import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
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):
    xnumel = 16
    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 + 16 * y3), xmask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 64 * x2 + 1024 * y1), tmp0, xmask)


@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 = 16
    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 + 16 * y3), xmask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 64 * x2 + 1024 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_3(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, 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')
    tmp1 = tl.load(in_ptr1 + y0, ymask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + (y0 + 64 * x2 + 262144 * y1), tmp4, ymask)
    tl.store(out_ptr1 + (y0 + 64 * x2 + 262144 * y1), tmp7, ymask)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_4(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, None)
    tl.store(out_ptr1 + x2, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_5(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, None)
    tl.store(out_ptr1 + x2, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_6(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, None)
    tl.store(out_ptr1 + x2, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_7(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, None)
    tl.store(out_ptr1 + x2, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_8(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xnumel = 1024
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, xmask)
    tl.store(out_ptr1 + x2, tmp7, xmask)


@triton.jit
def triton_poi_fused_convolution_leaky_relu_9(in_ptr0, in_ptr1, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp5 = 0.2
    tmp6 = tmp2 * tmp5
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(out_ptr0 + x2, tmp4, xmask)
    tl.store(out_ptr1 + x2, tmp7, xmask)


@triton.jit
def triton_poi_fused_cat_10(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
    x0 = xindex % 128
    x1 = xindex // 128
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, xmask)


@triton.jit
def triton_poi_fused_cat_11(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
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, 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 % 128
    x1 = xindex // 128
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_cat_13(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
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, 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
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_cat_15(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
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_cat_16(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
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 64, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (64 * x1 + x0), tmp4, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x0, tmp4, eviction_policy='evict_last', other=0.0)
    tmp7 = tmp5 + tmp6
    tmp8 = tl.full([1], 0, tl.int32)
    tmp9 = triton_helpers.maximum(tmp8, tmp7)
    tmp10 = tl.full(tmp9.shape, 0.0, tmp9.dtype)
    tmp11 = tl.where(tmp4, tmp9, tmp10)
    tmp12 = tmp0 >= tmp3
    tl.full([1], 128, tl.int64)
    tmp15 = tl.load(in_ptr2 + (64 * x1 + (-64 + x0)), tmp12,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.where(tmp4, tmp11, tmp15)
    tl.store(out_ptr0 + x2, tmp16, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_17(in_out_ptr0,
    in_ptr0, 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
    tmp0 = tl.load(in_out_ptr0 + x0, None)
    tmp1 = tl.load(in_ptr0 + 0)
    tmp2 = tl.broadcast_to(tmp1, [XBLOCK])
    tmp3 = tmp0 + tmp2
    tmp4 = tl.full([1], 0, tl.int32)
    tmp5 = triton_helpers.maximum(tmp4, tmp3)
    tmp6 = 0.0
    tmp7 = tmp5 <= tmp6
    tl.store(in_out_ptr0 + x0, tmp5, None)
    tl.store(out_ptr0 + x0, tmp7, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_18(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_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_19(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_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_20(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_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_21(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_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_22(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_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr1 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_23(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
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, xmask)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_24(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
    x2 = xindex
    x0 = xindex % 64
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, xmask)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9, primals_10, primals_11, primals_12,
        primals_13, primals_14, primals_15, primals_16, primals_17,
        primals_18, primals_19, primals_20, primals_21, primals_22,
        primals_23, primals_24, primals_25, primals_26, primals_27,
        primals_28, primals_29, primals_30, primals_31, primals_32, primals_33
        ) = args
    args.clear()
    assert_size_stride(primals_1, (64, 1, 6, 6), (36, 36, 6, 1))
    assert_size_stride(primals_2, (64,), (1,))
    assert_size_stride(primals_3, (4, 1, 128, 128), (16384, 16384, 128, 1))
    assert_size_stride(primals_4, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_5, (64,), (1,))
    assert_size_stride(primals_6, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_7, (64,), (1,))
    assert_size_stride(primals_8, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_9, (64,), (1,))
    assert_size_stride(primals_10, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_11, (64,), (1,))
    assert_size_stride(primals_12, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_13, (64,), (1,))
    assert_size_stride(primals_14, (64, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_15, (64,), (1,))
    assert_size_stride(primals_16, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_17, (64,), (1,))
    assert_size_stride(primals_18, (64, 64, 3, 3), (576, 9, 3, 1))
    assert_size_stride(primals_19, (64,), (1,))
    assert_size_stride(primals_20, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_21, (64,), (1,))
    assert_size_stride(primals_22, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_23, (64,), (1,))
    assert_size_stride(primals_24, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_25, (64,), (1,))
    assert_size_stride(primals_26, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_27, (64,), (1,))
    assert_size_stride(primals_28, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_29, (64,), (1,))
    assert_size_stride(primals_30, (128, 64, 4, 4), (1024, 16, 4, 1))
    assert_size_stride(primals_31, (64,), (1,))
    assert_size_stride(primals_32, (128, 1, 6, 6), (36, 36, 6, 1))
    assert_size_stride(primals_33, (1,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        get_raw_stream(0)
        triton_poi_fused_0[grid(4096, 16)](primals_4, buf0, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_4
        buf1 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_0[grid(4096, 16)](primals_6, buf1, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_6
        buf2 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_0[grid(4096, 16)](primals_8, buf2, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_8
        buf3 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_0[grid(4096, 16)](primals_10, buf3, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_10
        buf4 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_0[grid(4096, 16)](primals_12, buf4, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_12
        buf5 = empty_strided_cuda((64, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_0[grid(4096, 16)](primals_14, buf5, 4096, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_14
        buf6 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_16, buf6, 4096, 9, XBLOCK
            =16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_16
        buf7 = empty_strided_cuda((64, 64, 3, 3), (576, 1, 192, 64), torch.
            float32)
        triton_poi_fused_1[grid(4096, 9)](primals_18, buf7, 4096, 9, XBLOCK
            =16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_18
        buf8 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_20, buf8, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_20
        buf9 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_22, buf9, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_22
        buf10 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_24, buf10, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_24
        buf11 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_26, buf11, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_26
        buf12 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_28, buf12, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_28
        buf13 = empty_strided_cuda((128, 64, 4, 4), (1024, 1, 256, 64),
            torch.float32)
        triton_poi_fused_2[grid(8192, 16)](primals_30, buf13, 8192, 16,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_30
        buf14 = extern_kernels.convolution(primals_3, primals_1, stride=(2,
            2), padding=(2, 2), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf14, (4, 64, 64, 64), (262144, 4096, 64, 1))
        buf15 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.bool)
        buf16 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.float32)
        triton_poi_fused_convolution_leaky_relu_3[grid(256, 4096)](buf14,
            primals_2, buf15, buf16, 256, 4096, XBLOCK=4, YBLOCK=256,
            num_warps=4, num_stages=1)
        del buf14
        del primals_2
        buf17 = extern_kernels.convolution(buf16, buf0, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf17, (4, 64, 32, 32), (65536, 1, 2048, 64))
        buf18 = empty_strided_cuda((4, 64, 32, 32), (65536, 1, 2048, 64),
            torch.bool)
        buf19 = empty_strided_cuda((4, 64, 32, 32), (65536, 1, 2048, 64),
            torch.float32)
        triton_poi_fused_convolution_leaky_relu_4[grid(262144)](buf17,
            primals_5, buf18, buf19, 262144, XBLOCK=1024, num_warps=4,
            num_stages=1)
        del buf17
        del primals_5
        buf20 = extern_kernels.convolution(buf19, buf1, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf20, (4, 64, 16, 16), (16384, 1, 1024, 64))
        buf21 = empty_strided_cuda((4, 64, 16, 16), (16384, 1, 1024, 64),
            torch.bool)
        buf22 = empty_strided_cuda((4, 64, 16, 16), (16384, 1, 1024, 64),
            torch.float32)
        triton_poi_fused_convolution_leaky_relu_5[grid(65536)](buf20,
            primals_7, buf21, buf22, 65536, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf20
        del primals_7
        buf23 = extern_kernels.convolution(buf22, buf2, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf23, (4, 64, 8, 8), (4096, 1, 512, 64))
        buf24 = empty_strided_cuda((4, 64, 8, 8), (4096, 1, 512, 64), torch
            .bool)
        buf25 = empty_strided_cuda((4, 64, 8, 8), (4096, 1, 512, 64), torch
            .float32)
        triton_poi_fused_convolution_leaky_relu_6[grid(16384)](buf23,
            primals_9, buf24, buf25, 16384, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf23
        del primals_9
        buf26 = extern_kernels.convolution(buf25, buf3, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf26, (4, 64, 4, 4), (1024, 1, 256, 64))
        buf27 = empty_strided_cuda((4, 64, 4, 4), (1024, 1, 256, 64), torch
            .bool)
        buf28 = empty_strided_cuda((4, 64, 4, 4), (1024, 1, 256, 64), torch
            .float32)
        triton_poi_fused_convolution_leaky_relu_7[grid(4096)](buf26,
            primals_11, buf27, buf28, 4096, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf26
        del primals_11
        buf29 = extern_kernels.convolution(buf28, buf4, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf29, (4, 64, 2, 2), (256, 1, 128, 64))
        buf30 = empty_strided_cuda((4, 64, 2, 2), (256, 1, 128, 64), torch.bool
            )
        buf31 = empty_strided_cuda((4, 64, 2, 2), (256, 1, 128, 64), torch.
            float32)
        triton_poi_fused_convolution_leaky_relu_8[grid(1024)](buf29,
            primals_13, buf30, buf31, 1024, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf29
        del primals_13
        buf32 = extern_kernels.convolution(buf31, buf5, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf32, (4, 64, 1, 1), (64, 1, 64, 64))
        buf33 = empty_strided_cuda((4, 64, 1, 1), (64, 1, 64, 64), torch.bool)
        buf34 = empty_strided_cuda((4, 64, 1, 1), (64, 1, 64, 64), torch.
            float32)
        triton_poi_fused_convolution_leaky_relu_9[grid(256)](buf32,
            primals_15, buf33, buf34, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del primals_15
        buf35 = extern_kernels.convolution(buf34, buf6, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf35, (4, 64, 1, 1), (64, 1, 64, 64))
        buf36 = empty_strided_cuda((4, 64, 1, 1), (64, 1, 64, 64), torch.bool)
        buf37 = buf32
        del buf32
        triton_poi_fused_convolution_leaky_relu_9[grid(256)](buf35,
            primals_17, buf36, buf37, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf35
        del primals_17
        buf38 = extern_kernels.convolution(buf37, buf7, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf38, (4, 64, 1, 1), (64, 1, 64, 64))
        buf39 = empty_strided_cuda((4, 128, 1, 1), (128, 1, 128, 128),
            torch.float32)
        triton_poi_fused_cat_10[grid(512)](buf38, primals_19, buf34, buf39,
            512, XBLOCK=256, num_warps=4, num_stages=1)
        buf40 = extern_kernels.convolution(buf39, buf8, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf40, (4, 64, 2, 2), (256, 1, 128, 64))
        buf41 = empty_strided_cuda((4, 128, 2, 2), (512, 1, 256, 128),
            torch.float32)
        triton_poi_fused_cat_11[grid(2048)](buf40, primals_21, buf31, buf41,
            2048, XBLOCK=256, num_warps=4, num_stages=1)
        buf42 = extern_kernels.convolution(buf41, buf9, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf42, (4, 64, 4, 4), (1024, 1, 256, 64))
        buf43 = empty_strided_cuda((4, 128, 4, 4), (2048, 1, 512, 128),
            torch.float32)
        triton_poi_fused_cat_12[grid(8192)](buf42, primals_23, buf28, buf43,
            8192, XBLOCK=256, num_warps=4, num_stages=1)
        buf44 = extern_kernels.convolution(buf43, buf10, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf44, (4, 64, 8, 8), (4096, 1, 512, 64))
        buf45 = empty_strided_cuda((4, 128, 8, 8), (8192, 1, 1024, 128),
            torch.float32)
        triton_poi_fused_cat_13[grid(32768)](buf44, primals_25, buf25,
            buf45, 32768, XBLOCK=128, num_warps=4, num_stages=1)
        buf46 = extern_kernels.convolution(buf45, buf11, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf46, (4, 64, 16, 16), (16384, 1, 1024, 64))
        buf47 = empty_strided_cuda((4, 128, 16, 16), (32768, 1, 2048, 128),
            torch.float32)
        triton_poi_fused_cat_14[grid(131072)](buf46, primals_27, buf22,
            buf47, 131072, XBLOCK=512, num_warps=8, num_stages=1)
        buf48 = extern_kernels.convolution(buf47, buf12, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf48, (4, 64, 32, 32), (65536, 1, 2048, 64))
        buf49 = empty_strided_cuda((4, 128, 32, 32), (131072, 1, 4096, 128),
            torch.float32)
        triton_poi_fused_cat_15[grid(524288)](buf48, primals_29, buf19,
            buf49, 524288, XBLOCK=512, num_warps=8, num_stages=1)
        buf50 = extern_kernels.convolution(buf49, buf13, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf50, (4, 64, 64, 64), (262144, 1, 4096, 64))
        buf51 = empty_strided_cuda((4, 128, 64, 64), (524288, 1, 8192, 128),
            torch.float32)
        triton_poi_fused_cat_16[grid(2097152)](buf50, primals_31, buf16,
            buf51, 2097152, XBLOCK=1024, num_warps=4, num_stages=1)
        buf52 = extern_kernels.convolution(buf51, primals_32, stride=(2, 2),
            padding=(2, 2), dilation=(1, 1), transposed=True,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf52, (4, 1, 128, 128), (16384, 1, 128, 1))
        buf53 = reinterpret_tensor(buf52, (4, 1, 128, 128), (16384, 16384, 
            128, 1), 0)
        del buf52
        buf54 = empty_strided_cuda((4, 1, 128, 128), (16384, 1, 128, 1),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_17[grid(65536)](
            buf53, primals_33, buf54, 65536, XBLOCK=512, num_warps=4,
            num_stages=1)
        del primals_33
        buf55 = empty_strided_cuda((4, 64, 64, 64), (262144, 1, 4096, 64),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_18[grid(1048576)](
            buf50, primals_31, buf55, 1048576, XBLOCK=1024, num_warps=4,
            num_stages=1)
        del buf50
        del primals_31
        buf56 = empty_strided_cuda((4, 64, 32, 32), (65536, 1, 2048, 64),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_19[grid(262144)](
            buf48, primals_29, buf56, 262144, XBLOCK=1024, num_warps=4,
            num_stages=1)
        del buf48
        del primals_29
        buf57 = empty_strided_cuda((4, 64, 16, 16), (16384, 1, 1024, 64),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_20[grid(65536)](
            buf46, primals_27, buf57, 65536, XBLOCK=512, num_warps=4,
            num_stages=1)
        del buf46
        del primals_27
        buf58 = empty_strided_cuda((4, 64, 8, 8), (4096, 1, 512, 64), torch
            .bool)
        triton_poi_fused_convolution_relu_threshold_backward_21[grid(16384)](
            buf44, primals_25, buf58, 16384, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf44
        del primals_25
        buf59 = empty_strided_cuda((4, 64, 4, 4), (1024, 1, 256, 64), torch
            .bool)
        triton_poi_fused_convolution_relu_threshold_backward_22[grid(4096)](
            buf42, primals_23, buf59, 4096, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf42
        del primals_23
        buf60 = empty_strided_cuda((4, 64, 2, 2), (256, 1, 128, 64), torch.bool
            )
        triton_poi_fused_convolution_relu_threshold_backward_23[grid(1024)](
            buf40, primals_21, buf60, 1024, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf40
        del primals_21
        buf61 = empty_strided_cuda((4, 64, 1, 1), (64, 1, 64, 64), torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_24[grid(256)](
            buf38, primals_19, buf61, 256, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf38
        del primals_19
    return (buf53, primals_1, primals_3, buf0, buf1, buf2, buf3, buf4, buf5,
        buf6, buf7, buf8, buf9, buf10, buf11, buf12, buf13, primals_32,
        buf15, buf16, buf18, buf19, buf21, buf22, buf24, buf25, buf27,
        buf28, buf30, buf31, buf33, buf34, buf36, buf37, buf39, buf41,
        buf43, buf45, buf47, buf49, buf51, buf54, buf55, buf56, buf57,
        buf58, buf59, buf60, buf61)


class Conv2d(nn.Module):

    def __init__(self, in_channels, out_channels, kernel_size, stride=1, bn
        =False, activation='leakyrelu', dropout=False):
        super(Conv2d, self).__init__()
        padding = int((kernel_size - 1) / 2)
        self.conv = nn.Conv2d(in_channels, out_channels, kernel_size,
            stride, padding=padding)
        self.bn = nn.BatchNorm2d(out_channels, eps=0.001, momentum=0,
            affine=True) if bn else None
        self.dropout = nn.Dropout(p=0.5) if dropout else None
        if activation == 'leakyrelu':
            self.activation = nn.LeakyReLU(negative_slope=0.2)
        elif activation == 'relu':
            self.activation = nn.ReLU()
        elif activation == 'tanh':
            self.activation = nn.Tanh()
        else:
            raise ValueError('Not a valid activation, received {}'.format(
                activation))

    def forward(self, x):
        x = self.conv(x)
        if self.bn is not None:
            x = self.bn(x)
        if self.dropout is not None:
            x = self.dropout(x)
        x = self.activation(x)
        return x


class Deconv2d(nn.Module):

    def __init__(self, in_channels, out_channels, kernel_size, stride=1, bn
        =False, activation='leakyrelu', dropout=False):
        super(Deconv2d, self).__init__()
        padding = int((kernel_size - 1) / 2)
        self.conv = nn.ConvTranspose2d(in_channels, out_channels,
            kernel_size, stride, padding=padding)
        self.bn = nn.BatchNorm2d(out_channels, eps=0.001, momentum=0,
            affine=True) if bn else None
        self.dropout = nn.Dropout(p=0.5) if dropout else None
        if activation == 'leakyrelu':
            self.activation = nn.LeakyReLU(negative_slope=0.2)
        elif activation == 'relu':
            self.activation = nn.ReLU()
        elif activation == 'tanh':
            self.activation = nn.Tanh()
        else:
            raise ValueError('Not a valid activation, received {}'.format(
                activation))

    def forward(self, x):
        x = self.conv(x)
        if self.bn is not None:
            x = self.bn(x)
        if self.dropout is not None:
            x = self.dropout(x)
        x = self.activation(x)
        return x


class G_LargeNew(nn.Module):

    def __init__(self):
        super(G_LargeNew, self).__init__()
        self.encoder_1 = Conv2d(1, 64, 6, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_2 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_3 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_4 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_5 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_6 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_7 = Conv2d(64, 64, 4, stride=2, bn=False, activation=
            'leakyrelu', dropout=False)
        self.encoder_8 = Conv2d(64, 64, 3, stride=1, bn=False, activation=
            'leakyrelu', dropout=False)
        self.decoder_1 = Deconv2d(64, 64, 3, stride=1, bn=False, activation
            ='relu', dropout=True)
        self.decoder_2 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=True)
        self.decoder_3 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=True)
        self.decoder_4 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=False)
        self.decoder_5 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=False)
        self.decoder_6 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=False)
        self.decoder_7 = Deconv2d(128, 64, 4, stride=2, bn=False,
            activation='relu', dropout=False)
        self.decoder_8 = Deconv2d(128, 1, 6, stride=2, bn=False, activation
            ='relu', dropout=False)

    def forward(self, input_0):
        primals_1 = self.encoder_1.conv.weight
        primals_2 = self.encoder_1.conv.bias
        primals_4 = self.encoder_2.conv.weight
        primals_5 = self.encoder_2.conv.bias
        primals_6 = self.encoder_3.conv.weight
        primals_7 = self.encoder_3.conv.bias
        primals_8 = self.encoder_4.conv.weight
        primals_9 = self.encoder_4.conv.bias
        primals_10 = self.encoder_5.conv.weight
        primals_11 = self.encoder_5.conv.bias
        primals_12 = self.encoder_6.conv.weight
        primals_13 = self.encoder_6.conv.bias
        primals_14 = self.encoder_7.conv.weight
        primals_15 = self.encoder_7.conv.bias
        primals_16 = self.encoder_8.conv.weight
        primals_17 = self.encoder_8.conv.bias
        primals_18 = self.decoder_1.conv.weight
        primals_19 = self.decoder_1.conv.bias
        primals_20 = self.decoder_2.conv.weight
        primals_21 = self.decoder_2.conv.bias
        primals_22 = self.decoder_3.conv.weight
        primals_23 = self.decoder_3.conv.bias
        primals_24 = self.decoder_4.conv.weight
        primals_25 = self.decoder_4.conv.bias
        primals_26 = self.decoder_5.conv.weight
        primals_27 = self.decoder_5.conv.bias
        primals_28 = self.decoder_6.conv.weight
        primals_29 = self.decoder_6.conv.bias
        primals_30 = self.decoder_7.conv.weight
        primals_31 = self.decoder_7.conv.bias
        primals_32 = self.decoder_8.conv.weight
        primals_33 = self.decoder_8.conv.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])
        return output[0]


Measured latency_ms: 0.025243