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


@triton.jit
def triton_poi_fused_0(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 384
    xnumel = 9
    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 % 3
    y1 = yindex // 3
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask & ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 3 * x2 + 27 * y1), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused_1(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 12
    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 % 3
    y1 = yindex // 3
    tmp0 = tl.load(in_ptr0 + (x2 + 4096 * y3), ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 3 * x2 + 12288 * y1), tmp0, ymask)


@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 % 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_3(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 65280
    xnumel = 9
    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 % 256
    y1 = yindex // 256
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask & ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 256 * x2 + 2304 * y1), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused_4(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 65025
    xnumel = 9
    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 % 255
    y1 = yindex // 255
    tmp0 = tl.load(in_ptr0 + (x2 + 9 * y3), xmask & ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (y0 + 255 * x2 + 2295 * y1), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused_convolution_5(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_add_convolution_6(in_out_ptr0, in_ptr0, in_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 % 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)
    tmp2 = tmp0 + tmp1
    tmp4 = tmp2 + tmp3
    tl.store(in_out_ptr0 + x2, tmp4, None)


@triton.jit
def triton_poi_fused__to_copy_add_arange_mul_7(out_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 32
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tmp0.to(tl.float32)
    tmp2 = 0.5
    tmp3 = tmp1 * tmp2
    tmp4 = tmp3.to(tl.int32)
    tl.store(out_ptr0 + x0, tmp4, xmask)


@triton.jit
def triton_poi_fused_cat_8(in_ptr0, in_ptr1, in_ptr2, in_ptr3, out_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    tl.full([XBLOCK], True, tl.int1)
    x0 = xindex % 256
    x2 = xindex // 8192 % 32
    x1 = xindex // 256 % 32
    x3 = xindex // 262144
    x5 = xindex // 256
    x6 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 128, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + x2, tmp4, eviction_policy='evict_last', other=0.0)
    tmp6 = tl.full([XBLOCK], 16, tl.int32)
    tmp7 = tmp5 + tmp6
    tmp8 = tmp5 < 0
    tmp9 = tl.where(tmp8, tmp7, tmp5)
    tmp10 = tl.load(in_ptr0 + x1, tmp4, eviction_policy='evict_last', other=0.0
        )
    tmp11 = tmp10 + tmp6
    tmp12 = tmp10 < 0
    tmp13 = tl.where(tmp12, tmp11, tmp10)
    tmp14 = tl.load(in_ptr1 + (128 * tmp13 + 2048 * tmp9 + 32768 * x3 + x0),
        tmp4, eviction_policy='evict_last', other=0.0)
    tmp15 = tl.load(in_ptr2 + x0, tmp4, eviction_policy='evict_last', other=0.0
        )
    tmp16 = tmp14 + tmp15
    tmp17 = tl.full(tmp16.shape, 0.0, tmp16.dtype)
    tmp18 = tl.where(tmp4, tmp16, tmp17)
    tmp19 = tmp0 >= tmp3
    tl.full([1], 256, tl.int64)
    tmp22 = tl.load(in_ptr3 + (128 * x5 + (-128 + x0)), tmp19,
        eviction_policy='evict_last', other=0.0)
    tmp23 = tl.where(tmp4, tmp18, tmp22)
    tl.store(out_ptr0 + x6, tmp23, None)


@triton.jit
def triton_poi_fused_convolution_9(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 % 255
    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_convolution_10(in_out_ptr0, in_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 261120
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 255
    tmp0 = tl.load(in_out_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr0 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x2, tmp2, xmask)


@triton.jit
def triton_poi_fused_convolution_11(in_ptr0, in_ptr1, out_ptr0, ynumel,
    xnumel, YBLOCK: tl.constexpr, XBLOCK: tl.constexpr):
    ynumel = 1020
    xnumel = 64
    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
    y0 = yindex % 255
    y1 = yindex // 255
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 255 * x2 + 16320 * y1), xmask & ymask,
        eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr1 + y0, ymask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(out_ptr0 + (x2 + 64 * y3), tmp2, xmask & ymask)


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) = args
    args.clear()
    assert_size_stride(primals_1, (128, 3, 3, 3), (27, 9, 3, 1))
    assert_size_stride(primals_2, (128,), (1,))
    assert_size_stride(primals_3, (4, 3, 64, 64), (12288, 4096, 64, 1))
    assert_size_stride(primals_4, (128, 128, 1, 1), (128, 1, 1, 1))
    assert_size_stride(primals_5, (128,), (1,))
    assert_size_stride(primals_6, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_7, (128,), (1,))
    assert_size_stride(primals_8, (128, 128, 3, 3), (1152, 9, 3, 1))
    assert_size_stride(primals_9, (128,), (1,))
    assert_size_stride(primals_10, (255, 256, 3, 3), (2304, 9, 3, 1))
    assert_size_stride(primals_11, (255,), (1,))
    assert_size_stride(primals_12, (255, 255, 3, 3), (2295, 9, 3, 1))
    assert_size_stride(primals_13, (255,), (1,))
    assert_size_stride(primals_14, (255, 255, 3, 3), (2295, 9, 3, 1))
    assert_size_stride(primals_15, (255,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((128, 3, 3, 3), (27, 1, 9, 3), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_0[grid(384, 9)](primals_1, buf0, 384, 9, XBLOCK=16,
            YBLOCK=64, num_warps=4, num_stages=1)
        del primals_1
        buf1 = empty_strided_cuda((4, 3, 64, 64), (12288, 1, 192, 3), torch
            .float32)
        triton_poi_fused_1[grid(12, 4096)](primals_3, buf1, 12, 4096,
            XBLOCK=64, YBLOCK=16, num_warps=4, num_stages=1)
        del primals_3
        buf2 = empty_strided_cuda((128, 128, 3, 3), (1152, 1, 384, 128),
            torch.float32)
        triton_poi_fused_2[grid(16384, 9)](primals_6, buf2, 16384, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_6
        buf3 = empty_strided_cuda((128, 128, 3, 3), (1152, 1, 384, 128),
            torch.float32)
        triton_poi_fused_2[grid(16384, 9)](primals_8, buf3, 16384, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_8
        buf4 = empty_strided_cuda((255, 256, 3, 3), (2304, 1, 768, 256),
            torch.float32)
        triton_poi_fused_3[grid(65280, 9)](primals_10, buf4, 65280, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_10
        buf5 = empty_strided_cuda((255, 255, 3, 3), (2295, 1, 765, 255),
            torch.float32)
        triton_poi_fused_4[grid(65025, 9)](primals_12, buf5, 65025, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_12
        buf6 = empty_strided_cuda((255, 255, 3, 3), (2295, 1, 765, 255),
            torch.float32)
        triton_poi_fused_4[grid(65025, 9)](primals_14, buf6, 65025, 9,
            XBLOCK=16, YBLOCK=64, num_warps=4, num_stages=1)
        del primals_14
        buf7 = extern_kernels.convolution(buf1, buf0, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf7, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf8 = buf7
        del buf7
        triton_poi_fused_convolution_5[grid(524288)](buf8, primals_2, 
            524288, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_2
        buf9 = extern_kernels.convolution(buf8, primals_4, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf9, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf10 = buf9
        del buf9
        triton_poi_fused_convolution_5[grid(524288)](buf10, primals_5, 
            524288, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_5
        buf11 = extern_kernels.convolution(buf10, buf2, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf11, (4, 128, 32, 32), (131072, 1, 4096, 128))
        buf12 = buf11
        del buf11
        triton_poi_fused_add_convolution_6[grid(524288)](buf12, primals_7,
            buf8, 524288, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_7
        buf13 = extern_kernels.convolution(buf12, buf3, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf13, (4, 128, 16, 16), (32768, 1, 2048, 128))
        buf14 = empty_strided_cuda((32,), (1,), torch.int64)
        triton_poi_fused__to_copy_add_arange_mul_7[grid(32)](buf14, 32,
            XBLOCK=32, num_warps=1, num_stages=1)
        buf15 = empty_strided_cuda((4, 256, 32, 32), (262144, 1, 8192, 256),
            torch.float32)
        triton_poi_fused_cat_8[grid(1048576)](buf14, buf13, primals_9, buf8,
            buf15, 1048576, XBLOCK=1024, num_warps=4, num_stages=1)
        del buf13
        del primals_9
        buf16 = extern_kernels.convolution(buf15, buf4, stride=(1, 1),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf16, (4, 255, 32, 32), (261120, 1, 8160, 255))
        buf17 = buf16
        del buf16
        triton_poi_fused_convolution_9[grid(1044480)](buf17, primals_11, 
            1044480, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_11
        buf18 = extern_kernels.convolution(buf17, buf5, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf18, (4, 255, 16, 16), (65280, 1, 4080, 255))
        buf19 = buf18
        del buf18
        triton_poi_fused_convolution_10[grid(261120)](buf19, primals_13, 
            261120, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_13
        buf20 = extern_kernels.convolution(buf19, buf6, stride=(2, 2),
            padding=(1, 1), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf20, (4, 255, 8, 8), (16320, 1, 2040, 255))
        buf21 = empty_strided_cuda((4, 255, 8, 8), (16320, 64, 8, 1), torch
            .float32)
        triton_poi_fused_convolution_11[grid(1020, 64)](buf20, primals_15,
            buf21, 1020, 64, XBLOCK=32, YBLOCK=32, num_warps=4, num_stages=1)
        del buf20
        del primals_15
    return (buf21, buf0, buf1, primals_4, buf2, buf3, buf4, buf5, buf6,
        buf8, buf10, buf12, buf14, buf15, buf17, buf19)


class toy_yolov3New(nn.Module):

    def __init__(self):
        super(toy_yolov3New, self).__init__()
        self.conv1 = nn.Conv2d(3, 128, kernel_size=3, stride=2, padding=1)
        self.conv2_1 = nn.Conv2d(128, 128, kernel_size=1, stride=1, padding=0)
        self.conv2_2 = nn.Conv2d(128, 128, kernel_size=3, stride=1, padding=1)
        self.conv3 = nn.Conv2d(128, 128, kernel_size=3, stride=2, padding=1)
        self.conv4 = nn.Conv2d(256, 255, kernel_size=3, stride=1, padding=1)
        self.conv5 = nn.Conv2d(255, 255, kernel_size=3, stride=2, padding=1)
        self.conv6 = nn.Conv2d(255, 255, kernel_size=3, stride=2, padding=1)

    def forward(self, input_0):
        primals_1 = self.conv1.weight
        primals_2 = self.conv1.bias
        primals_4 = self.conv2_1.weight
        primals_5 = self.conv2_1.bias
        primals_6 = self.conv2_2.weight
        primals_7 = self.conv2_2.bias
        primals_8 = self.conv3.weight
        primals_9 = self.conv3.bias
        primals_10 = self.conv4.weight
        primals_11 = self.conv4.bias
        primals_12 = self.conv5.weight
        primals_13 = self.conv5.bias
        primals_14 = self.conv6.weight
        primals_15 = self.conv6.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])
        return output[0]


Measured latency_ms: 0.012787