sorted Source Nodes: [input_21], Original ATen: [aten.convolution]
        buf30 = extern_kernels.convolution(buf29, primals_32, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf30, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf31 = buf30; del buf30  # reuse
        buf32 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_21, input_22], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf31, primals_33, primals_34, buf32, 6144, grid=grid(6144), stream=stream0)
        del primals_33
        # Topologically Sorted Source Nodes: [input_23], Original ATen: [aten.convolution]
        buf33 = extern_kernels.convolution(buf32, primals_35, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf33, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf34 = buf33; del buf33  # reuse
        # Topologically Sorted Source Nodes: [input_23], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_1.run(buf34, primals_36, 6144, grid=grid(6144), stream=stream0)
        del primals_36
        buf35 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_3], Original ATen: [aten.cat]
        triton_poi_fused_cat_2.run(buf29, buf32, buf34, primals_37, buf35, 18432, grid=grid(18432), stream=stream0)
        # Topologically Sorted Source Nodes: [input_25], Original ATen: [aten.convolution]
        buf36 = extern_kernels.convolution(buf35, primals_38, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf36, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf37 = buf36; del buf36  # reuse
        buf38 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_25, input_26], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf37, primals_39, primals_40, buf38, 6144, grid=grid(6144), stream=stream0)
        del primals_39
        # Topologically Sorted Source Nodes: [input_27], Original ATen: [aten.convolution]
        buf39 = extern_kernels.convolution(buf38, primals_41, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf39, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf40 = buf39; del buf39  # reuse
        buf41 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_27, input_28], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_0.run(buf40, primals_42, primals_43, buf41, 6144, grid=grid(6144), stream=stream0)
        del primals_42
        # Topologically Sorted Source Nodes: [input_29], Original ATen: [aten.convolution]
        buf42 = extern_kernels.convolution(buf41, primals_44, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf42, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf43 = buf42; del buf42  # reuse
        # Topologically Sorted Source Nodes: [input_29], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_1.run(buf43, primals_45, 6144, grid=grid(6144), stream=stream0)
        del primals_45
        buf44 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_4], Original ATen: [aten.cat]
        triton_poi_fused_cat_2.run(buf38, buf41, buf43, primals_46, buf44, 18432, grid=grid(18432), stream=stream0)
        # Topologically Sorted Source Nodes: [input_31], Original ATen: [aten.convolution]
        buf45 = extern_kernels.convolution(buf44, primals_47, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf45, (4, 8, 4, 4), (128, 16, 4, 1))
        buf46 = buf45; del buf45  # reuse
        buf47 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_31, input_32], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_3.run(buf46, primals_48, primals_49, buf47, 512, grid=grid(512), stream=stream0)
        del primals_48
        # Topologically Sorted Source Nodes: [input_33], Original ATen: [aten.convolution]
        buf48 = extern_kernels.convolution(buf47, primals_50, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf48, (4, 4, 4, 4), (64, 16, 4, 1))
        buf49 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [x], Original ATen: [aten.cat]
        triton_poi_fused_cat_4.run(primals_3, buf48, primals_51, buf49, 512, grid=grid(512), stream=stream0)
        del primals_51
        # Topologically Sorted Source Nodes: [input_34], Original ATen: [aten.convolution]
        buf50 = extern_kernels.convolution(buf49, primals_52, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf50, (4, 4, 4, 4), (64, 16, 4, 1))
        buf51 = buf50; del buf50  # reuse
        buf52 = buf48; del buf48  # reuse
        # Topologically Sorted Source Nodes: [input_34, input_35], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf51, primals_53, primals_54, buf52, 256, grid=grid(256), stream=stream0)
        del primals_53
        # Topologically Sorted Source Nodes: [input_36], Original ATen: [aten.convolution]
        buf53 = extern_kernels.convolution(buf52, primals_55, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf53, (4, 4, 4, 4), (64, 16, 4, 1))
        buf54 = buf53; del buf53  # reuse
        buf55 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_36, input_37], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf54, primals_56, primals_57, buf55, 256, grid=grid(256), stream=stream0)
        del primals_56
        # Topologically Sorted Source Nodes: [input_38], Original ATen: [aten.convolution]
        buf56 = extern_kernels.convolution(buf55, primals_58, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf56, (4, 4, 4, 4), (64, 16, 4, 1))
        buf57 = buf56; del buf56  # reuse
        # Topologically Sorted Source Nodes: [input_38], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf57, primals_59, 256, grid=grid(256), stream=stream0)
        del primals_59
        buf58 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_5], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf52, buf55, buf57, primals_60, buf58, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_40], Original ATen: [aten.convolution]
        buf59 = extern_kernels.convolution(buf58, primals_61, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf59, (4, 4, 4, 4), (64, 16, 4, 1))
        buf60 = buf59; del buf59  # reuse
        buf61 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_40, input_41], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf60, primals_62, primals_63, buf61, 256, grid=grid(256), stream=stream0)
        del primals_62
        # Topologically Sorted Source Nodes: [input_42], Original ATen: [aten.convolution]
        buf62 = extern_kernels.convolution(buf61, primals_64, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf62, (4, 4, 4, 4), (64, 16, 4, 1))
        buf63 = buf62; del buf62  # reuse
        buf64 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_42, input_43], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf63, primals_65, primals_66, buf64, 256, grid=grid(256), stream=stream0)
        del primals_65
        # Topologically Sorted Source Nodes: [input_44], Original ATen: [aten.convolution]
        buf65 = extern_kernels.convolution(buf64, primals_67, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf65, (4, 4, 4, 4), (64, 16, 4, 1))
        buf66 = buf65; del buf65  # reuse
        # Topologically Sorted Source Nodes: [input_44], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf66, primals_68, 256, grid=grid(256), stream=stream0)
        del primals_68
        buf67 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_6], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf61, buf64, buf66, primals_69, buf67, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_46], Original ATen: [aten.convolution]
        buf68 = extern_kernels.convolution(buf67, primals_70, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf68, (4, 4, 4, 4), (64, 16, 4, 1))
        buf69 = buf68; del buf68  # reuse
        buf70 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_46, input_47], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf69, primals_71, primals_72, buf70, 256, grid=grid(256), stream=stream0)
        del primals_71
        # Topologically Sorted Source Nodes: [input_48], Original ATen: [aten.convolution]
        buf71 = extern_kernels.convolution(buf70, primals_73, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf71, (4, 4, 4, 4), (64, 16, 4, 1))
        buf72 = buf71; del buf71  # reuse
        buf73 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_48, input_49], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf72, primals_74, primals_75, buf73, 256, grid=grid(256), stream=stream0)
        del primals_74
        # Topologically Sorted Source Nodes: [input_50], Original ATen: [aten.convolution]
        buf74 = extern_kernels.convolution(buf73, primals_76, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 4, 4, 4), (64, 16, 4, 1))
        buf75 = buf74; del buf74  # reuse
        # Topologically Sorted Source Nodes: [input_50], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf75, primals_77, 256, grid=grid(256), stream=stream0)
        del primals_77
        buf76 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_7], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf70, buf73, buf75, primals_78, buf76, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_52], Original ATen: [aten.convolution]
        buf77 = extern_kernels.convolution(buf76, primals_79, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf77, (4, 4, 4, 4), (64, 16, 4, 1))
        buf78 = buf77; del buf77  # reuse
        buf79 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_52, input_53], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf78, primals_80, primals_81, buf79, 256, grid=grid(256), stream=stream0)
        del primals_80
        # Topologically Sorted Source Nodes: [input_54], Original ATen: [aten.convolution]
        buf80 = extern_kernels.convolution(buf79, primals_82, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 4, 4, 4), (64, 16, 4, 1))
        buf81 = buf80; del buf80  # reuse
        buf82 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_54, input_55], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf81, primals_83, primals_84, buf82, 256, grid=grid(256), stream=stream0)
        del primals_83
        # Topologically Sorted Source Nodes: [input_56], Original ATen: [aten.convolution]
        buf83 = extern_kernels.convolution(buf82, primals_85, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf83, (4, 4, 4, 4), (64, 16, 4, 1))
        buf84 = buf83; del buf83  # reuse
        # Topologically Sorted Source Nodes: [input_56], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf84, primals_86, 256, grid=grid(256), stream=stream0)
        del primals_86
        buf85 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_8], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf79, buf82, buf84, primals_87, buf85, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_58], Original ATen: [aten.convolution]
        buf86 = extern_kernels.convolution(buf85, primals_88, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf86, (4, 4, 4, 4), (64, 16, 4, 1))
        buf87 = buf86; del buf86  # reuse
        buf88 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_58, input_59], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf87, primals_89, primals_90, buf88, 256, grid=grid(256), stream=stream0)
        del primals_89
        # Topologically Sorted Source Nodes: [input_60], Original ATen: [aten.convolution]
        buf89 = extern_kernels.convolution(buf88, primals_91, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf89, (4, 4, 4, 4), (64, 16, 4, 1))
        buf90 = buf89; del buf89  # reuse
        buf91 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_60, input_61], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf90, primals_92, primals_93, buf91, 256, grid=grid(256), stream=stream0)
        del primals_92
        # Topologically Sorted Source Nodes: [input_62], Original ATen: [aten.convolution]
        buf92 = extern_kernels.convolution(buf91, primals_94, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf92, (4, 4, 4, 4), (64, 16, 4, 1))
        buf93 = buf92; del buf92  # reuse
        # Topologically Sorted Source Nodes: [input_62], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf93, primals_95, 256, grid=grid(256), stream=stream0)
        del primals_95
        buf94 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_9], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf88, buf91, buf93, primals_96, buf94, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_64], Original ATen: [aten.convolution]
        buf95 = extern_kernels.convolution(buf94, primals_97, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf95, (4, 16, 4, 4), (256, 16, 4, 1))
        buf96 = buf95; del buf95  # reuse
        buf97 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_64, input_65], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_8.run(buf96, primals_98, primals_99, buf97, 1024, grid=grid(1024), stream=stream0)
        del primals_98
        # Topologically Sorted Source Nodes: [input_66], Original ATen: [aten.convolution]
        buf98 = extern_kernels.convolution(buf97, primals_100, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf98, (4, 4, 4, 4), (64, 16, 4, 1))
        buf99 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [x_1], Original ATen: [aten.cat]
        triton_poi_fused_cat_4.run(primals_3, buf98, primals_101, buf99, 512, grid=grid(512), stream=stream0)
        del primals_101
        # Topologically Sorted Source Nodes: [input_67], Original ATen: [aten.convolution]
        buf100 = extern_kernels.convolution(buf99, primals_102, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf100, (4, 4, 4, 4), (64, 16, 4, 1))
        buf101 = buf100; del buf100  # reuse
        buf102 = buf98; del buf98  # reuse
        # Topologically Sorted Source Nodes: [input_67, input_68], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf101, primals_103, primals_104, buf102, 256, grid=grid(256), stream=stream0)
        del primals_103
        # Topologically Sorted Source Nodes: [input_69], Original ATen: [aten.convolution]
        buf103 = extern_kernels.convolution(buf102, primals_105, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf103, (4, 4, 4, 4), (64, 16, 4, 1))
        buf104 = buf103; del buf103  # reuse
        buf105 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_69, input_70], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf104, primals_106, primals_107, buf105, 256, grid=grid(256), stream=stream0)
        del primals_106
        # Topologically Sorted Source Nodes: [input_71], Original ATen: [aten.convolution]
        buf106 = extern_kernels.convolution(buf105, primals_108, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf106, (4, 4, 4, 4), (64, 16, 4, 1))
        buf107 = buf106; del buf106  # reuse
        # Topologically Sorted Source Nodes: [input_71], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf107, primals_109, 256, grid=grid(256), stream=stream0)
        del primals_109
        buf108 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_10], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf102, buf105, buf107, primals_110, buf108, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_73], Original ATen: [aten.convolution]
        buf109 = extern_kernels.convolution(buf108, primals_111, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf109, (4, 4, 4, 4), (64, 16, 4, 1))
        buf110 = buf109; del buf109  # reuse
        buf111 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_73, input_74], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf110, primals_112, primals_113, buf111, 256, grid=grid(256), stream=stream0)
        del primals_112
        # Topologically Sorted Source Nodes: [input_75], Original ATen: [aten.convolution]
        buf112 = extern_kernels.convolution(buf111, primals_114, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf112, (4, 4, 4, 4), (64, 16, 4, 1))
        buf113 = buf112; del buf112  # reuse
        buf114 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_75, input_76], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf113, primals_115, primals_116, buf114, 256, grid=grid(256), stream=stream0)
        del primals_115
        # Topologically Sorted Source Nodes: [input_77], Original ATen: [aten.convolution]
        buf115 = extern_kernels.convolution(buf114, primals_117, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf115, (4, 4, 4, 4), (64, 16, 4, 1))
        buf116 = buf115; del buf115  # reuse
        # Topologically Sorted Source Nodes: [input_77], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf116, primals_118, 256, grid=grid(256), stream=stream0)
        del primals_118
        buf117 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_11], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf111, buf114, buf116, primals_119, buf117, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_79], Original ATen: [aten.convolution]
        buf118 = extern_kernels.convolution(buf117, primals_120, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf118, (4, 4, 4, 4), (64, 16, 4, 1))
        buf119 = buf118; del buf118  # reuse
        buf120 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_79, input_80], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf119, primals_121, primals_122, buf120, 256, grid=grid(256), stream=stream0)
        del primals_121
        # Topologically Sorted Source Nodes: [input_81], Original ATen: [aten.convolution]
        buf121 = extern_kernels.convolution(buf120, primals_123, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf121, (4, 4, 4, 4), (64, 16, 4, 1))
        buf122 = buf121; del buf121  # reuse
        buf123 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_81, input_82], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf122, primals_124, primals_125, buf123, 256, grid=grid(256), stream=stream0)
        del primals_124
        # Topologically Sorted Source Nodes: [input_83], Original ATen: [aten.convolution]
        buf124 = extern_kernels.convolution(buf123, primals_126, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf124, (4, 4, 4, 4), (64, 16, 4, 1))
        buf125 = buf124; del buf124  # reuse
        # Topologically Sorted Source Nodes: [input_83], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf125, primals_127, 256, grid=grid(256), stream=stream0)
        del primals_127
        buf126 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_12], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf120, buf123, buf125, primals_128, buf126, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_85], Original ATen: [aten.convolution]
        buf127 = extern_kernels.convolution(buf126, primals_129, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf127, (4, 4, 4, 4), (64, 16, 4, 1))
        buf128 = buf127; del buf127  # reuse
        buf129 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_85, input_86], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf128, primals_130, primals_131, buf129, 256, grid=grid(256), stream=stream0)
        del primals_130
        # Topologically Sorted Source Nodes: [input_87], Original ATen: [aten.convolution]
        buf130 = extern_kernels.convolution(buf129, primals_132, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf130, (4, 4, 4, 4), (64, 16, 4, 1))
        buf131 = buf130; del buf130  # reuse
        buf132 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_87, input_88], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf131, primals_133, primals_134, buf132, 256, grid=grid(256), stream=stream0)
        del primals_133
        # Topologically Sorted Source Nodes: [input_89], Original ATen: [aten.convolution]
        buf133 = extern_kernels.convolution(buf132, primals_135, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf133, (4, 4, 4, 4), (64, 16, 4, 1))
        buf134 = buf133; del buf133  # reuse
        # Topologically Sorted Source Nodes: [input_89], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf134, primals_136, 256, grid=grid(256), stream=stream0)
        del primals_136
        buf135 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_13], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf129, buf132, buf134, primals_137, buf135, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_91], Original ATen: [aten.convolution]
        buf136 = extern_kernels.convolution(buf135, primals_138, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf136, (4, 4, 4, 4), (64, 16, 4, 1))
        buf137 = buf136; del buf136  # reuse
        buf138 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_91, input_92], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf137, primals_139, primals_140, buf138, 256, grid=grid(256), stream=stream0)
        del primals_139
        # Topologically Sorted Source Nodes: [input_93], Original ATen: [aten.convolution]
        buf139 = extern_kernels.convolution(buf138, primals_141, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf139, (4, 4, 4, 4), (64, 16, 4, 1))
        buf140 = buf139; del buf139  # reuse
        buf141 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_93, input_94], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf140, primals_142, primals_143, buf141, 256, grid=grid(256), stream=stream0)
        del primals_142
        # Topologically Sorted Source Nodes: [input_95], Original ATen: [aten.convolution]
        buf142 = extern_kernels.convolution(buf141, primals_144, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf142, (4, 4, 4, 4), (64, 16, 4, 1))
        buf143 = buf142; del buf142  # reuse
        # Topologically Sorted Source Nodes: [input_95], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf143, primals_145, 256, grid=grid(256), stream=stream0)
        del primals_145
        buf144 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_14], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf138, buf141, buf143, primals_146, buf144, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_97], Original ATen: [aten.convolution]
        buf145 = extern_kernels.convolution(buf144, primals_147, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf145, (4, 16, 4, 4), (256, 16, 4, 1))
        buf146 = buf145; del buf145  # reuse
        buf147 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_97, input_98], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_8.run(buf146, primals_148, primals_149, buf147, 1024, grid=grid(1024), stream=stream0)
        del primals_148
        # Topologically Sorted Source Nodes: [input_99], Original ATen: [aten.convolution]
        buf148 = extern_kernels.convolution(buf147, primals_150, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf148, (4, 4, 4, 4), (64, 16, 4, 1))
        buf149 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [x_2], Original ATen: [aten.cat]
        triton_poi_fused_cat_4.run(primals_3, buf148, primals_151, buf149, 512, grid=grid(512), stream=stream0)
        del primals_151
        # Topologically Sorted Source Nodes: [input_100], Original ATen: [aten.convolution]
        buf150 = extern_kernels.convolution(buf149, primals_152, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf150, (4, 4, 4, 4), (64, 16, 4, 1))
        buf151 = buf150; del buf150  # reuse
        buf152 = buf148; del buf148  # reuse
        # Topologically Sorted Source Nodes: [input_100, input_101], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf151, primals_153, primals_154, buf152, 256, grid=grid(256), stream=stream0)
        del primals_153
        # Topologically Sorted Source Nodes: [input_102], Original ATen: [aten.convolution]
        buf153 = extern_kernels.convolution(buf152, primals_155, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf153, (4, 4, 4, 4), (64, 16, 4, 1))
        buf154 = buf153; del buf153  # reuse
        buf155 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_102, input_103], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf154, primals_156, primals_157, buf155, 256, grid=grid(256), stream=stream0)
        del primals_156
        # Topologically Sorted Source Nodes: [input_104], Original ATen: [aten.convolution]
        buf156 = extern_kernels.convolution(buf155, primals_158, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf156, (4, 4, 4, 4), (64, 16, 4, 1))
        buf157 = buf156; del buf156  # reuse
        # Topologically Sorted Source Nodes: [input_104], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf157, primals_159, 256, grid=grid(256), stream=stream0)
        del primals_159
        buf158 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_15], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf152, buf155, buf157, primals_160, buf158, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_106], Original ATen: [aten.convolution]
        buf159 = extern_kernels.convolution(buf158, primals_161, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf159, (4, 4, 4, 4), (64, 16, 4, 1))
        buf160 = buf159; del buf159  # reuse
        buf161 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_106, input_107], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf160, primals_162, primals_163, buf161, 256, grid=grid(256), stream=stream0)
        del primals_162
        # Topologically Sorted Source Nodes: [input_108], Original ATen: [aten.convolution]
        buf162 = extern_kernels.convolution(buf161, primals_164, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf162, (4, 4, 4, 4), (64, 16, 4, 1))
        buf163 = buf162; del buf162  # reuse
        buf164 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_108, input_109], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf163, primals_165, primals_166, buf164, 256, grid=grid(256), stream=stream0)
        del primals_165
        # Topologically Sorted Source Nodes: [input_110], Original ATen: [aten.convolution]
        buf165 = extern_kernels.convolution(buf164, primals_167, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf165, (4, 4, 4, 4), (64, 16, 4, 1))
        buf166 = buf165; del buf165  # reuse
        # Topologically Sorted Source Nodes: [input_110], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf166, primals_168, 256, grid=grid(256), stream=stream0)
        del primals_168
        buf167 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_16], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf161, buf164, buf166, primals_169, buf167, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_112], Original ATen: [aten.convolution]
        buf168 = extern_kernels.convolution(buf167, primals_170, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf168, (4, 4, 4, 4), (64, 16, 4, 1))
        buf169 = buf168; del buf168  # reuse
        buf170 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_112, input_113], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf169, primals_171, primals_172, buf170, 256, grid=grid(256), stream=stream0)
        del primals_171
        # Topologically Sorted Source Nodes: [input_114], Original ATen: [aten.convolution]
        buf171 = extern_kernels.convolution(buf170, primals_173, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf171, (4, 4, 4, 4), (64, 16, 4, 1))
        buf172 = buf171; del buf171  # reuse
        buf173 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_114, input_115], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf172, primals_174, primals_175, buf173, 256, grid=grid(256), stream=stream0)
        del primals_174
        # Topologically Sorted Source Nodes: [input_116], Original ATen: [aten.convolution]
        buf174 = extern_kernels.convolution(buf173, primals_176, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf174, (4, 4, 4, 4), (64, 16, 4, 1))
        buf175 = buf174; del buf174  # reuse
        # Topologically Sorted Source Nodes: [input_116], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf175, primals_177, 256, grid=grid(256), stream=stream0)
        del primals_177
        buf176 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_17], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf170, buf173, buf175, primals_178, buf176, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_118], Original ATen: [aten.convolution]
        buf177 = extern_kernels.convolution(buf176, primals_179, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf177, (4, 4, 4, 4), (64, 16, 4, 1))
        buf178 = buf177; del buf177  # reuse
        buf179 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_118, input_119], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf178, primals_180, primals_181, buf179, 256, grid=grid(256), stream=stream0)
        del primals_180
        # Topologically Sorted Source Nodes: [input_120], Original ATen: [aten.convolution]
        buf180 = extern_kernels.convolution(buf179, primals_182, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf180, (4, 4, 4, 4), (64, 16, 4, 1))
        buf181 = buf180; del buf180  # reuse
        buf182 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_120, input_121], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf181, primals_183, primals_184, buf182, 256, grid=grid(256), stream=stream0)
        del primals_183
        # Topologically Sorted Source Nodes: [input_122], Original ATen: [aten.convolution]
        buf183 = extern_kernels.convolution(buf182, primals_185, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf183, (4, 4, 4, 4), (64, 16, 4, 1))
        buf184 = buf183; del buf183  # reuse
        # Topologically Sorted Source Nodes: [input_122], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf184, primals_186, 256, grid=grid(256), stream=stream0)
        del primals_186
        buf185 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_18], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf179, buf182, buf184, primals_187, buf185, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_124], Original ATen: [aten.convolution]
        buf186 = extern_kernels.convolution(buf185, primals_188, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf186, (4, 4, 4, 4), (64, 16, 4, 1))
        buf187 = buf186; del buf186  # reuse
        buf188 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_124, input_125], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf187, primals_189, primals_190, buf188, 256, grid=grid(256), stream=stream0)
        del primals_189
        # Topologically Sorted Source Nodes: [input_126], Original ATen: [aten.convolution]
        buf189 = extern_kernels.convolution(buf188, primals_191, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf189, (4, 4, 4, 4), (64, 16, 4, 1))
        buf190 = buf189; del buf189  # reuse
        buf191 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_126, input_127], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_5.run(buf190, primals_192, primals_193, buf191, 256, grid=grid(256), stream=stream0)
        del primals_192
        # Topologically Sorted Source Nodes: [input_128], Original ATen: [aten.convolution]
        buf192 = extern_kernels.convolution(buf191, primals_194, stride=(1, 1), padding=(1, 1), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf192, (4, 4, 4, 4), (64, 16, 4, 1))
        buf193 = buf192; del buf192  # reuse
        # Topologically Sorted Source Nodes: [input_128], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf193, primals_195, 256, grid=grid(256), stream=stream0)
        del primals_195
        buf194 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [out_19], Original ATen: [aten.cat]
        triton_poi_fused_cat_7.run(buf188, buf191, buf193, primals_196, buf194, 768, grid=grid(768), stream=stream0)
        # Topologically Sorted Source Nodes: [input_130], Original ATen: [aten.convolution]
        buf195 = extern_kernels.convolution(buf194, primals_197, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf195, (4, 16, 4, 4), (256, 16, 4, 1))
        buf196 = buf195; del buf195  # reuse
        buf197 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.float32)
        # Topologically Sorted Source Nodes: [input_130, input_131], Original ATen: [aten.convolution, aten._prelu_kernel]
        triton_poi_fused__prelu_kernel_convolution_8.run(buf196, primals_198, primals_199, buf197, 1024, grid=grid(1024), stream=stream0)
        del primals_198
        # Topologically Sorted Source Nodes: [input_132], Original ATen: [aten.convolution]
        buf198 = extern_kernels.convolution(buf197, primals_200, stride=(1, 1), padding=(0, 0), dilation=(1, 1), transposed=False, output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf198, (4, 4, 4, 4), (64, 16, 4, 1))
        buf199 = buf198; del buf198  # reuse
        # Topologically Sorted Source Nodes: [input_132], Original ATen: [aten.convolution]
        triton_poi_fused_convolution_6.run(buf199, primals_201, 256, grid=grid(256), stream=stream0)
        del primals_201
    return (buf199, primals_1, primals_3, primals_4, primals_5, primals_7, primals_8, primals_10, primals_11, primals_13, primals_14, primals_16, primals_17, primals_19, primals_20, primals_22, primals_23, primals_25, primals_26, primals_28, primals_29, primals_31, primals_32, primals_34, primals_35, primals_37, primals_38, primals_40, primals_41, primals_43, primals_44, primals_46, primals_47, primals_49, primals_50, primals_52, primals_54, primals_55, primals_57, primals_58, primals_60, primals_61, primals_63, primals_64, primals_66, primals_67, primals_69, primals_70, primals_72, primals_73, primals_75, primals_76, primals_78, primals_79, primals_81, primals_82, primals_84, primals_85, primals_87, primals_88, primals_90, primals_91, primals_93, primals_94, primals_96, primals_97, primals_99, primals_100, primals_102, primals_104, primals_105, primals_107, primals_108, primals_110, primals_111, primals_113, primals_114, primals_116, primals_117, primals_119, primals_120, primals_122, primals_123, primals_125, primals_126, primals_128, primals_129, primals_131, primals_132, primals_134, primals_135, primals_137, primals_138, primals_140, primals_141, primals_143, primals_144, primals_146, primals_147, primals_149, primals_150, primals_152, primals_154, primals_155, primals_157, primals_158, primals_160, primals_161, primals_163, primals_164, primals_166, primals_167, primals_169, primals_170, primals_172, primals_173, primals_175, primals_176, primals_178, primals_179, primals_181, primals_182, primals_184, primals_185, primals_187, primals_188, primals_190, primals_191, primals_193, primals_194, primals_196, primals_197, primals_199, primals_200, buf1, buf2, buf4, buf5, buf7, buf8, buf10, buf11, buf13, buf14, buf16, buf17, buf19, buf20, buf22, buf23, buf25, buf26, buf28, buf29, buf31, buf32, buf34, buf35, buf37, buf38, buf40, buf41, buf43, buf44, buf46, buf47, buf49, buf51, buf52, buf54, buf55, buf57, buf58, buf60, buf61, buf63, buf64, buf66, buf67, buf69, buf70, buf72, buf73, buf75, buf76, buf78, buf79, buf81, buf82, buf84, buf85, buf87, buf88, buf90, buf91, buf93, buf94, buf96, buf97, buf99, buf101, buf102, buf104, buf105, buf107, buf108, buf110, buf111, buf113, buf114, buf116, buf117, buf119, buf120, buf122, buf123, buf125, buf126, buf128, buf129, buf131, buf132, buf134, buf135, buf137, buf138, buf140, buf141, buf143, buf144, buf146, buf147, buf149, buf151, buf152, buf154, buf155, buf157, buf158, buf160, buf161, buf163, buf164, buf166, buf167, buf169, buf170, buf172, buf173, buf175, buf176, buf178, buf179, buf181, buf182, buf184, buf185, buf187, buf188, buf190, buf191, buf193, buf194, buf196, buf197, )


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((96, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_2 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_3 = rand_strided((4, 4, 4, 4), (64, 16, 4, 1), device='cuda:0', dtype=torch.float32)
    primals_4 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_5 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_6 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_7 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_8 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_9 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_10 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_11 = rand_strided((96, 288, 3, 3), (2592, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_12 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_13 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_14 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_15 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_16 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_17 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_18 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_19 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_20 = rand_strided((96, 288, 3, 3), (2592, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_21 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_22 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_23 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_24 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_25 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_26 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_27 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_28 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_29 = rand_strided((96, 288, 3, 3), (2592, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_30 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_31 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_32 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_33 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_34 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_35 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_36 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_37 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_38 = rand_strided((96, 288, 3, 3), (2592, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_39 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_40 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_41 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_42 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_43 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_44 = rand_strided((96, 96, 3, 3), (864, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_45 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_46 = rand_strided((96, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_47 = rand_strided((8, 288, 1, 1), (288, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_48 = rand_strided((8, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_49 = rand_strided((8, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_50 = rand_strided((4, 8, 1, 1), (8, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_51 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_52 = rand_strided((4, 8, 3, 3), (72, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_53 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_54 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_55 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_56 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_57 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_58 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_59 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_60 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_61 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_62 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_63 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_64 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_65 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_66 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_67 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_68 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_69 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_70 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_71 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_72 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_73 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_74 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_75 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_76 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_77 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_78 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_79 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_80 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_81 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_82 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_83 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_84 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_85 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_86 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_87 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_88 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_89 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_90 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_91 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_92 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_93 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_94 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_95 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_96 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_97 = rand_strided((16, 12, 1, 1), (12, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_98 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_99 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_100 = rand_strided((4, 16, 1, 1), (16, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_101 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_102 = rand_strided((4, 8, 3, 3), (72, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_103 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_104 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_105 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_106 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_107 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_108 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_109 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_110 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_111 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_112 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_113 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_114 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_115 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_116 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_117 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_118 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_119 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_120 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_121 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_122 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_123 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_124 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_125 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_126 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_127 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_128 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_129 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_130 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_131 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_132 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_133 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_134 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_135 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_136 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_137 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_138 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_139 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_140 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_141 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_142 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_143 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_144 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_145 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_146 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_147 = rand_strided((16, 12, 1, 1), (12, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_148 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_149 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_150 = rand_strided((4, 16, 1, 1), (16, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_151 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_152 = rand_strided((4, 8, 3, 3), (72, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_153 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_154 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_155 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_156 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_157 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_158 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_159 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_160 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_161 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_162 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_163 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_164 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_165 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_166 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_167 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_168 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_169 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_170 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_171 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_172 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_173 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_174 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_175 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_176 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_177 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_178 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_179 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_180 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_181 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_182 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_183 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_184 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_185 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_186 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_187 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_188 = rand_strided((4, 12, 3, 3), (108, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_189 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_190 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_191 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_192 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_193 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_194 = rand_strided((4, 4, 3, 3), (36, 9, 3, 1), device='cuda:0', dtype=torch.float32)
    primals_195 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_196 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_197 = rand_strided((16, 12, 1, 1), (12, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_198 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_199 = rand_strided((16, ), (1, ), device='cuda:0', dtype=torch.float32)
    primals_200 = rand_strided((4, 16, 1, 1), (16, 1, 1, 1), device='cuda:0', dtype=torch.float32)
    primals_201 = rand_strided((4, ), (1, ), device='cuda:0', dtype=torch.float32)
    fn = lambda: call([primals_1, primals_2, primals_3, primals_4, primals_5, primals_6, primals_7, primals_8, primals_9, primals_10, primals_11, primals_12, primals_13, primals_14, primals_15, primals_16, primals_17, primals_18, primals_19, primals_20, primals_21, primals_22, primals_23, primals_24, primals_25, primals_26, primals_27, primals_28, primals_29, primals_30, primals_31, primals_32, primals_33, primals_34, primals_35, primals_36, primals_37, primals_38, primals_39, primals_40, primals_41, primals_42, primals_43, primals_44, primals_45, primals_46, primals_47, primals_48, primals_49, primals_50, primals_51, primals_52, primals_53, primals_54, primals_55, primals_56, primals_57, primals_58, primals_59, primals_60, primals_61, primals_62, primals_63, primals_64, primals_65, primals_66, primals_67, primals_68, primals_69, primals_70, primals_71, primals_72, primals_73, primals_74, primals_75, primals_76, primals_77, primals_78, primals_79, primals_80, primals_81, primals_82, primals_83, primals_84, primals_85, primals_86, primals_87, primals_88, primals_89, primals_90, primals_91, primals_92, primals_93, primals_94, primals_95, primals_96, primals_97, primals_98, primals_99, primals_100, primals_101, primals_102, primals_103, primals_104, primals_105, primals_106, primals_107, primals_108, primals_109, primals_110, primals_111, primals_112, primals_113, primals_114, primals_115, primals_116, primals_117, primals_118, primals_119, primals_120, primals_121, primals_122, primals_123, primals_124, primals_125, primals_126, primals_127, primals_128, primals_129, primals_130, primals_131, primals_132, primals_133, primals_134, primals_135, primals_136, primals_137, primals_138, primals_139, primals_140, primals_141, primals_142, primals_143, primals_144, primals_145, primals_146, primals_147, primals_148, primals_149, primals_150, primals_151, primals_152, primals_153, primals_154, primals_155, primals_156, primals_157, primals_158, primals_159, primals_160, primals_161, primals_162, primals_163, primals_164, primals_165, primals_166, primals_167, primals_168, primals_169, primals_170, primals_171, primals_172, primals_173, primals_174, primals_175, primals_176, primals_177, primals_178, primals_179, primals_180, primals_181, primals_182, primals_183, primals_184, primals_185, primals_186, primals_187, primals_188, primals_189, primals_190, primals_191, primals_192, primals_193, primals_194, primals_195, primals_196, primals_197, primals_198, primals_199, primals_200, primals_201])
    return print_performance(fn, times=times, repeat=repeat)


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

import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from itertools import chain as chain
from collections import OrderedDict
import torch.hub


class concatLayer(nn.Module):

    def __init__(self, in_channels, out_channels_perSub, i, j, appendix):
        super(concatLayer, self).__init__()
        self.firstSub = self.concatLayerSub(in_channels,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_0')
        self.secondSub = self.concatLayerSub(out_channels_perSub,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_1')
        self.thirdSub = self.concatLayerSub(out_channels_perSub,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_2')

    def forward(self, x):
        firstSub = self.firstSub(x)
        secondSub = self.secondSub(firstSub)
        thirdSub = self.thirdSub(secondSub)
        out = torch.cat([firstSub, secondSub, thirdSub], 1)
        return out

    def concatLayerSub(self, in_channels, out_channels, layerName):
        concatLayerSubOrdered = OrderedDict()
        conv2d = nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1)
        concatLayerSubOrdered.update({('Mconv' + layerName): conv2d})
        concatLayerSubOrdered.update({('Mprelu' + layerName): nn.PReLU(
            out_channels)})
        return nn.Sequential(concatLayerSubOrdered)


class stage(nn.Module):

    def __init__(self, stageID, in_channels, out_channels_perSub,
        mid_channels, out_channels, appendix):
        super(stage, self).__init__()
        self.firstConcat = concatLayer(in_channels, out_channels_perSub, 1,
            stageID, appendix)
        self.secondConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 2, stageID, appendix)
        self.thirdConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 3, stageID, appendix)
        self.fourthConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 4, stageID, appendix)
        self.fifthConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 5, stageID, appendix)
        conv2d = nn.Conv2d(3 * out_channels_perSub, mid_channels,
            kernel_size=1, padding=0)
        prelu = nn.PReLU(mid_channels)
        self.afterConcatsFirst = nn.Sequential(OrderedDict({(
            'Mconv6_stage%d_%s' % (stageID, appendix)): conv2d, (
            'Mprelu6_stage%d_%s' % (stageID, appendix)): prelu}))
        conv2d = nn.Conv2d(mid_channels, out_channels, kernel_size=1, padding=0
            )
        self.afterConcatsSecond = nn.Sequential(OrderedDict({(
            'Mconv7_stage%d_%s' % (stageID, appendix)): conv2d}))

    def forward(self, x):
        x = self.firstConcat(x)
        x = self.secondConcat(x)
        x = self.thirdConcat(x)
        x = self.fourthConcat(x)
        x = self.fifthConcat(x)
        x = self.afterConcatsFirst(x)
        out = self.afterConcatsSecond(x)
        return out


class L2Part(nn.Module):

    def __init__(self, in_channels, stage_out_channels):
        super(L2Part, self).__init__()
        self.firstStage = stage(0, in_channels, 96, in_channels * 2,
            stage_out_channels, 'L2')
        self.secondStage = stage(1, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')
        self.thirdStage = stage(2, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')
        self.fourthStage = stage(3, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')

    def forward(self, features):
        x = self.firstStage(features)
        x = torch.cat([features, x], 1)
        x = self.secondStage(x)
        x = torch.cat([features, x], 1)
        x = self.thirdStage(x)
        x = torch.cat([features, x], 1)
        out = self.fourthStage(x)
        return out


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


def get_init_inputs():
    return [[], {'in_channels': 4, 'stage_out_channels': 4}]

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
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from itertools import chain as chain
from collections import OrderedDict
import torch.hub
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__prelu_kernel_convolution_0(in_out_ptr0, in_ptr0,
    in_ptr1, out_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 // 16 % 96
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, None)
    tl.store(out_ptr0 + x3, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_1(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 // 16 % 96
    tmp0 = tl.load(in_out_ptr0 + x3, None)
    tmp1 = tl.load(in_ptr0 + x1, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, None)


@triton.jit
def triton_poi_fused_cat_2(in_ptr0, in_ptr1, in_ptr2, in_ptr3, out_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x1 = xindex // 16 % 288
    x0 = xindex % 16
    x2 = xindex // 4608
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 96, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 16 * x1 + 1536 * x2), tmp4, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 192, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (x0 + 16 * (-96 + x1) + 1536 * x2), tmp9,
        other=0.0)
    tmp11 = tmp0 >= tmp7
    tl.full([1], 288, tl.int64)
    tmp14 = tl.load(in_ptr2 + (x0 + 16 * (-192 + x1) + 1536 * x2), tmp11,
        other=0.0)
    tmp15 = 0.0
    tmp16 = tmp14 > tmp15
    tmp17 = tl.load(in_ptr3 + (-192 + x1), tmp11, eviction_policy=
        'evict_last', other=0.0)
    tmp18 = tmp17 * tmp14
    tmp19 = tl.where(tmp16, tmp14, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp11, tmp19, tmp20)
    tmp22 = tl.where(tmp9, tmp10, tmp21)
    tmp23 = tl.where(tmp4, tmp5, tmp22)
    tl.store(out_ptr0 + x3, tmp23, None)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_3(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 512
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 8
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + x3, tmp7, xmask)


@triton.jit
def triton_poi_fused_cat_4(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 512
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 16 % 8
    x0 = xindex % 16
    x2 = xindex // 128
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 16 * x1 + 64 * x2), tmp4 & xmask, other=0.0)
    tmp6 = tmp0 >= tmp3
    tl.full([1], 8, tl.int64)
    tmp9 = tl.load(in_ptr1 + (x0 + 16 * (-4 + x1) + 64 * x2), tmp6 & xmask,
        other=0.0)
    tmp10 = tl.load(in_ptr2 + (-4 + x1), tmp6 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp11 = tmp9 + tmp10
    tmp12 = tl.full(tmp11.shape, 0.0, tmp11.dtype)
    tmp13 = tl.where(tmp6, tmp11, tmp12)
    tmp14 = tl.where(tmp4, tmp5, tmp13)
    tl.store(out_ptr0 + x3, tmp14, xmask)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_5(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 4
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + x3, tmp7, xmask)


@triton.jit
def triton_poi_fused_convolution_6(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 4
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)


@triton.jit
def triton_poi_fused_cat_7(in_ptr0, in_ptr1, in_ptr2, in_ptr3, out_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xnumel = 768
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 16 % 12
    x0 = xindex % 16
    x2 = xindex // 192
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 16 * x1 + 64 * x2), tmp4 & xmask, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 8, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (x0 + 16 * (-4 + x1) + 64 * x2), tmp9 & xmask,
        other=0.0)
    tmp11 = tmp0 >= tmp7
    tl.full([1], 12, tl.int64)
    tmp14 = tl.load(in_ptr2 + (x0 + 16 * (-8 + x1) + 64 * x2), tmp11 &
        xmask, other=0.0)
    tmp15 = 0.0
    tmp16 = tmp14 > tmp15
    tmp17 = tl.load(in_ptr3 + (-8 + x1), tmp11 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp18 = tmp17 * tmp14
    tmp19 = tl.where(tmp16, tmp14, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp11, tmp19, tmp20)
    tmp22 = tl.where(tmp9, tmp10, tmp21)
    tmp23 = tl.where(tmp4, tmp5, tmp22)
    tl.store(out_ptr0 + x3, tmp23, xmask)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_8(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 1024
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 16
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + x3, tmp7, xmask)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9, primals_10, primals_11, primals_12,
        primals_13, primals_14, primals_15, primals_16, primals_17,
        primals_18, primals_19, primals_20, primals_21, primals_22,
        primals_23, primals_24, primals_25, primals_26, primals_27,
        primals_28, primals_29, primals_30, primals_31, primals_32,
        primals_33, primals_34, primals_35, primals_36, primals_37,
        primals_38, primals_39, primals_40, primals_41, primals_42,
        primals_43, primals_44, primals_45, primals_46, primals_47,
        primals_48, primals_49, primals_50, primals_51, primals_52,
        primals_53, primals_54, primals_55, primals_56, primals_57,
        primals_58, primals_59, primals_60, primals_61, primals_62,
        primals_63, primals_64, primals_65, primals_66, primals_67,
        primals_68, primals_69, primals_70, primals_71, primals_72,
        primals_73, primals_74, primals_75, primals_76, primals_77,
        primals_78, primals_79, primals_80, primals_81, primals_82,
        primals_83, primals_84, primals_85, primals_86, primals_87,
        primals_88, primals_89, primals_90, primals_91, primals_92,
        primals_93, primals_94, primals_95, primals_96, primals_97,
        primals_98, primals_99, primals_100, primals_101, primals_102,
        primals_103, primals_104, primals_105, primals_106, primals_107,
        primals_108, primals_109, primals_110, primals_111, primals_112,
        primals_113, primals_114, primals_115, primals_116, primals_117,
        primals_118, primals_119, primals_120, primals_121, primals_122,
        primals_123, primals_124, primals_125, primals_126, primals_127,
        primals_128, primals_129, primals_130, primals_131, primals_132,
        primals_133, primals_134, primals_135, primals_136, primals_137,
        primals_138, primals_139, primals_140, primals_141, primals_142,
        primals_143, primals_144, primals_145, primals_146, primals_147,
        primals_148, primals_149, primals_150, primals_151, primals_152,
        primals_153, primals_154, primals_155, primals_156, primals_157,
        primals_158, primals_159, primals_160, primals_161, primals_162,
        primals_163, primals_164, primals_165, primals_166, primals_167,
        primals_168, primals_169, primals_170, primals_171, primals_172,
        primals_173, primals_174, primals_175, primals_176, primals_177,
        primals_178, primals_179, primals_180, primals_181, primals_182,
        primals_183, primals_184, primals_185, primals_186, primals_187,
        primals_188, primals_189, primals_190, primals_191, primals_192,
        primals_193, primals_194, primals_195, primals_196, primals_197,
        primals_198, primals_199, primals_200, primals_201) = args
    args.clear()
    assert_size_stride(primals_1, (96, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_2, (96,), (1,))
    assert_size_stride(primals_3, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_4, (96,), (1,))
    assert_size_stride(primals_5, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_6, (96,), (1,))
    assert_size_stride(primals_7, (96,), (1,))
    assert_size_stride(primals_8, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_9, (96,), (1,))
    assert_size_stride(primals_10, (96,), (1,))
    assert_size_stride(primals_11, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_12, (96,), (1,))
    assert_size_stride(primals_13, (96,), (1,))
    assert_size_stride(primals_14, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_15, (96,), (1,))
    assert_size_stride(primals_16, (96,), (1,))
    assert_size_stride(primals_17, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_18, (96,), (1,))
    assert_size_stride(primals_19, (96,), (1,))
    assert_size_stride(primals_20, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_21, (96,), (1,))
    assert_size_stride(primals_22, (96,), (1,))
    assert_size_stride(primals_23, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_24, (96,), (1,))
    assert_size_stride(primals_25, (96,), (1,))
    assert_size_stride(primals_26, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_27, (96,), (1,))
    assert_size_stride(primals_28, (96,), (1,))
    assert_size_stride(primals_29, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_30, (96,), (1,))
    assert_size_stride(primals_31, (96,), (1,))
    assert_size_stride(primals_32, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_33, (96,), (1,))
    assert_size_stride(primals_34, (96,), (1,))
    assert_size_stride(primals_35, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_36, (96,), (1,))
    assert_size_stride(primals_37, (96,), (1,))
    assert_size_stride(primals_38, (96, 288, 3, 3), (2592, 9, 3, 1))
    assert_size_stride(primals_39, (96,), (1,))
    assert_size_stride(primals_40, (96,), (1,))
    assert_size_stride(primals_41, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_42, (96,), (1,))
    assert_size_stride(primals_43, (96,), (1,))
    assert_size_stride(primals_44, (96, 96, 3, 3), (864, 9, 3, 1))
    assert_size_stride(primals_45, (96,), (1,))
    assert_size_stride(primals_46, (96,), (1,))
    assert_size_stride(primals_47, (8, 288, 1, 1), (288, 1, 1, 1))
    assert_size_stride(primals_48, (8,), (1,))
    assert_size_stride(primals_49, (8,), (1,))
    assert_size_stride(primals_50, (4, 8, 1, 1), (8, 1, 1, 1))
    assert_size_stride(primals_51, (4,), (1,))
    assert_size_stride(primals_52, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_53, (4,), (1,))
    assert_size_stride(primals_54, (4,), (1,))
    assert_size_stride(primals_55, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_56, (4,), (1,))
    assert_size_stride(primals_57, (4,), (1,))
    assert_size_stride(primals_58, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_59, (4,), (1,))
    assert_size_stride(primals_60, (4,), (1,))
    assert_size_stride(primals_61, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_62, (4,), (1,))
    assert_size_stride(primals_63, (4,), (1,))
    assert_size_stride(primals_64, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_65, (4,), (1,))
    assert_size_stride(primals_66, (4,), (1,))
    assert_size_stride(primals_67, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_68, (4,), (1,))
    assert_size_stride(primals_69, (4,), (1,))
    assert_size_stride(primals_70, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_71, (4,), (1,))
    assert_size_stride(primals_72, (4,), (1,))
    assert_size_stride(primals_73, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_74, (4,), (1,))
    assert_size_stride(primals_75, (4,), (1,))
    assert_size_stride(primals_76, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_77, (4,), (1,))
    assert_size_stride(primals_78, (4,), (1,))
    assert_size_stride(primals_79, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_80, (4,), (1,))
    assert_size_stride(primals_81, (4,), (1,))
    assert_size_stride(primals_82, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_83, (4,), (1,))
    assert_size_stride(primals_84, (4,), (1,))
    assert_size_stride(primals_85, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_86, (4,), (1,))
    assert_size_stride(primals_87, (4,), (1,))
    assert_size_stride(primals_88, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_89, (4,), (1,))
    assert_size_stride(primals_90, (4,), (1,))
    assert_size_stride(primals_91, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_92, (4,), (1,))
    assert_size_stride(primals_93, (4,), (1,))
    assert_size_stride(primals_94, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_95, (4,), (1,))
    assert_size_stride(primals_96, (4,), (1,))
    assert_size_stride(primals_97, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_98, (16,), (1,))
    assert_size_stride(primals_99, (16,), (1,))
    assert_size_stride(primals_100, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_101, (4,), (1,))
    assert_size_stride(primals_102, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_103, (4,), (1,))
    assert_size_stride(primals_104, (4,), (1,))
    assert_size_stride(primals_105, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_106, (4,), (1,))
    assert_size_stride(primals_107, (4,), (1,))
    assert_size_stride(primals_108, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_109, (4,), (1,))
    assert_size_stride(primals_110, (4,), (1,))
    assert_size_stride(primals_111, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_112, (4,), (1,))
    assert_size_stride(primals_113, (4,), (1,))
    assert_size_stride(primals_114, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_115, (4,), (1,))
    assert_size_stride(primals_116, (4,), (1,))
    assert_size_stride(primals_117, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_118, (4,), (1,))
    assert_size_stride(primals_119, (4,), (1,))
    assert_size_stride(primals_120, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_121, (4,), (1,))
    assert_size_stride(primals_122, (4,), (1,))
    assert_size_stride(primals_123, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_124, (4,), (1,))
    assert_size_stride(primals_125, (4,), (1,))
    assert_size_stride(primals_126, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_127, (4,), (1,))
    assert_size_stride(primals_128, (4,), (1,))
    assert_size_stride(primals_129, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_130, (4,), (1,))
    assert_size_stride(primals_131, (4,), (1,))
    assert_size_stride(primals_132, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_133, (4,), (1,))
    assert_size_stride(primals_134, (4,), (1,))
    assert_size_stride(primals_135, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_136, (4,), (1,))
    assert_size_stride(primals_137, (4,), (1,))
    assert_size_stride(primals_138, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_139, (4,), (1,))
    assert_size_stride(primals_140, (4,), (1,))
    assert_size_stride(primals_141, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_142, (4,), (1,))
    assert_size_stride(primals_143, (4,), (1,))
    assert_size_stride(primals_144, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_145, (4,), (1,))
    assert_size_stride(primals_146, (4,), (1,))
    assert_size_stride(primals_147, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_148, (16,), (1,))
    assert_size_stride(primals_149, (16,), (1,))
    assert_size_stride(primals_150, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_151, (4,), (1,))
    assert_size_stride(primals_152, (4, 8, 3, 3), (72, 9, 3, 1))
    assert_size_stride(primals_153, (4,), (1,))
    assert_size_stride(primals_154, (4,), (1,))
    assert_size_stride(primals_155, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_156, (4,), (1,))
    assert_size_stride(primals_157, (4,), (1,))
    assert_size_stride(primals_158, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_159, (4,), (1,))
    assert_size_stride(primals_160, (4,), (1,))
    assert_size_stride(primals_161, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_162, (4,), (1,))
    assert_size_stride(primals_163, (4,), (1,))
    assert_size_stride(primals_164, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_165, (4,), (1,))
    assert_size_stride(primals_166, (4,), (1,))
    assert_size_stride(primals_167, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_168, (4,), (1,))
    assert_size_stride(primals_169, (4,), (1,))
    assert_size_stride(primals_170, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_171, (4,), (1,))
    assert_size_stride(primals_172, (4,), (1,))
    assert_size_stride(primals_173, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_174, (4,), (1,))
    assert_size_stride(primals_175, (4,), (1,))
    assert_size_stride(primals_176, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_177, (4,), (1,))
    assert_size_stride(primals_178, (4,), (1,))
    assert_size_stride(primals_179, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_180, (4,), (1,))
    assert_size_stride(primals_181, (4,), (1,))
    assert_size_stride(primals_182, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_183, (4,), (1,))
    assert_size_stride(primals_184, (4,), (1,))
    assert_size_stride(primals_185, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_186, (4,), (1,))
    assert_size_stride(primals_187, (4,), (1,))
    assert_size_stride(primals_188, (4, 12, 3, 3), (108, 9, 3, 1))
    assert_size_stride(primals_189, (4,), (1,))
    assert_size_stride(primals_190, (4,), (1,))
    assert_size_stride(primals_191, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_192, (4,), (1,))
    assert_size_stride(primals_193, (4,), (1,))
    assert_size_stride(primals_194, (4, 4, 3, 3), (36, 9, 3, 1))
    assert_size_stride(primals_195, (4,), (1,))
    assert_size_stride(primals_196, (4,), (1,))
    assert_size_stride(primals_197, (16, 12, 1, 1), (12, 1, 1, 1))
    assert_size_stride(primals_198, (16,), (1,))
    assert_size_stride(primals_199, (16,), (1,))
    assert_size_stride(primals_200, (4, 16, 1, 1), (16, 1, 1, 1))
    assert_size_stride(primals_201, (4,), (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, 96, 4, 4), (1536, 16, 4, 1))
        buf1 = buf0
        del buf0
        buf2 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        get_raw_stream(0)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf1,
            primals_2, primals_4, buf2, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_2
        buf3 = extern_kernels.convolution(buf2, primals_5, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf3, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf4 = buf3
        del buf3
        buf5 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf4,
            primals_6, primals_7, buf5, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_6
        buf6 = extern_kernels.convolution(buf5, primals_8, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf6, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf7 = buf6
        del buf6
        triton_poi_fused_convolution_1[grid(6144)](buf7, primals_9, 6144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_9
        buf8 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_2[grid(18432)](buf2, buf5, buf7, primals_10,
            buf8, 18432, XBLOCK=256, num_warps=4, num_stages=1)
        buf9 = extern_kernels.convolution(buf8, primals_11, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf9, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf10 = buf9
        del buf9
        buf11 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf10,
            primals_12, primals_13, buf11, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_12
        buf12 = extern_kernels.convolution(buf11, primals_14, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf12, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf13 = buf12
        del buf12
        buf14 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf13,
            primals_15, primals_16, buf14, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_15
        buf15 = extern_kernels.convolution(buf14, primals_17, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf15, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf16 = buf15
        del buf15
        triton_poi_fused_convolution_1[grid(6144)](buf16, primals_18, 6144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_18
        buf17 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_2[grid(18432)](buf11, buf14, buf16, primals_19,
            buf17, 18432, XBLOCK=256, num_warps=4, num_stages=1)
        buf18 = extern_kernels.convolution(buf17, primals_20, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf19 = buf18
        del buf18
        buf20 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf19,
            primals_21, primals_22, buf20, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_21
        buf21 = extern_kernels.convolution(buf20, primals_23, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf21, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf22 = buf21
        del buf21
        buf23 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf22,
            primals_24, primals_25, buf23, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_24
        buf24 = extern_kernels.convolution(buf23, primals_26, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf24, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf25 = buf24
        del buf24
        triton_poi_fused_convolution_1[grid(6144)](buf25, primals_27, 6144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_27
        buf26 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_2[grid(18432)](buf20, buf23, buf25, primals_28,
            buf26, 18432, XBLOCK=256, num_warps=4, num_stages=1)
        buf27 = extern_kernels.convolution(buf26, primals_29, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf27, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf28 = buf27
        del buf27
        buf29 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf28,
            primals_30, primals_31, buf29, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_30
        buf30 = extern_kernels.convolution(buf29, primals_32, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf30, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf31 = buf30
        del buf30
        buf32 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf31,
            primals_33, primals_34, buf32, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_33
        buf33 = extern_kernels.convolution(buf32, primals_35, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf33, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf34 = buf33
        del buf33
        triton_poi_fused_convolution_1[grid(6144)](buf34, primals_36, 6144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_36
        buf35 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_2[grid(18432)](buf29, buf32, buf34, primals_37,
            buf35, 18432, XBLOCK=256, num_warps=4, num_stages=1)
        buf36 = extern_kernels.convolution(buf35, primals_38, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf36, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf37 = buf36
        del buf36
        buf38 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf37,
            primals_39, primals_40, buf38, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_39
        buf39 = extern_kernels.convolution(buf38, primals_41, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf39, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf40 = buf39
        del buf39
        buf41 = empty_strided_cuda((4, 96, 4, 4), (1536, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_0[grid(6144)](buf40,
            primals_42, primals_43, buf41, 6144, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_42
        buf42 = extern_kernels.convolution(buf41, primals_44, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf42, (4, 96, 4, 4), (1536, 16, 4, 1))
        buf43 = buf42
        del buf42
        triton_poi_fused_convolution_1[grid(6144)](buf43, primals_45, 6144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_45
        buf44 = empty_strided_cuda((4, 288, 4, 4), (4608, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_2[grid(18432)](buf38, buf41, buf43, primals_46,
            buf44, 18432, XBLOCK=256, num_warps=4, num_stages=1)
        buf45 = extern_kernels.convolution(buf44, primals_47, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf45, (4, 8, 4, 4), (128, 16, 4, 1))
        buf46 = buf45
        del buf45
        buf47 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_3[grid(512)](buf46,
            primals_48, primals_49, buf47, 512, XBLOCK=256, num_warps=4,
            num_stages=1)
        del primals_48
        buf48 = extern_kernels.convolution(buf47, primals_50, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf48, (4, 4, 4, 4), (64, 16, 4, 1))
        buf49 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32
            )
        triton_poi_fused_cat_4[grid(512)](primals_3, buf48, primals_51,
            buf49, 512, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_51
        buf50 = extern_kernels.convolution(buf49, primals_52, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf50, (4, 4, 4, 4), (64, 16, 4, 1))
        buf51 = buf50
        del buf50
        buf52 = buf48
        del buf48
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf51,
            primals_53, primals_54, buf52, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_53
        buf53 = extern_kernels.convolution(buf52, primals_55, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf53, (4, 4, 4, 4), (64, 16, 4, 1))
        buf54 = buf53
        del buf53
        buf55 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf54,
            primals_56, primals_57, buf55, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_56
        buf56 = extern_kernels.convolution(buf55, primals_58, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf56, (4, 4, 4, 4), (64, 16, 4, 1))
        buf57 = buf56
        del buf56
        triton_poi_fused_convolution_6[grid(256)](buf57, primals_59, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_59
        buf58 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf52, buf55, buf57, primals_60,
            buf58, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf59 = extern_kernels.convolution(buf58, primals_61, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf59, (4, 4, 4, 4), (64, 16, 4, 1))
        buf60 = buf59
        del buf59
        buf61 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf60,
            primals_62, primals_63, buf61, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_62
        buf62 = extern_kernels.convolution(buf61, primals_64, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf62, (4, 4, 4, 4), (64, 16, 4, 1))
        buf63 = buf62
        del buf62
        buf64 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf63,
            primals_65, primals_66, buf64, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_65
        buf65 = extern_kernels.convolution(buf64, primals_67, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf65, (4, 4, 4, 4), (64, 16, 4, 1))
        buf66 = buf65
        del buf65
        triton_poi_fused_convolution_6[grid(256)](buf66, primals_68, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_68
        buf67 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf61, buf64, buf66, primals_69,
            buf67, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf68 = extern_kernels.convolution(buf67, primals_70, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf68, (4, 4, 4, 4), (64, 16, 4, 1))
        buf69 = buf68
        del buf68
        buf70 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf69,
            primals_71, primals_72, buf70, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_71
        buf71 = extern_kernels.convolution(buf70, primals_73, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf71, (4, 4, 4, 4), (64, 16, 4, 1))
        buf72 = buf71
        del buf71
        buf73 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf72,
            primals_74, primals_75, buf73, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_74
        buf74 = extern_kernels.convolution(buf73, primals_76, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf74, (4, 4, 4, 4), (64, 16, 4, 1))
        buf75 = buf74
        del buf74
        triton_poi_fused_convolution_6[grid(256)](buf75, primals_77, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_77
        buf76 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf70, buf73, buf75, primals_78,
            buf76, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf77 = extern_kernels.convolution(buf76, primals_79, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf77, (4, 4, 4, 4), (64, 16, 4, 1))
        buf78 = buf77
        del buf77
        buf79 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf78,
            primals_80, primals_81, buf79, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_80
        buf80 = extern_kernels.convolution(buf79, primals_82, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf80, (4, 4, 4, 4), (64, 16, 4, 1))
        buf81 = buf80
        del buf80
        buf82 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf81,
            primals_83, primals_84, buf82, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_83
        buf83 = extern_kernels.convolution(buf82, primals_85, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf83, (4, 4, 4, 4), (64, 16, 4, 1))
        buf84 = buf83
        del buf83
        triton_poi_fused_convolution_6[grid(256)](buf84, primals_86, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_86
        buf85 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf79, buf82, buf84, primals_87,
            buf85, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf86 = extern_kernels.convolution(buf85, primals_88, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf86, (4, 4, 4, 4), (64, 16, 4, 1))
        buf87 = buf86
        del buf86
        buf88 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf87,
            primals_89, primals_90, buf88, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_89
        buf89 = extern_kernels.convolution(buf88, primals_91, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf89, (4, 4, 4, 4), (64, 16, 4, 1))
        buf90 = buf89
        del buf89
        buf91 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf90,
            primals_92, primals_93, buf91, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_92
        buf92 = extern_kernels.convolution(buf91, primals_94, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf92, (4, 4, 4, 4), (64, 16, 4, 1))
        buf93 = buf92
        del buf92
        triton_poi_fused_convolution_6[grid(256)](buf93, primals_95, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_95
        buf94 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf88, buf91, buf93, primals_96,
            buf94, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf95 = extern_kernels.convolution(buf94, primals_97, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf95, (4, 16, 4, 4), (256, 16, 4, 1))
        buf96 = buf95
        del buf95
        buf97 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_8[grid(1024)](buf96,
            primals_98, primals_99, buf97, 1024, XBLOCK=256, num_warps=4,
            num_stages=1)
        del primals_98
        buf98 = extern_kernels.convolution(buf97, primals_100, stride=(1, 1
            ), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf98, (4, 4, 4, 4), (64, 16, 4, 1))
        buf99 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.float32
            )
        triton_poi_fused_cat_4[grid(512)](primals_3, buf98, primals_101,
            buf99, 512, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_101
        buf100 = extern_kernels.convolution(buf99, primals_102, stride=(1, 
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf100, (4, 4, 4, 4), (64, 16, 4, 1))
        buf101 = buf100
        del buf100
        buf102 = buf98
        del buf98
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf101,
            primals_103, primals_104, buf102, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_103
        buf103 = extern_kernels.convolution(buf102, primals_105, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf103, (4, 4, 4, 4), (64, 16, 4, 1))
        buf104 = buf103
        del buf103
        buf105 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf104,
            primals_106, primals_107, buf105, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_106
        buf106 = extern_kernels.convolution(buf105, primals_108, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf106, (4, 4, 4, 4), (64, 16, 4, 1))
        buf107 = buf106
        del buf106
        triton_poi_fused_convolution_6[grid(256)](buf107, primals_109, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_109
        buf108 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf102, buf105, buf107,
            primals_110, buf108, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf109 = extern_kernels.convolution(buf108, primals_111, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf109, (4, 4, 4, 4), (64, 16, 4, 1))
        buf110 = buf109
        del buf109
        buf111 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf110,
            primals_112, primals_113, buf111, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_112
        buf112 = extern_kernels.convolution(buf111, primals_114, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf112, (4, 4, 4, 4), (64, 16, 4, 1))
        buf113 = buf112
        del buf112
        buf114 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf113,
            primals_115, primals_116, buf114, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_115
        buf115 = extern_kernels.convolution(buf114, primals_117, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf115, (4, 4, 4, 4), (64, 16, 4, 1))
        buf116 = buf115
        del buf115
        triton_poi_fused_convolution_6[grid(256)](buf116, primals_118, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_118
        buf117 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf111, buf114, buf116,
            primals_119, buf117, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf118 = extern_kernels.convolution(buf117, primals_120, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf118, (4, 4, 4, 4), (64, 16, 4, 1))
        buf119 = buf118
        del buf118
        buf120 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf119,
            primals_121, primals_122, buf120, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_121
        buf121 = extern_kernels.convolution(buf120, primals_123, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf121, (4, 4, 4, 4), (64, 16, 4, 1))
        buf122 = buf121
        del buf121
        buf123 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf122,
            primals_124, primals_125, buf123, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_124
        buf124 = extern_kernels.convolution(buf123, primals_126, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf124, (4, 4, 4, 4), (64, 16, 4, 1))
        buf125 = buf124
        del buf124
        triton_poi_fused_convolution_6[grid(256)](buf125, primals_127, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_127
        buf126 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf120, buf123, buf125,
            primals_128, buf126, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf127 = extern_kernels.convolution(buf126, primals_129, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf127, (4, 4, 4, 4), (64, 16, 4, 1))
        buf128 = buf127
        del buf127
        buf129 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf128,
            primals_130, primals_131, buf129, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_130
        buf130 = extern_kernels.convolution(buf129, primals_132, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf130, (4, 4, 4, 4), (64, 16, 4, 1))
        buf131 = buf130
        del buf130
        buf132 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf131,
            primals_133, primals_134, buf132, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_133
        buf133 = extern_kernels.convolution(buf132, primals_135, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf133, (4, 4, 4, 4), (64, 16, 4, 1))
        buf134 = buf133
        del buf133
        triton_poi_fused_convolution_6[grid(256)](buf134, primals_136, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_136
        buf135 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf129, buf132, buf134,
            primals_137, buf135, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf136 = extern_kernels.convolution(buf135, primals_138, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf136, (4, 4, 4, 4), (64, 16, 4, 1))
        buf137 = buf136
        del buf136
        buf138 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf137,
            primals_139, primals_140, buf138, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_139
        buf139 = extern_kernels.convolution(buf138, primals_141, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf139, (4, 4, 4, 4), (64, 16, 4, 1))
        buf140 = buf139
        del buf139
        buf141 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf140,
            primals_142, primals_143, buf141, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_142
        buf142 = extern_kernels.convolution(buf141, primals_144, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf142, (4, 4, 4, 4), (64, 16, 4, 1))
        buf143 = buf142
        del buf142
        triton_poi_fused_convolution_6[grid(256)](buf143, primals_145, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_145
        buf144 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf138, buf141, buf143,
            primals_146, buf144, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf145 = extern_kernels.convolution(buf144, primals_147, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf145, (4, 16, 4, 4), (256, 16, 4, 1))
        buf146 = buf145
        del buf145
        buf147 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_8[grid(1024)](buf146,
            primals_148, primals_149, buf147, 1024, XBLOCK=256, num_warps=4,
            num_stages=1)
        del primals_148
        buf148 = extern_kernels.convolution(buf147, primals_150, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf148, (4, 4, 4, 4), (64, 16, 4, 1))
        buf149 = empty_strided_cuda((4, 8, 4, 4), (128, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_4[grid(512)](primals_3, buf148, primals_151,
            buf149, 512, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_151
        buf150 = extern_kernels.convolution(buf149, primals_152, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf150, (4, 4, 4, 4), (64, 16, 4, 1))
        buf151 = buf150
        del buf150
        buf152 = buf148
        del buf148
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf151,
            primals_153, primals_154, buf152, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_153
        buf153 = extern_kernels.convolution(buf152, primals_155, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf153, (4, 4, 4, 4), (64, 16, 4, 1))
        buf154 = buf153
        del buf153
        buf155 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf154,
            primals_156, primals_157, buf155, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_156
        buf156 = extern_kernels.convolution(buf155, primals_158, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf156, (4, 4, 4, 4), (64, 16, 4, 1))
        buf157 = buf156
        del buf156
        triton_poi_fused_convolution_6[grid(256)](buf157, primals_159, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_159
        buf158 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf152, buf155, buf157,
            primals_160, buf158, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf159 = extern_kernels.convolution(buf158, primals_161, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf159, (4, 4, 4, 4), (64, 16, 4, 1))
        buf160 = buf159
        del buf159
        buf161 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf160,
            primals_162, primals_163, buf161, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_162
        buf162 = extern_kernels.convolution(buf161, primals_164, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf162, (4, 4, 4, 4), (64, 16, 4, 1))
        buf163 = buf162
        del buf162
        buf164 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf163,
            primals_165, primals_166, buf164, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_165
        buf165 = extern_kernels.convolution(buf164, primals_167, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf165, (4, 4, 4, 4), (64, 16, 4, 1))
        buf166 = buf165
        del buf165
        triton_poi_fused_convolution_6[grid(256)](buf166, primals_168, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_168
        buf167 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf161, buf164, buf166,
            primals_169, buf167, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf168 = extern_kernels.convolution(buf167, primals_170, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf168, (4, 4, 4, 4), (64, 16, 4, 1))
        buf169 = buf168
        del buf168
        buf170 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf169,
            primals_171, primals_172, buf170, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_171
        buf171 = extern_kernels.convolution(buf170, primals_173, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf171, (4, 4, 4, 4), (64, 16, 4, 1))
        buf172 = buf171
        del buf171
        buf173 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf172,
            primals_174, primals_175, buf173, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_174
        buf174 = extern_kernels.convolution(buf173, primals_176, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf174, (4, 4, 4, 4), (64, 16, 4, 1))
        buf175 = buf174
        del buf174
        triton_poi_fused_convolution_6[grid(256)](buf175, primals_177, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_177
        buf176 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf170, buf173, buf175,
            primals_178, buf176, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf177 = extern_kernels.convolution(buf176, primals_179, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf177, (4, 4, 4, 4), (64, 16, 4, 1))
        buf178 = buf177
        del buf177
        buf179 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf178,
            primals_180, primals_181, buf179, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_180
        buf180 = extern_kernels.convolution(buf179, primals_182, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf180, (4, 4, 4, 4), (64, 16, 4, 1))
        buf181 = buf180
        del buf180
        buf182 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf181,
            primals_183, primals_184, buf182, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_183
        buf183 = extern_kernels.convolution(buf182, primals_185, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf183, (4, 4, 4, 4), (64, 16, 4, 1))
        buf184 = buf183
        del buf183
        triton_poi_fused_convolution_6[grid(256)](buf184, primals_186, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_186
        buf185 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf179, buf182, buf184,
            primals_187, buf185, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf186 = extern_kernels.convolution(buf185, primals_188, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf186, (4, 4, 4, 4), (64, 16, 4, 1))
        buf187 = buf186
        del buf186
        buf188 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf187,
            primals_189, primals_190, buf188, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_189
        buf189 = extern_kernels.convolution(buf188, primals_191, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf189, (4, 4, 4, 4), (64, 16, 4, 1))
        buf190 = buf189
        del buf189
        buf191 = empty_strided_cuda((4, 4, 4, 4), (64, 16, 4, 1), torch.float32
            )
        triton_poi_fused__prelu_kernel_convolution_5[grid(256)](buf190,
            primals_192, primals_193, buf191, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_192
        buf192 = extern_kernels.convolution(buf191, primals_194, stride=(1,
            1), padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf192, (4, 4, 4, 4), (64, 16, 4, 1))
        buf193 = buf192
        del buf192
        triton_poi_fused_convolution_6[grid(256)](buf193, primals_195, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_195
        buf194 = empty_strided_cuda((4, 12, 4, 4), (192, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_7[grid(768)](buf188, buf191, buf193,
            primals_196, buf194, 768, XBLOCK=128, num_warps=4, num_stages=1)
        buf195 = extern_kernels.convolution(buf194, primals_197, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf195, (4, 16, 4, 4), (256, 16, 4, 1))
        buf196 = buf195
        del buf195
        buf197 = empty_strided_cuda((4, 16, 4, 4), (256, 16, 4, 1), torch.
            float32)
        triton_poi_fused__prelu_kernel_convolution_8[grid(1024)](buf196,
            primals_198, primals_199, buf197, 1024, XBLOCK=256, num_warps=4,
            num_stages=1)
        del primals_198
        buf198 = extern_kernels.convolution(buf197, primals_200, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf198, (4, 4, 4, 4), (64, 16, 4, 1))
        buf199 = buf198
        del buf198
        triton_poi_fused_convolution_6[grid(256)](buf199, primals_201, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_201
    return (buf199, primals_1, primals_3, primals_4, primals_5, primals_7,
        primals_8, primals_10, primals_11, primals_13, primals_14,
        primals_16, primals_17, primals_19, primals_20, primals_22,
        primals_23, primals_25, primals_26, primals_28, primals_29,
        primals_31, primals_32, primals_34, primals_35, primals_37,
        primals_38, primals_40, primals_41, primals_43, primals_44,
        primals_46, primals_47, primals_49, primals_50, primals_52,
        primals_54, primals_55, primals_57, primals_58, primals_60,
        primals_61, primals_63, primals_64, primals_66, primals_67,
        primals_69, primals_70, primals_72, primals_73, primals_75,
        primals_76, primals_78, primals_79, primals_81, primals_82,
        primals_84, primals_85, primals_87, primals_88, primals_90,
        primals_91, primals_93, primals_94, primals_96, primals_97,
        primals_99, primals_100, primals_102, primals_104, primals_105,
        primals_107, primals_108, primals_110, primals_111, primals_113,
        primals_114, primals_116, primals_117, primals_119, primals_120,
        primals_122, primals_123, primals_125, primals_126, primals_128,
        primals_129, primals_131, primals_132, primals_134, primals_135,
        primals_137, primals_138, primals_140, primals_141, primals_143,
        primals_144, primals_146, primals_147, primals_149, primals_150,
        primals_152, primals_154, primals_155, primals_157, primals_158,
        primals_160, primals_161, primals_163, primals_164, primals_166,
        primals_167, primals_169, primals_170, primals_172, primals_173,
        primals_175, primals_176, primals_178, primals_179, primals_181,
        primals_182, primals_184, primals_185, primals_187, primals_188,
        primals_190, primals_191, primals_193, primals_194, primals_196,
        primals_197, primals_199, primals_200, buf1, buf2, buf4, buf5, buf7,
        buf8, buf10, buf11, buf13, buf14, buf16, buf17, buf19, buf20, buf22,
        buf23, buf25, buf26, buf28, buf29, buf31, buf32, buf34, buf35,
        buf37, buf38, buf40, buf41, buf43, buf44, buf46, buf47, buf49,
        buf51, buf52, buf54, buf55, buf57, buf58, buf60, buf61, buf63,
        buf64, buf66, buf67, buf69, buf70, buf72, buf73, buf75, buf76,
        buf78, buf79, buf81, buf82, buf84, buf85, buf87, buf88, buf90,
        buf91, buf93, buf94, buf96, buf97, buf99, buf101, buf102, buf104,
        buf105, buf107, buf108, buf110, buf111, buf113, buf114, buf116,
        buf117, buf119, buf120, buf122, buf123, buf125, buf126, buf128,
        buf129, buf131, buf132, buf134, buf135, buf137, buf138, buf140,
        buf141, buf143, buf144, buf146, buf147, buf149, buf151, buf152,
        buf154, buf155, buf157, buf158, buf160, buf161, buf163, buf164,
        buf166, buf167, buf169, buf170, buf172, buf173, buf175, buf176,
        buf178, buf179, buf181, buf182, buf184, buf185, buf187, buf188,
        buf190, buf191, buf193, buf194, buf196, buf197)


class concatLayer(nn.Module):

    def __init__(self, in_channels, out_channels_perSub, i, j, appendix):
        super(concatLayer, self).__init__()
        self.firstSub = self.concatLayerSub(in_channels,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_0')
        self.secondSub = self.concatLayerSub(out_channels_perSub,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_1')
        self.thirdSub = self.concatLayerSub(out_channels_perSub,
            out_channels_perSub, '%d_stage%d_' % (i, j) + appendix + '_2')

    def forward(self, x):
        firstSub = self.firstSub(x)
        secondSub = self.secondSub(firstSub)
        thirdSub = self.thirdSub(secondSub)
        out = torch.cat([firstSub, secondSub, thirdSub], 1)
        return out

    def concatLayerSub(self, in_channels, out_channels, layerName):
        concatLayerSubOrdered = OrderedDict()
        conv2d = nn.Conv2d(in_channels, out_channels, kernel_size=3, padding=1)
        concatLayerSubOrdered.update({('Mconv' + layerName): conv2d})
        concatLayerSubOrdered.update({('Mprelu' + layerName): nn.PReLU(
            out_channels)})
        return nn.Sequential(concatLayerSubOrdered)


class stage(nn.Module):

    def __init__(self, stageID, in_channels, out_channels_perSub,
        mid_channels, out_channels, appendix):
        super(stage, self).__init__()
        self.firstConcat = concatLayer(in_channels, out_channels_perSub, 1,
            stageID, appendix)
        self.secondConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 2, stageID, appendix)
        self.thirdConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 3, stageID, appendix)
        self.fourthConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 4, stageID, appendix)
        self.fifthConcat = concatLayer(3 * out_channels_perSub,
            out_channels_perSub, 5, stageID, appendix)
        conv2d = nn.Conv2d(3 * out_channels_perSub, mid_channels,
            kernel_size=1, padding=0)
        prelu = nn.PReLU(mid_channels)
        self.afterConcatsFirst = nn.Sequential(OrderedDict({(
            'Mconv6_stage%d_%s' % (stageID, appendix)): conv2d, (
            'Mprelu6_stage%d_%s' % (stageID, appendix)): prelu}))
        conv2d = nn.Conv2d(mid_channels, out_channels, kernel_size=1, padding=0
            )
        self.afterConcatsSecond = nn.Sequential(OrderedDict({(
            'Mconv7_stage%d_%s' % (stageID, appendix)): conv2d}))

    def forward(self, x):
        x = self.firstConcat(x)
        x = self.secondConcat(x)
        x = self.thirdConcat(x)
        x = self.fourthConcat(x)
        x = self.fifthConcat(x)
        x = self.afterConcatsFirst(x)
        out = self.afterConcatsSecond(x)
        return out


class L2PartNew(nn.Module):

    def __init__(self, in_channels, stage_out_channels):
        super(L2PartNew, self).__init__()
        self.firstStage = stage(0, in_channels, 96, in_channels * 2,
            stage_out_channels, 'L2')
        self.secondStage = stage(1, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')
        self.thirdStage = stage(2, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')
        self.fourthStage = stage(3, in_channels + stage_out_channels,
            in_channels, in_channels * 4, stage_out_channels, 'L2')

    def forward(self, input_0):
        primals_1 = (self.firstStage.firstConcat.firstSub.
            Mconv1_stage0_L2_0.weight)
        primals_2 = (self.firstStage.firstConcat.firstSub.
            Mconv1_stage0_L2_0.bias)
        primals_4 = (self.firstStage.firstConcat.firstSub.
            Mprelu1_stage0_L2_0.weight)
        primals_5 = (self.firstStage.firstConcat.secondSub.
            Mconv1_stage0_L2_1.weight)
        primals_6 = (self.firstStage.firstConcat.secondSub.
            Mconv1_stage0_L2_1.bias)
        primals_7 = (self.firstStage.firstConcat.secondSub.
            Mprelu1_stage0_L2_1.weight)
        primals_8 = (self.firstStage.firstConcat.thirdSub.
            Mconv1_stage0_L2_2.weight)
        primals_9 = (self.firstStage.firstConcat.thirdSub.
            Mconv1_stage0_L2_2.bias)
        primals_10 = (self.firstStage.firstConcat.thirdSub.
            Mprelu1_stage0_L2_2.weight)
        primals_11 = (self.firstStage.secondConcat.firstSub.
            Mconv2_stage0_L2_0.weight)
        primals_12 = (self.firstStage.secondConcat.firstSub.
            Mconv2_stage0_L2_0.bias)
        primals_13 = (self.firstStage.secondConcat.firstSub.
            Mprelu2_stage0_L2_0.weight)
        primals_14 = (self.firstStage.secondConcat.secondSub.
            Mconv2_stage0_L2_1.weight)
        primals_15 = (self.firstStage.secondConcat.secondSub.
            Mconv2_stage0_L2_1.bias)
        primals_16 = (self.firstStage.secondConcat.secondSub.
            Mprelu2_stage0_L2_1.weight)
        primals_17 = (self.firstStage.secondConcat.thirdSub.
            Mconv2_stage0_L2_2.weight)
        primals_18 = (self.firstStage.secondConcat.thirdSub.
            Mconv2_stage0_L2_2.bias)
        primals_19 = (self.firstStage.secondConcat.thirdSub.
            Mprelu2_stage0_L2_2.weight)
        primals_20 = (self.firstStage.thirdConcat.firstSub.
            Mconv3_stage0_L2_0.weight)
        primals_21 = (self.firstStage.thirdConcat.firstSub.
            Mconv3_stage0_L2_0.bias)
        primals_22 = (self.firstStage.thirdConcat.firstSub.
            Mprelu3_stage0_L2_0.weight)
        primals_23 = (self.firstStage.thirdConcat.secondSub.
            Mconv3_stage0_L2_1.weight)
        primals_24 = (self.firstStage.thirdConcat.secondSub.
            Mconv3_stage0_L2_1.bias)
        primals_25 = (self.firstStage.thirdConcat.secondSub.
            Mprelu3_stage0_L2_1.weight)
        primals_26 = (self.firstStage.thirdConcat.thirdSub.
            Mconv3_stage0_L2_2.weight)
        primals_27 = (self.firstStage.thirdConcat.thirdSub.
            Mconv3_stage0_L2_2.bias)
        primals_28 = (self.firstStage.thirdConcat.thirdSub.
            Mprelu3_stage0_L2_2.weight)
        primals_29 = (self.firstStage.fourthConcat.firstSub.
            Mconv4_stage0_L2_0.weight)
        primals_30 = (self.firstStage.fourthConcat.firstSub.
            Mconv4_stage0_L2_0.bias)
        primals_31 = (self.firstStage.fourthConcat.firstSub.
            Mprelu4_stage0_L2_0.weight)
        primals_32 = (self.firstStage.fourthConcat.secondSub.
            Mconv4_stage0_L2_1.weight)
        primals_33 = (self.firstStage.fourthConcat.secondSub.
            Mconv4_stage0_L2_1.bias)
        primals_34 = (self.firstStage.fourthConcat.secondSub.
            Mprelu4_stage0_L2_1.weight)
        primals_35 = (self.firstStage.fourthConcat.thirdSub.
            Mconv4_stage0_L2_2.weight)
        primals_36 = (self.firstStage.fourthConcat.thirdSub.
            Mconv4_stage0_L2_2.bias)
        primals_37 = (self.firstStage.fourthConcat.thirdSub.
            Mprelu4_stage0_L2_2.weight)
        primals_38 = (self.firstStage.fifthConcat.firstSub.
            Mconv5_stage0_L2_0.weight)
        primals_39 = (self.firstStage.fifthConcat.firstSub.
            Mconv5_stage0_L2_0.bias)
        primals_40 = (self.firstStage.fifthConcat.firstSub.
            Mprelu5_stage0_L2_0.weight)
        primals_41 = (self.firstStage.fifthConcat.secondSub.
            Mconv5_stage0_L2_1.weight)
        primals_42 = (self.firstStage.fifthConcat.secondSub.
            Mconv5_stage0_L2_1.bias)
        primals_43 = (self.firstStage.fifthConcat.secondSub.
            Mprelu5_stage0_L2_1.weight)
        primals_44 = (self.firstStage.fifthConcat.thirdSub.
            Mconv5_stage0_L2_2.weight)
        primals_45 = (self.firstStage.fifthConcat.thirdSub.
            Mconv5_stage0_L2_2.bias)
        primals_46 = (self.firstStage.fifthConcat.thirdSub.
            Mprelu5_stage0_L2_2.weight)
        primals_47 = self.firstStage.afterConcatsFirst.Mconv6_stage0_L2.weight
        primals_48 = self.firstStage.afterConcatsFirst.Mconv6_stage0_L2.bias
        primals_49 = self.firstStage.afterConcatsFirst.Mprelu6_stage0_L2.weight
        primals_50 = self.firstStage.afterConcatsSecond.Mconv7_stage0_L2.weight
        primals_51 = self.firstStage.afterConcatsSecond.Mconv7_stage0_L2.bias
        primals_52 = (self.secondStage.firstConcat.firstSub.
            Mconv1_stage1_L2_0.weight)
        primals_53 = (self.secondStage.firstConcat.firstSub.
            Mconv1_stage1_L2_0.bias)
        primals_54 = (self.secondStage.firstConcat.firstSub.
            Mprelu1_stage1_L2_0.weight)
        primals_55 = (self.secondStage.firstConcat.secondSub.
            Mconv1_stage1_L2_1.weight)
        primals_56 = (self.secondStage.firstConcat.secondSub.
            Mconv1_stage1_L2_1.bias)
        primals_57 = (self.secondStage.firstConcat.secondSub.
            Mprelu1_stage1_L2_1.weight)
        primals_58 = (self.secondStage.firstConcat.thirdSub.
            Mconv1_stage1_L2_2.weight)
        primals_59 = (self.secondStage.firstConcat.thirdSub.
            Mconv1_stage1_L2_2.bias)
        primals_60 = (self.secondStage.firstConcat.thirdSub.
            Mprelu1_stage1_L2_2.weight)
        primals_61 = (self.secondStage.secondConcat.firstSub.
            Mconv2_stage1_L2_0.weight)
        primals_62 = (self.secondStage.secondConcat.firstSub.
            Mconv2_stage1_L2_0.bias)
        primals_63 = (self.secondStage.secondConcat.firstSub.
            Mprelu2_stage1_L2_0.weight)
        primals_64 = (self.secondStage.secondConcat.secondSub.
            Mconv2_stage1_L2_1.weight)
        primals_65 = (self.secondStage.secondConcat.secondSub.
            Mconv2_stage1_L2_1.bias)
        primals_66 = (self.secondStage.secondConcat.secondSub.
            Mprelu2_stage1_L2_1.weight)
        primals_67 = (self.secondStage.secondConcat.thirdSub.
            Mconv2_stage1_L2_2.weight)
        primals_68 = (self.secondStage.secondConcat.thirdSub.
            Mconv2_stage1_L2_2.bias)
        primals_69 = (self.secondStage.secondConcat.thirdSub.
            Mprelu2_stage1_L2_2.weight)
        primals_70 = (self.secondStage.thirdConcat.firstSub.
            Mconv3_stage1_L2_0.weight)
        primals_71 = (self.secondStage.thirdConcat.firstSub.
            Mconv3_stage1_L2_0.bias)
        primals_72 = (self.secondStage.thirdConcat.firstSub.
            Mprelu3_stage1_L2_0.weight)
        primals_73 = (self.secondStage.thirdConcat.secondSub.
            Mconv3_stage1_L2_1.weight)
        primals_74 = (self.secondStage.thirdConcat.secondSub.
            Mconv3_stage1_L2_1.bias)
        primals_75 = (self.secondStage.thirdConcat.secondSub.
            Mprelu3_stage1_L2_1.weight)
        primals_76 = (self.secondStage.thirdConcat.thirdSub.
            Mconv3_stage1_L2_2.weight)
        primals_77 = (self.secondStage.thirdConcat.thirdSub.
            Mconv3_stage1_L2_2.bias)
        primals_78 = (self.secondStage.thirdConcat.thirdSub.
            Mprelu3_stage1_L2_2.weight)
        primals_79 = (self.secondStage.fourthConcat.firstSub.
            Mconv4_stage1_L2_0.weight)
        primals_80 = (self.secondStage.fourthConcat.firstSub.
            Mconv4_stage1_L2_0.bias)
        primals_81 = (self.secondStage.fourthConcat.firstSub.
            Mprelu4_stage1_L2_0.weight)
        primals_82 = (self.secondStage.fourthConcat.secondSub.
            Mconv4_stage1_L2_1.weight)
        primals_83 = (self.secondStage.fourthConcat.secondSub.
            Mconv4_stage1_L2_1.bias)
        primals_84 = (self.secondStage.fourthConcat.secondSub.
            Mprelu4_stage1_L2_1.weight)
        primals_85 = (self.secondStage.fourthConcat.thirdSub.
            Mconv4_stage1_L2_2.weight)
        primals_86 = (self.secondStage.fourthConcat.thirdSub.
            Mconv4_stage1_L2_2.bias)
        primals_87 = (self.secondStage.fourthConcat.thirdSub.
            Mprelu4_stage1_L2_2.weight)
        primals_88 = (self.secondStage.fifthConcat.firstSub.
            Mconv5_stage1_L2_0.weight)
        primals_89 = (self.secondStage.fifthConcat.firstSub.
            Mconv5_stage1_L2_0.bias)
        primals_90 = (self.secondStage.fifthConcat.firstSub.
            Mprelu5_stage1_L2_0.weight)
        primals_91 = (self.secondStage.fifthConcat.secondSub.
            Mconv5_stage1_L2_1.weight)
        primals_92 = (self.secondStage.fifthConcat.secondSub.
            Mconv5_stage1_L2_1.bias)
        primals_93 = (self.secondStage.fifthConcat.secondSub.
            Mprelu5_stage1_L2_1.weight)
        primals_94 = (self.secondStage.fifthConcat.thirdSub.
            Mconv5_stage1_L2_2.weight)
        primals_95 = (self.secondStage.fifthConcat.thirdSub.
            Mconv5_stage1_L2_2.bias)
        primals_96 = (self.secondStage.fifthConcat.thirdSub.
            Mprelu5_stage1_L2_2.weight)
        primals_97 = self.secondStage.afterConcatsFirst.Mconv6_stage1_L2.weight
        primals_98 = self.secondStage.afterConcatsFirst.Mconv6_stage1_L2.bias
        primals_99 = (self.secondStage.afterConcatsFirst.Mprelu6_stage1_L2.
            weight)
        primals_100 = (self.secondStage.afterConcatsSecond.Mconv7_stage1_L2
            .weight)
        primals_101 = self.secondStage.afterConcatsSecond.Mconv7_stage1_L2.bias
        primals_102 = (self.thirdStage.firstConcat.firstSub.
            Mconv1_stage2_L2_0.weight)
        primals_103 = (self.thirdStage.firstConcat.firstSub.
            Mconv1_stage2_L2_0.bias)
        primals_104 = (self.thirdStage.firstConcat.firstSub.
            Mprelu1_stage2_L2_0.weight)
        primals_105 = (self.thirdStage.firstConcat.secondSub.
            Mconv1_stage2_L2_1.weight)
        primals_106 = (self.thirdStage.firstConcat.secondSub.
            Mconv1_stage2_L2_1.bias)
        primals_107 = (self.thirdStage.firstConcat.secondSub.
            Mprelu1_stage2_L2_1.weight)
        primals_108 = (self.thirdStage.firstConcat.thirdSub.
            Mconv1_stage2_L2_2.weight)
        primals_109 = (self.thirdStage.firstConcat.thirdSub.
            Mconv1_stage2_L2_2.bias)
        primals_110 = (self.thirdStage.firstConcat.thirdSub.
            Mprelu1_stage2_L2_2.weight)
        primals_111 = (self.thirdStage.secondConcat.firstSub.
            Mconv2_stage2_L2_0.weight)
        primals_112 = (self.thirdStage.secondConcat.firstSub.
            Mconv2_stage2_L2_0.bias)
        primals_113 = (self.thirdStage.secondConcat.firstSub.
            Mprelu2_stage2_L2_0.weight)
        primals_114 = (self.thirdStage.secondConcat.secondSub.
            Mconv2_stage2_L2_1.weight)
        primals_115 = (self.thirdStage.secondConcat.secondSub.
            Mconv2_stage2_L2_1.bias)
        primals_116 = (self.thirdStage.secondConcat.secondSub.
            Mprelu2_stage2_L2_1.weight)
        primals_117 = (self.thirdStage.secondConcat.thirdSub.
            Mconv2_stage2_L2_2.weight)
        primals_118 = (self.thirdStage.secondConcat.thirdSub.
            Mconv2_stage2_L2_2.bias)
        primals_119 = (self.thirdStage.secondConcat.thirdSub.
            Mprelu2_stage2_L2_2.weight)
        primals_120 = (self.thirdStage.thirdConcat.firstSub.
            Mconv3_stage2_L2_0.weight)
        primals_121 = (self.thirdStage.thirdConcat.firstSub.
            Mconv3_stage2_L2_0.bias)
        primals_122 = (self.thirdStage.thirdConcat.firstSub.
            Mprelu3_stage2_L2_0.weight)
        primals_123 = (self.thirdStage.thirdConcat.secondSub.
            Mconv3_stage2_L2_1.weight)
        primals_124 = (self.thirdStage.thirdConcat.secondSub.
            Mconv3_stage2_L2_1.bias)
        primals_125 = (self.thirdStage.thirdConcat.secondSub.
            Mprelu3_stage2_L2_1.weight)
        primals_126 = (self.thirdStage.thirdConcat.thirdSub.
            Mconv3_stage2_L2_2.weight)
        primals_127 = (self.thirdStage.thirdConcat.thirdSub.
            Mconv3_stage2_L2_2.bias)
        primals_128 = (self.thirdStage.thirdConcat.thirdSub.
            Mprelu3_stage2_L2_2.weight)
        primals_129 = (self.thirdStage.fourthConcat.firstSub.
            Mconv4_stage2_L2_0.weight)
        primals_130 = (self.thirdStage.fourthConcat.firstSub.
            Mconv4_stage2_L2_0.bias)
        primals_131 = (self.thirdStage.fourthConcat.firstSub.
            Mprelu4_stage2_L2_0.weight)
        primals_132 = (self.thirdStage.fourthConcat.secondSub.
            Mconv4_stage2_L2_1.weight)
        primals_133 = (self.thirdStage.fourthConcat.secondSub.
            Mconv4_stage2_L2_1.bias)
        primals_134 = (self.thirdStage.fourthConcat.secondSub.
            Mprelu4_stage2_L2_1.weight)
        primals_135 = (self.thirdStage.fourthConcat.thirdSub.
            Mconv4_stage2_L2_2.weight)
        primals_136 = (self.thirdStage.fourthConcat.thirdSub.
            Mconv4_stage2_L2_2.bias)
        primals_137 = (self.thirdStage.fourthConcat.thirdSub.
            Mprelu4_stage2_L2_2.weight)
        primals_138 = (self.thirdStage.fifthConcat.firstSub.
            Mconv5_stage2_L2_0.weight)
        primals_139 = (self.thirdStage.fifthConcat.firstSub.
            Mconv5_stage2_L2_0.bias)
        primals_140 = (self.thirdStage.fifthConcat.firstSub.
            Mprelu5_stage2_L2_0.weight)
        primals_141 = (self.thirdStage.fifthConcat.secondSub.
            Mconv5_stage2_L2_1.weight)
        primals_142 = (self.thirdStage.fifthConcat.secondSub.
            Mconv5_stage2_L2_1.bias)
        primals_143 = (self.thirdStage.fifthConcat.secondSub.
            Mprelu5_stage2_L2_1.weight)
        primals_144 = (self.thirdStage.fifthConcat.thirdSub.
            Mconv5_stage2_L2_2.weight)
        primals_145 = (self.thirdStage.fifthConcat.thirdSub.
            Mconv5_stage2_L2_2.bias)
        primals_146 = (self.thirdStage.fifthConcat.thirdSub.
            Mprelu5_stage2_L2_2.weight)
        primals_147 = self.thirdStage.afterConcatsFirst.Mconv6_stage2_L2.weight
        primals_148 = self.thirdStage.afterConcatsFirst.Mconv6_stage2_L2.bias
        primals_149 = (self.thirdStage.afterConcatsFirst.Mprelu6_stage2_L2.
            weight)
        primals_150 = (self.thirdStage.afterConcatsSecond.Mconv7_stage2_L2.
            weight)
        primals_151 = self.thirdStage.afterConcatsSecond.Mconv7_stage2_L2.bias
        primals_152 = (self.fourthStage.firstConcat.firstSub.
            Mconv1_stage3_L2_0.weight)
        primals_153 = (self.fourthStage.firstConcat.firstSub.
            Mconv1_stage3_L2_0.bias)
        primals_154 = (self.fourthStage.firstConcat.firstSub.
            Mprelu1_stage3_L2_0.weight)
        primals_155 = (self.fourthStage.firstConcat.secondSub.
            Mconv1_stage3_L2_1.weight)
        primals_156 = (self.fourthStage.firstConcat.secondSub.
            Mconv1_stage3_L2_1.bias)
        primals_157 = (self.fourthStage.firstConcat.secondSub.
            Mprelu1_stage3_L2_1.weight)
        primals_158 = (self.fourthStage.firstConcat.thirdSub.
            Mconv1_stage3_L2_2.weight)
        primals_159 = (self.fourthStage.firstConcat.thirdSub.
            Mconv1_stage3_L2_2.bias)
        primals_160 = (self.fourthStage.firstConcat.thirdSub.
            Mprelu1_stage3_L2_2.weight)
        primals_161 = (self.fourthStage.secondConcat.firstSub.
            Mconv2_stage3_L2_0.weight)
        primals_162 = (self.fourthStage.secondConcat.firstSub.
            Mconv2_stage3_L2_0.bias)
        primals_163 = (self.fourthStage.secondConcat.firstSub.
            Mprelu2_stage3_L2_0.weight)
        primals_164 = (self.fourthStage.secondConcat.secondSub.
            Mconv2_stage3_L2_1.weight)
        primals_165 = (self.fourthStage.secondConcat.secondSub.
            Mconv2_stage3_L2_1.bias)
        primals_166 = (self.fourthStage.secondConcat.secondSub.
            Mprelu2_stage3_L2_1.weight)
        primals_167 = (self.fourthStage.secondConcat.thirdSub.
            Mconv2_stage3_L2_2.weight)
        primals_168 = (self.fourthStage.secondConcat.thirdSub.
            Mconv2_stage3_L2_2.bias)
        primals_169 = (self.fourthStage.secondConcat.thirdSub.
            Mprelu2_stage3_L2_2.weight)
        primals_170 = (self.fourthStage.thirdConcat.firstSub.
            Mconv3_stage3_L2_0.weight)
        primals_171 = (self.fourthStage.thirdConcat.firstSub.
            Mconv3_stage3_L2_0.bias)
        primals_172 = (self.fourthStage.thirdConcat.firstSub.
            Mprelu3_stage3_L2_0.weight)
        primals_173 = (self.fourthStage.thirdConcat.secondSub.
            Mconv3_stage3_L2_1.weight)
        primals_174 = (self.fourthStage.thirdConcat.secondSub.
            Mconv3_stage3_L2_1.bias)
        primals_175 = (self.fourthStage.thirdConcat.secondSub.
            Mprelu3_stage3_L2_1.weight)
        primals_176 = (self.fourthStage.thirdConcat.thirdSub.
            Mconv3_stage3_L2_2.weight)
        primals_177 = (self.fourthStage.thirdConcat.thirdSub.
            Mconv3_stage3_L2_2.bias)
        primals_178 = (self.fourthStage.thirdConcat.thirdSub.
            Mprelu3_stage3_L2_2.weight)
        primals_179 = (self.fourthStage.fourthConcat.firstSub.
            Mconv4_stage3_L2_0.weight)
        primals_180 = (self.fourthStage.fourthConcat.firstSub.
            Mconv4_stage3_L2_0.bias)
        primals_181 = (self.fourthStage.fourthConcat.firstSub.
            Mprelu4_stage3_L2_0.weight)
        primals_182 = (self.fourthStage.fourthConcat.secondSub.
            Mconv4_stage3_L2_1.weight)
        primals_183 = (self.fourthStage.fourthConcat.secondSub.
            Mconv4_stage3_L2_1.bias)
        primals_184 = (self.fourthStage.fourthConcat.secondSub.
            Mprelu4_stage3_L2_1.weight)
        primals_185 = (self.fourthStage.fourthConcat.thirdSub.
            Mconv4_stage3_L2_2.weight)
        primals_186 = (self.fourthStage.fourthConcat.thirdSub.
            Mconv4_stage3_L2_2.bias)
        primals_187 = (self.fourthStage.fourthConcat.thirdSub.
            Mprelu4_stage3_L2_2.weight)
        primals_188 = (self.fourthStage.fifthConcat.firstSub.
            Mconv5_stage3_L2_0.weight)
        primals_189 = (self.fourthStage.fifthConcat.firstSub.
            Mconv5_stage3_L2_0.bias)
        primals_190 = (self.fourthStage.fifthConcat.firstSub.
            Mprelu5_stage3_L2_0.weight)
        primals_191 = (self.fourthStage.fifthConcat.secondSub.
            Mconv5_stage3_L2_1.weight)
        primals_192 = (self.fourthStage.fifthConcat.secondSub.
            Mconv5_stage3_L2_1.bias)
        primals_193 = (self.fourthStage.fifthConcat.secondSub.
            Mprelu5_stage3_L2_1.weight)
        primals_194 = (self.fourthStage.fifthConcat.thirdSub.
            Mconv5_stage3_L2_2.weight)
        primals_195 = (self.fourthStage.fifthConcat.thirdSub.
            Mconv5_stage3_L2_2.bias)
        primals_196 = (self.fourthStage.fifthConcat.thirdSub.
            Mprelu5_stage3_L2_2.weight)
        primals_197 = (self.fourthStage.afterConcatsFirst.Mconv6_stage3_L2.
            weight)
        primals_198 = self.fourthStage.afterConcatsFirst.Mconv6_stage3_L2.bias
        primals_199 = (self.fourthStage.afterConcatsFirst.Mprelu6_stage3_L2
            .weight)
        primals_200 = (self.fourthStage.afterConcatsSecond.Mconv7_stage3_L2
            .weight)
        primals_201 = self.fourthStage.afterConcatsSecond.Mconv7_stage3_L2.bias
        primals_3 = input_0
        output = call([primals_1, primals_2, primals_3, primals_4,
            primals_5, primals_6, primals_7, primals_8, primals_9,
            primals_10, primals_11, primals_12, primals_13, primals_14,
            primals_15, primals_16, primals_17, primals_18, primals_19,
            primals_20, primals_21, primals_22, primals_23, primals_24,
            primals_25, primals_26, primals_27, primals_28, primals_29,
            primals_30, primals_31, primals_32, primals_33, primals_34,
            primals_35, primals_36, primals_37, primals_38, primals_39,
            primals_40, primals_41, primals_42, primals_43, primals_44,
            primals_45, primals_46, primals_47, primals_48, primals_49,
            primals_50, primals_51, primals_52, primals_53, primals_54,
            primals_55, primals_56, primals_57, primals_58, primals_59,
            primals_60, primals_61, primals_62, primals_63, primals_64,
            primals_65, primals_66, primals_67, primals_68, primals_69,
            primals_70, primals_71, primals_72, primals_73, primals_74,
            primals_75, primals_76, primals_77, primals_78, primals_79,
            primals_80, primals_81, primals_82, primals_83, primals_84,
            primals_85, primals_86, primals_87, primals_88, primals_89,
            primals_90, primals_91, primals_92, primals_93, primals_94,
            primals_95, primals_96, primals_97, primals_98, primals_99,
            primals_100, primals_101, primals_102, primals_103, primals_104,
            primals_105, primals_106, primals_107, primals_108, primals_109,
            primals_110, primals_111, primals_112, primals_113, primals_114,
            primals_115, primals_116, primals_117, primals_118, primals_119,
            primals_120, primals_121, primals_122, primals_123, primals_124,
            primals_125, primals_126, primals_127, primals_128, primals_129,
            primals_130, primals_131, primals_132, primals_133, primals_134,
            primals_135, primals_136, primals_137, primals_138, primals_139,
            primals_140, primals_141, primals_142, primals_143, primals_144,
            primals_145, primals_146, primals_147, primals_148, primals_149,
            primals_150, primals_151, primals_152, primals_153, primals_154,
            primals_155, primals_156, primals_157, primals_158, primals_159,
            primals_160, primals_161, primals_162, primals_163, primals_164,
            primals_165, primals_166, primals_167, primals_168, primals_169,
            primals_170, primals_171, primals_172, primals_173, primals_174,
            primals_175, primals_176, primals_177, primals_178, primals_179,
            primals_180, primals_181, primals_182, primals_183, primals_184,
            primals_185, primals_186, primals_187, primals_188, primals_189,
            primals_190, primals_191, primals_192, primals_193, primals_194,
            primals_195, primals_196, primals_197, primals_198, primals_199,
            primals_200, primals_201])
        return output[0]
