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


@triton.jit
def triton_poi_fused_0(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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]
    xmask = xindex < xnumel
    x2 = xindex
    y3 = yindex
    y0 = yindex % 4
    y1 = yindex // 4
    tmp0 = tl.load(in_ptr0 + (x2 + 16 * y3), xmask & ymask)
    tl.store(out_ptr0 + (y0 + 4 * x2 + 64 * y1), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused_1(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    xnumel = 3
    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 % 384
    y1 = yindex // 384
    tmp0 = tl.load(in_ptr0 + (x2 + 3 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 384 * x2 + 1152 * 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) + 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 % 448
    y1 = yindex // 448
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask, eviction_policy='evict_last'
        )
    tl.store(out_ptr0 + (y0 + 448 * x2 + 4032 * y1), tmp0, xmask)


@triton.jit
def triton_poi_fused_convolution_relu_3(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 % 384
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x2, tmp4, None)


@triton.jit
def triton_poi_fused_convolution_relu_4(in_out_ptr0, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x2 = xindex
    x0 = xindex % 448
    tmp0 = tl.load(in_out_ptr0 + x2, None)
    tmp1 = tl.load(in_ptr0 + x0, None, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tl.store(in_out_ptr0 + x2, tmp4, None)


@triton.jit
def triton_poi_fused_avg_pool2d_5(in_ptr0, 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 // 16 % 4
    x1 = xindex // 4 % 4
    x6 = xindex
    tmp0 = -1 + x2
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tmp2 & tmp4
    tmp6 = -1 + x1
    tmp7 = tmp6 >= tmp1
    tmp8 = tmp6 < tmp3
    tmp9 = tmp7 & tmp8
    tmp10 = tmp5 & tmp9
    tmp11 = tl.load(in_ptr0 + (-20 + x6), tmp10 & xmask, other=0.0)
    tmp12 = x1
    tmp13 = tmp12 >= tmp1
    tmp14 = tmp12 < tmp3
    tmp15 = tmp13 & tmp14
    tmp16 = tmp5 & tmp15
    tmp17 = tl.load(in_ptr0 + (-16 + x6), tmp16 & xmask, other=0.0)
    tmp18 = tmp17 + tmp11
    tmp19 = 1 + x1
    tmp20 = tmp19 >= tmp1
    tmp21 = tmp19 < tmp3
    tmp22 = tmp20 & tmp21
    tmp23 = tmp5 & tmp22
    tmp24 = tl.load(in_ptr0 + (-12 + x6), tmp23 & xmask, other=0.0)
    tmp25 = tmp24 + tmp18
    tmp26 = x2
    tmp27 = tmp26 >= tmp1
    tmp28 = tmp26 < tmp3
    tmp29 = tmp27 & tmp28
    tmp30 = tmp29 & tmp9
    tmp31 = tl.load(in_ptr0 + (-4 + x6), tmp30 & xmask, other=0.0)
    tmp32 = tmp31 + tmp25
    tmp33 = tmp29 & tmp15
    tmp34 = tl.load(in_ptr0 + x6, tmp33 & xmask, other=0.0)
    tmp35 = tmp34 + tmp32
    tmp36 = tmp29 & tmp22
    tmp37 = tl.load(in_ptr0 + (4 + x6), tmp36 & xmask, other=0.0)
    tmp38 = tmp37 + tmp35
    tmp39 = 1 + x2
    tmp40 = tmp39 >= tmp1
    tmp41 = tmp39 < tmp3
    tmp42 = tmp40 & tmp41
    tmp43 = tmp42 & tmp9
    tmp44 = tl.load(in_ptr0 + (12 + x6), tmp43 & xmask, other=0.0)
    tmp45 = tmp44 + tmp38
    tmp46 = tmp42 & tmp15
    tmp47 = tl.load(in_ptr0 + (16 + x6), tmp46 & xmask, other=0.0)
    tmp48 = tmp47 + tmp45
    tmp49 = tmp42 & tmp22
    tmp50 = tl.load(in_ptr0 + (20 + x6), tmp49 & xmask, other=0.0)
    tmp51 = tmp50 + tmp48
    tmp52 = 1 + -1 * x1 + -1 * x2 + x1 * x2 + (5 * (5 <= 2 + x1) + (2 + x1) *
        (2 + x1 < 5)) * (5 * (5 <= 2 + x2) + (2 + x2) * (2 + x2 < 5)
        ) + -1 * x1 * (5 * (5 <= 2 + x2) + (2 + x2) * (2 + x2 < 5)
        ) + -1 * x2 * (5 * (5 <= 2 + x1) + (2 + x1) * (2 + x1 < 5)) + (5 *
        (5 <= 2 + x1) + (2 + x1) * (2 + x1 < 5)) + (5 * (5 <= 2 + x2) + (2 +
        x2) * (2 + x2 < 5))
    tmp53 = tmp51 / tmp52
    tl.store(out_ptr0 + x6, tmp53, xmask)


@triton.jit
def triton_poi_fused_cat_6(in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4,
    in_ptr5, in_ptr6, in_ptr7, in_ptr8, in_ptr9, in_ptr10, in_ptr11,
    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 % 2048
    x0 = xindex % 16
    x2 = xindex // 32768
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 320, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (320 * x0 + 5120 * x2 + x1), tmp4,
        eviction_policy='evict_last', other=0.0)
    tmp6 = tl.load(in_ptr1 + x1, 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
    tmp13 = tl.full([1], 1088, tl.int64)
    tmp14 = tmp0 < tmp13
    tmp15 = tmp12 & tmp14
    tmp16 = -320 + x1
    tmp18 = tl.full([1], 384, tl.int64)
    tmp19 = tmp16 < tmp18
    tmp20 = tmp19 & tmp15
    tmp21 = tl.load(in_ptr2 + (384 * x0 + 6144 * x2 + (-320 + x1)), tmp20,
        eviction_policy='evict_last', other=0.0)
    tmp22 = tl.load(in_ptr3 + (-320 + x1), tmp20, eviction_policy=
        'evict_last', other=0.0)
    tmp23 = tmp21 + tmp22
    tmp24 = triton_helpers.maximum(tmp8, tmp23)
    tmp25 = tl.full(tmp24.shape, 0.0, tmp24.dtype)
    tmp26 = tl.where(tmp20, tmp24, tmp25)
    tmp27 = tmp16 >= tmp18
    tl.full([1], 768, tl.int64)
    tmp30 = tmp27 & tmp15
    tmp31 = tl.load(in_ptr4 + (384 * x0 + 6144 * x2 + (-384 + (-320 + x1))),
        tmp30, eviction_policy='evict_last', other=0.0)
    tmp32 = tl.load(in_ptr5 + (-384 + (-320 + x1)), tmp30, eviction_policy=
        'evict_last', other=0.0)
    tmp33 = tmp31 + tmp32
    tmp34 = triton_helpers.maximum(tmp8, tmp33)
    tmp35 = tl.full(tmp34.shape, 0.0, tmp34.dtype)
    tmp36 = tl.where(tmp30, tmp34, tmp35)
    tmp37 = tl.where(tmp19, tmp26, tmp36)
    tmp38 = tl.full(tmp37.shape, 0.0, tmp37.dtype)
    tmp39 = tl.where(tmp15, tmp37, tmp38)
    tmp40 = tmp0 >= tmp13
    tmp41 = tl.full([1], 1856, tl.int64)
    tmp42 = tmp0 < tmp41
    tmp43 = tmp40 & tmp42
    tmp44 = -1088 + x1
    tmp46 = tmp44 < tmp18
    tmp47 = tmp46 & tmp43
    tmp48 = tl.load(in_ptr6 + (384 * x0 + 6144 * x2 + (-1088 + x1)), tmp47,
        eviction_policy='evict_last', other=0.0)
    tmp49 = tl.load(in_ptr7 + (-1088 + x1), tmp47, eviction_policy=
        'evict_last', other=0.0)
    tmp50 = tmp48 + tmp49
    tmp51 = triton_helpers.maximum(tmp8, tmp50)
    tmp52 = tl.full(tmp51.shape, 0.0, tmp51.dtype)
    tmp53 = tl.where(tmp47, tmp51, tmp52)
    tmp54 = tmp44 >= tmp18
    tmp56 = tmp54 & tmp43
    tmp57 = tl.load(in_ptr8 + (384 * x0 + 6144 * x2 + (-384 + (-1088 + x1))
        ), tmp56, eviction_policy='evict_last', other=0.0)
    tmp58 = tl.load(in_ptr9 + (-384 + (-1088 + x1)), tmp56, eviction_policy
        ='evict_last', other=0.0)
    tmp59 = tmp57 + tmp58
    tmp60 = triton_helpers.maximum(tmp8, tmp59)
    tmp61 = tl.full(tmp60.shape, 0.0, tmp60.dtype)
    tmp62 = tl.where(tmp56, tmp60, tmp61)
    tmp63 = tl.where(tmp46, tmp53, tmp62)
    tmp64 = tl.full(tmp63.shape, 0.0, tmp63.dtype)
    tmp65 = tl.where(tmp43, tmp63, tmp64)
    tmp66 = tmp0 >= tmp41
    tl.full([1], 2048, tl.int64)
    tmp69 = tl.load(in_ptr10 + (192 * x0 + 3072 * x2 + (-1856 + x1)), tmp66,
        eviction_policy='evict_last', other=0.0)
    tmp70 = tl.load(in_ptr11 + (-1856 + x1), tmp66, eviction_policy=
        'evict_last', other=0.0)
    tmp71 = tmp69 + tmp70
    tmp72 = triton_helpers.maximum(tmp8, tmp71)
    tmp73 = tl.full(tmp72.shape, 0.0, tmp72.dtype)
    tmp74 = tl.where(tmp66, tmp72, tmp73)
    tmp75 = tl.where(tmp43, tmp65, tmp74)
    tmp76 = tl.where(tmp15, tmp39, tmp75)
    tmp77 = tl.where(tmp4, tmp11, tmp76)
    tl.store(out_ptr0 + x3, tmp77, None)


@triton.jit
def triton_poi_fused_convolution_relu_threshold_backward_7(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 % 192
    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_8(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 % 384
    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_9(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 % 320
    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)


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) = args
    args.clear()
    assert_size_stride(primals_1, (320, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_2, (320,), (1,))
    assert_size_stride(primals_3, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_4, (384, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_5, (384,), (1,))
    assert_size_stride(primals_6, (384, 384, 1, 3), (1152, 3, 3, 1))
    assert_size_stride(primals_7, (384,), (1,))
    assert_size_stride(primals_8, (384, 384, 3, 1), (1152, 3, 1, 1))
    assert_size_stride(primals_9, (384,), (1,))
    assert_size_stride(primals_10, (448, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_11, (448,), (1,))
    assert_size_stride(primals_12, (384, 448, 3, 3), (4032, 9, 3, 1))
    assert_size_stride(primals_13, (384,), (1,))
    assert_size_stride(primals_14, (384, 384, 1, 3), (1152, 3, 3, 1))
    assert_size_stride(primals_15, (384,), (1,))
    assert_size_stride(primals_16, (384, 384, 3, 1), (1152, 3, 1, 1))
    assert_size_stride(primals_17, (384,), (1,))
    assert_size_stride(primals_18, (192, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_19, (192,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((4, 4, 4, 4), (64, 1, 16, 4), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_0[grid(16, 16)](primals_3, buf0, 16, 16, XBLOCK=16,
            YBLOCK=16, num_warps=4, num_stages=1)
        del primals_3
        buf1 = empty_strided_cuda((384, 384, 1, 3), (1152, 1, 1152, 384),
            torch.float32)
        triton_poi_fused_1[grid(147456, 3)](primals_6, buf1, 147456, 3,
            XBLOCK=4, YBLOCK=256, num_warps=4, num_stages=1)
        del primals_6
        buf2 = empty_strided_cuda((384, 384, 3, 1), (1152, 1, 384, 384),
            torch.float32)
        triton_poi_fused_1[grid(147456, 3)](primals_8, buf2, 147456, 3,
            XBLOCK=4, YBLOCK=256, num_warps=4, num_stages=1)
        del primals_8
        buf3 = empty_strided_cuda((384, 448, 3, 3), (4032, 1, 1344, 448),
            torch.float32)
        triton_poi_fused_2[grid(172032, 9)](primals_12, buf3, 172032, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_12
        buf4 = empty_strided_cuda((384, 384, 1, 3), (1152, 1, 1152, 384),
            torch.float32)
        triton_poi_fused_1[grid(147456, 3)](primals_14, buf4, 147456, 3,
            XBLOCK=4, YBLOCK=256, num_warps=4, num_stages=1)
        del primals_14
        buf5 = empty_strided_cuda((384, 384, 3, 1), (1152, 1, 384, 384),
            torch.float32)
        triton_poi_fused_1[grid(147456, 3)](primals_16, buf5, 147456, 3,
            XBLOCK=4, YBLOCK=256, num_warps=4, num_stages=1)
        del primals_16
        buf6 = extern_kernels.convolution(buf0, primals_1, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf6, (4, 320, 4, 4), (5120, 1, 1280, 320))
        buf7 = extern_kernels.convolution(buf0, primals_4, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf7, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf8 = buf7
        del buf7
        triton_poi_fused_convolution_relu_3[grid(24576)](buf8, primals_5, 
            24576, XBLOCK=128, num_warps=4, num_stages=1)
        del primals_5
        buf9 = extern_kernels.convolution(buf8, buf1, stride=(1, 1),
            padding=(0, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf9, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf10 = extern_kernels.convolution(buf8, buf2, stride=(1, 1),
            padding=(1, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf10, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf11 = extern_kernels.convolution(buf0, primals_10, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf11, (4, 448, 4, 4), (7168, 1, 1792, 448))
        buf12 = buf11
        del buf11
        triton_poi_fused_convolution_relu_4[grid(28672)](buf12, primals_11,
            28672, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_11
        buf13 = extern_kernels.convolution(buf12, buf3, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf13, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf14 = buf13
        del buf13
        triton_poi_fused_convolution_relu_3[grid(24576)](buf14, primals_13,
            24576, XBLOCK=128, num_warps=4, num_stages=1)
        del primals_13
        buf15 = extern_kernels.convolution(buf14, buf4, stride=(1, 1),
            padding=(0, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf15, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf16 = extern_kernels.convolution(buf14, buf5, stride=(1, 1),
            padding=(1, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf16, (4, 384, 4, 4), (6144, 1, 1536, 384))
        buf17 = empty_strided_cuda((4, 4, 4, 4), (64, 1, 16, 4), torch.float32)
        triton_poi_fused_avg_pool2d_5[grid(256)](buf0, buf17, 256, XBLOCK=
            256, num_warps=4, num_stages=1)
        buf18 = extern_kernels.convolution(buf17, primals_18, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 192, 4, 4), (3072, 1, 768, 192))
        buf19 = empty_strided_cuda((4, 2048, 4, 4), (32768, 16, 4, 1),
            torch.float32)
        triton_poi_fused_cat_6[grid(131072)](buf6, primals_2, buf9,
            primals_7, buf10, primals_9, buf15, primals_15, buf16,
            primals_17, buf18, primals_19, buf19, 131072, XBLOCK=512,
            num_warps=8, num_stages=1)
        buf20 = empty_strided_cuda((4, 192, 4, 4), (3072, 1, 768, 192),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_7[grid(12288)](
            buf18, primals_19, buf20, 12288, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf18
        del primals_19
        buf21 = empty_strided_cuda((4, 384, 4, 4), (6144, 1, 1536, 384),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_8[grid(24576)](
            buf16, primals_17, buf21, 24576, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf16
        del primals_17
        buf22 = empty_strided_cuda((4, 384, 4, 4), (6144, 1, 1536, 384),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_8[grid(24576)](
            buf15, primals_15, buf22, 24576, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf15
        del primals_15
        buf23 = empty_strided_cuda((4, 384, 4, 4), (6144, 1, 1536, 384),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_8[grid(24576)](
            buf10, primals_9, buf23, 24576, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf10
        del primals_9
        buf24 = empty_strided_cuda((4, 384, 4, 4), (6144, 1, 1536, 384),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_8[grid(24576)](
            buf9, primals_7, buf24, 24576, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf9
        del primals_7
        buf25 = empty_strided_cuda((4, 320, 4, 4), (5120, 1, 1280, 320),
            torch.bool)
        triton_poi_fused_convolution_relu_threshold_backward_9[grid(20480)](
            buf6, primals_2, buf25, 20480, XBLOCK=256, num_warps=4,
            num_stages=1)
        del buf6
        del primals_2
    return (buf19, primals_1, buf0, primals_4, buf1, buf2, primals_10, buf3,
        buf4, buf5, primals_18, buf8, buf12, buf14, buf17, buf20, buf21,
        buf22, buf23, buf24, buf25)


class Conv2d(nn.Module):

    def __init__(self, in_channels, out_channels, kernel_size, batch_norm=
        False, **kwargs):
        super(Conv2d, self).__init__()
        self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, **kwargs)
        self.relu = nn.ReLU(inplace=True)
        self.batch_norm = batch_norm
        if self.batch_norm:
            self.bn = nn.BatchNorm2d(out_channels, eps=0.001)

    def forward(self, x):
        x = self.conv(x)
        if self.batch_norm:
            x = self.bn(x)
        x = self.relu(x)
        return x


class InceptionCNew(nn.Module):

    def __init__(self, in_channels):
        super(InceptionCNew, self).__init__()
        self.branch1x1 = Conv2d(in_channels, 320, 1)
        self.branch3x3_1 = Conv2d(in_channels, 384, 1)
        self.branch3x3_2a = Conv2d(384, 384, (1, 3), padding=(0, 1))
        self.branch3x3_2b = Conv2d(384, 384, (3, 1), padding=(1, 0))
        self.branch3x3dbl_1 = Conv2d(in_channels, 448, 1)
        self.branch3x3dbl_2 = Conv2d(448, 384, 3, padding=1)
        self.branch3x3dbl_3a = Conv2d(384, 384, (1, 3), padding=(0, 1))
        self.branch3x3dbl_3b = Conv2d(384, 384, (3, 1), padding=(1, 0))
        self.branch_pool = Conv2d(in_channels, 192, 1)

    def forward(self, input_0):
        primals_1 = self.branch1x1.conv.weight
        primals_2 = self.branch1x1.conv.bias
        primals_4 = self.branch3x3_1.conv.weight
        primals_5 = self.branch3x3_1.conv.bias
        primals_6 = self.branch3x3_2a.conv.weight
        primals_7 = self.branch3x3_2a.conv.bias
        primals_8 = self.branch3x3_2b.conv.weight
        primals_9 = self.branch3x3_2b.conv.bias
        primals_10 = self.branch3x3dbl_1.conv.weight
        primals_11 = self.branch3x3dbl_1.conv.bias
        primals_12 = self.branch3x3dbl_2.conv.weight
        primals_13 = self.branch3x3dbl_2.conv.bias
        primals_14 = self.branch3x3dbl_3a.conv.weight
        primals_15 = self.branch3x3dbl_3a.conv.bias
        primals_16 = self.branch3x3dbl_3b.conv.weight
        primals_17 = self.branch3x3dbl_3b.conv.bias
        primals_18 = self.branch_pool.conv.weight
        primals_19 = self.branch_pool.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])
        return output[0]


Measured latency_ms: 0.013746