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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_0(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 256
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    ymask = yindex < ynumel
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    x2 = xindex
    y3 = yindex
    y0 = yindex % 64
    y1 = yindex // 64
    tmp0 = tl.load(in_ptr0 + (x2 + 4096 * y3), ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 64 * x2 + 262144 * y1), tmp0, ymask)


@triton.jit
def triton_poi_fused_1(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 9
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 64
    y1 = yindex // 64
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 64 * x2 + 576 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_2(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 9
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 64
    y1 = yindex // 64
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 64 * x2 + 576 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_3(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 9
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 128
    y1 = yindex // 128
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 128 * x2 + 1152 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_4(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 9
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 128
    y1 = yindex // 128
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 128 * x2 + 1152 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_5(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 9
    yoffset = (tl.program_id(1) + tl.program_id(2) * tl.num_programs(1)
        ) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 256
    y1 = yindex // 256
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 256 * x2 + 2304 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_6(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)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + 0)
    tmp6 = tl.broadcast_to(tmp5, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp7 = tmp6 * tmp2
    tmp8 = tl.where(tmp4, tmp2, tmp7)
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp8, None)


@triton.jit
def triton_poi_fused__prelu_kernel_add_convolution_7(in_out_ptr0, in_ptr0,
    in_ptr1, in_ptr2, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr1 + x2, None)
    tmp6 = tl.load(in_ptr2 + 0)
    tmp7 = tl.broadcast_to(tmp6, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp4 = 0.0
    tmp5 = tmp2 > tmp4
    tmp8 = tmp7 * tmp2
    tmp9 = tl.where(tmp5, tmp2, tmp8)
    tmp10 = tmp3 + tmp9
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp10, None)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_8(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)
    x2 = xindex
    x0 = xindex % 128
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + 0)
    tmp6 = tl.broadcast_to(tmp5, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp7 = tmp6 * tmp2
    tmp8 = tl.where(tmp4, tmp2, tmp7)
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp8, None)


@triton.jit
def triton_poi_fused__prelu_kernel_add_convolution_9(in_out_ptr0, in_ptr0,
    in_ptr1, in_ptr2, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 128
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr1 + x2, None)
    tmp6 = tl.load(in_ptr2 + 0)
    tmp7 = tl.broadcast_to(tmp6, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp4 = 0.0
    tmp5 = tmp2 > tmp4
    tmp8 = tmp7 * tmp2
    tmp9 = tl.where(tmp5, tmp2, tmp8)
    tmp10 = tmp3 + tmp9
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp10, None)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_10(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)
    x2 = xindex
    x0 = xindex % 256
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + 0)
    tmp6 = tl.broadcast_to(tmp5, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp7 = tmp6 * tmp2
    tmp8 = tl.where(tmp4, tmp2, tmp7)
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp8, None)


@triton.jit
def triton_poi_fused__prelu_kernel_add_convolution_11(in_out_ptr0, in_ptr0,
    in_ptr1, in_ptr2, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 256
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr1 + x2, None)
    tmp6 = tl.load(in_ptr2 + 0)
    tmp7 = tl.broadcast_to(tmp6, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp4 = 0.0
    tmp5 = tmp2 > tmp4
    tmp8 = tmp7 * tmp2
    tmp9 = tl.where(tmp5, tmp2, tmp8)
    tmp10 = tmp3 + tmp9
    tl.store(in_out_ptr0 + x2, tmp2, None)
    tl.store(out_ptr0 + x2, tmp10, None)


@triton.jit
def triton_poi_fused_cat_12(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 256
    x1 = xindex // 256 % 32
    x2 = xindex // 8192 % 32
    x3 = xindex // 262144
    x4 = xindex // 256
    x5 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 128, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (2 * (x2 % 2) + 4 * x0 + 512 * (x1 // 2) + 
        8192 * (x2 // 2) + 131072 * x3 + x1 % 2), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + (2 * (x2 % 2) + 4 * x0 + x1 % 2), tmp4,
        eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full(tmp7.shape, 0.0, tmp7.dtype)
    tmp9 = tl.where(tmp4, tmp7, tmp8)
    tmp10 = tmp0 >= tmp3
    tl.full([1], 256, tl.int64)
    tmp13 = tl.load(in_ptr2 + (128 * x4 + (-128 + x0)), tmp10,
        eviction_policy='evict_last', other=0.0)
    tmp14 = tl.where(tmp4, tmp9, tmp13)
    tl.store(out_ptr0 + x5, tmp14, None)


@triton.jit
def triton_poi_fused_convolution_13(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)
    x2 = xindex
    x0 = xindex % 128
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x2, tmp2, None)


@triton.jit
def triton_poi_fused_cat_14(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 128
    x1 = xindex // 128 % 64
    x2 = xindex // 8192 % 64
    x3 = xindex // 524288
    x4 = xindex // 128
    x5 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (2 * (x2 % 2) + 4 * x0 + 256 * (x1 // 2) + 
        8192 * (x2 // 2) + 262144 * x3 + x1 % 2), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + (2 * (x2 % 2) + 4 * x0 + x1 % 2), tmp4,
        eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full(tmp7.shape, 0.0, tmp7.dtype)
    tmp9 = tl.where(tmp4, tmp7, tmp8)
    tmp10 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp13 = tl.load(in_ptr2 + (64 * x4 + (-64 + x0)), tmp10,
        eviction_policy='evict_last', other=0.0)
    tmp14 = tl.where(tmp4, tmp9, tmp13)
    tl.store(out_ptr0 + x5, tmp14, None)


@triton.jit
def triton_poi_fused_convolution_15(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)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x2, tmp2, None)


@triton.jit
def triton_poi_fused_add_convolution_16(in_ptr0, in_ptr1, in_ptr2, out_ptr0,
    ynumel, xnumel, YBLOCK: tl.constexpr, XBLOCK: tl.constexpr):
    xnumel = 64
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    tl.full([XBLOCK, YBLOCK], True, tl.int1)
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 4096
    y1 = yindex // 4096
    tmp0 = tl.load(in_ptr0 + (x2 + 64 * y3), xmask, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr1 + x2, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + (x2 + 64 * y3), xmask, eviction_policy=
        'evict_last')
    tmp2 = tmp0 + tmp1
    tmp4 = tmp2 + tmp3
    tl.store(out_ptr0 + (y0 + 4096 * x2 + 262144 * y1), tmp4, 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
        ) = args
    args.clear()
    assert_size_stride(primals_1, (4, 64, 64, 64), (262144, 4096, 64, 1))
    assert_size_stride(primals_2, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_3, (64,), (1,))
    assert_size_stride(primals_4, (1,), (1,))
    assert_size_stride(primals_5, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_6, (64,), (1,))
    assert_size_stride(primals_7, (1,), (1,))
    assert_size_stride(primals_8, (128, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_9, (128,), (1,))
    assert_size_stride(primals_10, (1,), (1,))
    assert_size_stride(primals_11, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_12, (128,), (1,))
    assert_size_stride(primals_13, (1,), (1,))
    assert_size_stride(primals_14, (256, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_15, (256,), (1,))
    assert_size_stride(primals_16, (1,), (1,))
    assert_size_stride(primals_17, (256, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_18, (256,), (1,))
    assert_size_stride(primals_19, (1,), (1,))
    assert_size_stride(primals_20, (512, 256, 1, 1), (256, 1, 1, 1))
    assert_size_stride(primals_21, (512,), (1,))
    assert_size_stride(primals_22, (128, 256, 1, 1), (256, 1, 1, 1))
    assert_size_stride(primals_23, (128,), (1,))
    assert_size_stride(primals_24, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_25, (128,), (1,))
    assert_size_stride(primals_26, (1,), (1,))
    assert_size_stride(primals_27, (256, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_28, (256,), (1,))
    assert_size_stride(primals_29, (64, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_30, (64,), (1,))
    assert_size_stride(primals_31, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_32, (64,), (1,))
    assert_size_stride(primals_33, (1,), (1,))
    assert_size_stride(primals_34, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_35, (64,), (1,))
    assert_size_stride(primals_36, (1,), (1,))
    assert_size_stride(primals_37, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_38, (64,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.float32)
        get_raw_stream(0)
        triton_poi_fused_0[grid(256, 4096)](primals_1, buf0, 256, 4096,
            XBLOCK=32, YBLOCK=32, num_warps=4, num_stages=1)
        del primals_1
        buf1 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_2, buf1, 4096, 9, XBLOCK=
            16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_2
        buf2 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_5, buf2, 4096, 9, XBLOCK=
            16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_5
        buf3 = empty_strided_cuda((128, 64, 3, 3), (576, 1, 192, 64), torch
            .float32)
        triton_poi_fused_2[grid(8192, 9)](primals_8, buf3, 8192, 9, XBLOCK=
            16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_8
        buf4 = empty_strided_cuda((128, 128, 3, 3), (1152, 1, 384, 128),
            torch.float32)
        triton_poi_fused_3[grid(16384, 9)](primals_11, buf4, 16384, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_11
        buf5 = empty_strided_cuda((256, 128, 3, 3), (1152, 1, 384, 128),
            torch.float32)
        triton_poi_fused_4[grid(32768, 9)](primals_14, buf5, 32768, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_14
        buf6 = empty_strided_cuda((256, 256, 3, 3), (2304, 1, 768, 256),
            torch.float32)
        triton_poi_fused_5[grid(65536, 9)](primals_17, buf6, 65536, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_17
        buf7 = empty_strided_cuda((128, 128, 3, 3), (1152, 1, 384, 128),
            torch.float32)
        triton_poi_fused_3[grid(16384, 9)](primals_24, buf7, 16384, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_24
        buf8 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_31, buf8, 4096, 9, XBLOCK
            =16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_31
        buf9 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_34, buf9, 4096, 9, XBLOCK
            =16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_34
        buf10 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch
            .float32)
        triton_poi_fused_1[grid(4096, 9)](primals_37, buf10, 4096, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_37
        buf11 = extern_kernels.convolution(buf0, buf1, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf11, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf12 = buf11
        del buf11
        buf13 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.float32)
        triton_poi_fused__prelu_kernel_convolution_6[grid(1048576)](buf12,
            primals_3, primals_4, buf13, 1048576, XBLOCK=512, num_warps=8,
            num_stages=1)
        del primals_3
        buf14 = extern_kernels.convolution(buf13, buf2, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf14, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf15 = buf14
        del buf14
        buf16 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.float32)
        triton_poi_fused__prelu_kernel_add_convolution_7[grid(1048576)](buf15,
            primals_6, buf0, primals_7, buf16, 1048576, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_6
        buf17 = extern_kernels.convolution(buf16, buf3, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf17, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf18 = buf17
        del buf17
        buf19 = empty_strided_cuda((4, 128, 32, 32), (131072, 1, 4096, 128),
            torch.float32)
        triton_poi_fused__prelu_kernel_convolution_8[grid(524288)](buf18,
            primals_9, primals_10, buf19, 524288, XBLOCK=1024, num_warps=4,
            num_stages=1)
        del primals_9
        buf20 = extern_kernels.convolution(buf19, buf4, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf20, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf21 = buf20
        del buf20
        buf22 = empty_strided_cuda((4, 128, 32, 32), (131072, 1, 4096, 128),
            torch.float32)
        triton_poi_fused__prelu_kernel_add_convolution_9[grid(524288)](buf21,
            primals_12, buf19, primals_13, buf22, 524288, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_12
        buf23 = extern_kernels.convolution(buf22, buf5, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf23, (4, 256, 16, 16), (65536, 1, 4096, 256))
        buf24 = buf23
        del buf23
        buf25 = empty_strided_cuda((4, 256, 16, 16), (65536, 1, 4096, 256),
            torch.float32)
        triton_poi_fused__prelu_kernel_convolution_10[grid(262144)](buf24,
            primals_15, primals_16, buf25, 262144, XBLOCK=512, num_warps=8,
            num_stages=1)
        del primals_15
        buf26 = extern_kernels.convolution(buf25, buf6, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf26, (4, 256, 16, 16), (65536, 1, 4096, 256))
        buf27 = buf26
        del buf26
        buf28 = empty_strided_cuda((4, 256, 16, 16), (65536, 1, 4096, 256),
            torch.float32)
        triton_poi_fused__prelu_kernel_add_convolution_11[grid(262144)](buf27,
            primals_18, buf25, primals_19, buf28, 262144, XBLOCK=1024,
            num_warps=4, num_stages=1)
        del primals_18
        buf29 = extern_kernels.convolution(buf28, primals_20, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf29, (4, 512, 16, 16), (131072, 1, 8192, 512))
        buf30 = empty_strided_cuda((4, 256, 32, 32), (262144, 1, 8192, 256),
            torch.float32)
        triton_poi_fused_cat_12[grid(1048576)](buf29, primals_21, buf22,
            buf30, 1048576, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_21
        buf31 = extern_kernels.convolution(buf30, primals_22, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf31, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf32 = buf31
        del buf31
        triton_poi_fused_convolution_13[grid(524288)](buf32, primals_23, 
            524288, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_23
        buf33 = extern_kernels.convolution(buf32, buf7, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf33, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf34 = buf33
        del buf33
        buf35 = reinterpret_tensor(buf29, (4, 128, 32, 32), (131072, 1, 
            4096, 128), 0)
        del buf29
        triton_poi_fused__prelu_kernel_add_convolution_9[grid(524288)](buf34,
            primals_25, buf32, primals_26, buf35, 524288, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_25
        buf36 = extern_kernels.convolution(buf35, primals_27, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf36, (4, 256, 32, 32), (262144, 1, 8192, 256))
        buf37 = empty_strided_cuda((4, 128, 64, 64), (524288, 1, 8192, 128),
            torch.float32)
        triton_poi_fused_cat_14[grid(2097152)](buf36, primals_28, buf16,
            buf37, 2097152, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_28
        buf38 = extern_kernels.convolution(buf37, primals_29, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf38, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf39 = buf38
        del buf38
        triton_poi_fused_convolution_15[grid(1048576)](buf39, primals_30, 
            1048576, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_30
        buf40 = extern_kernels.convolution(buf39, buf8, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf40, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf41 = buf40
        del buf40
        buf42 = reinterpret_tensor(buf36, (4, 64, 64, 64), (262144, 1, 4096,
            64), 0)
        del buf36
        triton_poi_fused__prelu_kernel_convolution_6[grid(1048576)](buf41,
            primals_32, primals_33, buf42, 1048576, XBLOCK=512, num_warps=8,
            num_stages=1)
        del primals_32
        buf43 = extern_kernels.convolution(buf42, buf9, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf43, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf44 = buf43
        del buf43
        buf45 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.float32)
        triton_poi_fused__prelu_kernel_add_convolution_7[grid(1048576)](buf44,
            primals_35, buf39, primals_36, buf45, 1048576, XBLOCK=512,
            num_warps=8, num_stages=1)
        del primals_35
        buf46 = extern_kernels.convolution(buf45, buf10, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf46, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf47 = empty_strided_cuda((4, 64, 64, 64), (262144, 4096, 64, 1),
            torch.float32)
        triton_poi_fused_add_convolution_16[grid(16384, 64)](buf46,
            primals_38, buf0, buf47, 16384, 64, XBLOCK=64, YBLOCK=64,
            num_warps=8, num_stages=1)
        del buf46
        del primals_38
    return (buf47, buf0, buf1, primals_4, buf2, primals_7, buf3, primals_10,
        buf4, primals_13, buf5, primals_16, buf6, primals_19, primals_20,
        primals_22, buf7, primals_26, primals_27, primals_29, buf8,
        primals_33, buf9, primals_36, buf10, buf12, buf13, buf15, buf16,
        buf18, buf19, buf21, buf22, buf24, buf25, buf27, buf28, buf30,
        buf32, buf34, buf35, buf37, buf39, buf41, buf42, buf44, buf45)


class _Residual_BlockNew(nn.Module):

    def __init__(self, num_chans=64):
        super(_Residual_BlockNew, self).__init__()
        bias = True
        self.conv1 = nn.Conv2d(num_chans, num_chans, kernel_size=3, stride=
            1, padding=1, bias=bias)
        self.relu2 = nn.PReLU()
        self.conv3 = nn.Conv2d(num_chans, num_chans, kernel_size=3, stride=
            1, padding=1, bias=bias)
        self.relu4 = nn.PReLU()
        self.conv5 = nn.Conv2d(num_chans, num_chans * 2, kernel_size=3,
            stride=2, padding=1, bias=bias)
        self.relu6 = nn.PReLU()
        self.conv7 = nn.Conv2d(num_chans * 2, num_chans * 2, kernel_size=3,
            stride=1, padding=1, bias=bias)
        self.relu8 = nn.PReLU()
        self.conv9 = nn.Conv2d(num_chans * 2, num_chans * 4, kernel_size=3,
            stride=2, padding=1, bias=bias)
        self.relu10 = nn.PReLU()
        self.conv11 = nn.Conv2d(num_chans * 4, num_chans * 4, kernel_size=3,
            stride=1, padding=1, bias=bias)
        self.relu12 = nn.PReLU()
        self.conv13 = nn.Conv2d(num_chans * 4, num_chans * 8, kernel_size=1,
            stride=1, padding=0, bias=bias)
        self.up14 = nn.PixelShuffle(2)
        self.conv15 = nn.Conv2d(num_chans * 4, num_chans * 2, kernel_size=1,
            stride=1, padding=0, bias=bias)
        self.conv16 = nn.Conv2d(num_chans * 2, num_chans * 2, kernel_size=3,
            stride=1, padding=1, bias=bias)
        self.relu17 = nn.PReLU()
        self.conv18 = nn.Conv2d(num_chans * 2, num_chans * 4, kernel_size=1,
            stride=1, padding=0, bias=bias)
        self.up19 = nn.PixelShuffle(2)
        self.conv20 = nn.Conv2d(num_chans * 2, num_chans, kernel_size=1,
            stride=1, padding=0, bias=bias)
        self.conv21 = nn.Conv2d(num_chans, num_chans, kernel_size=3, stride
            =1, padding=1, bias=bias)
        self.relu22 = nn.PReLU()
        self.conv23 = nn.Conv2d(num_chans, num_chans, kernel_size=3, stride
            =1, padding=1, bias=bias)
        self.relu24 = nn.PReLU()
        self.conv25 = nn.Conv2d(num_chans, num_chans, kernel_size=3, stride
            =1, padding=1, bias=bias)

    def forward(self, input_0):
        primals_2 = self.conv1.weight
        primals_3 = self.conv1.bias
        primals_4 = self.relu2.weight
        primals_5 = self.conv3.weight
        primals_6 = self.conv3.bias
        primals_7 = self.relu4.weight
        primals_8 = self.conv5.weight
        primals_9 = self.conv5.bias
        primals_10 = self.relu6.weight
        primals_11 = self.conv7.weight
        primals_12 = self.conv7.bias
        primals_13 = self.relu8.weight
        primals_14 = self.conv9.weight
        primals_15 = self.conv9.bias
        primals_16 = self.relu10.weight
        primals_17 = self.conv11.weight
        primals_18 = self.conv11.bias
        primals_19 = self.relu12.weight
        primals_20 = self.conv13.weight
        primals_21 = self.conv13.bias
        primals_22 = self.conv15.weight
        primals_23 = self.conv15.bias
        primals_24 = self.conv16.weight
        primals_25 = self.conv16.bias
        primals_26 = self.relu17.weight
        primals_27 = self.conv18.weight
        primals_28 = self.conv18.bias
        primals_29 = self.conv20.weight
        primals_30 = self.conv20.bias
        primals_31 = self.conv21.weight
        primals_32 = self.conv21.bias
        primals_33 = self.relu22.weight
        primals_34 = self.conv23.weight
        primals_35 = self.conv23.bias
        primals_36 = self.relu24.weight
        primals_37 = self.conv25.weight
        primals_38 = self.conv25.bias
        primals_1 = 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])
        return output[0]


Measured latency_ms: 0.62468