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
from torch import nn
from torch.nn import functional as F
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_convolution_0(in_out_ptr0, in_out_ptr1, in_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xnumel = 492032
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 3844 % 32
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_out_ptr1 + x3, xmask)
    tmp2 = tmp0 + tmp1
    tmp4 = tmp3 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(in_out_ptr1 + x3, tmp4, xmask)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_relu_1(in_ptr0, out_ptr0,
    out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xnumel = 123008
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 31
    x3 = xindex // 31
    x2 = xindex // 30752
    x4 = xindex % 30752
    x5 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 124 * x3), xmask, eviction_policy=
        'evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 124 * x3), xmask,
        eviction_policy='evict_last')
    tmp7 = tl.load(in_ptr0 + (62 + 2 * x0 + 124 * x3), xmask,
        eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr0 + (63 + 2 * x0 + 124 * x3), xmask,
        eviction_policy='evict_last')
    tmp2 = tmp1 > tmp0
    tmp3 = tl.full([1], 1, tl.int8)
    tmp4 = tl.full([1], 0, tl.int8)
    tmp5 = tl.where(tmp2, tmp3, tmp4)
    tmp6 = triton_helpers.maximum(tmp1, tmp0)
    tmp8 = tmp7 > tmp6
    tmp9 = tl.full([1], 2, tl.int8)
    tmp10 = tl.where(tmp8, tmp9, tmp5)
    tmp11 = triton_helpers.maximum(tmp7, tmp6)
    tmp13 = tmp12 > tmp11
    tmp14 = tl.full([1], 3, tl.int8)
    tmp15 = tl.where(tmp13, tmp14, tmp10)
    tmp16 = triton_helpers.maximum(tmp12, tmp11)
    tmp17 = tl.full([1], 0, tl.int32)
    tmp18 = triton_helpers.maximum(tmp17, tmp16)
    tl.store(out_ptr0 + (x4 + 30848 * x2), tmp15, xmask)
    tl.store(out_ptr1 + x5, tmp18, xmask)


@triton.jit
def triton_poi_fused_convolution_2(in_out_ptr0, in_out_ptr1, in_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xnumel = 215296
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 841 % 64
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_out_ptr1 + x3, xmask)
    tmp2 = tmp0 + tmp1
    tmp4 = tmp3 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(in_out_ptr1 + x3, tmp4, xmask)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_relu_threshold_backward_3(in_ptr0,
    out_ptr0, out_ptr1, out_ptr2, xnumel, XBLOCK: tl.constexpr):
    xnumel = 50176
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 14
    x1 = xindex // 14 % 14
    x2 = xindex // 196
    x3 = xindex
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 58 * x1 + 841 * x2), xmask,
        eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 58 * x1 + 841 * x2), xmask,
        eviction_policy='evict_last')
    tmp7 = tl.load(in_ptr0 + (29 + 2 * x0 + 58 * x1 + 841 * x2), xmask,
        eviction_policy='evict_last')
    tmp12 = tl.load(in_ptr0 + (30 + 2 * x0 + 58 * x1 + 841 * x2), xmask,
        eviction_policy='evict_last')
    tmp2 = tmp1 > tmp0
    tmp3 = tl.full([1], 1, tl.int8)
    tmp4 = tl.full([1], 0, tl.int8)
    tmp5 = tl.where(tmp2, tmp3, tmp4)
    tmp6 = triton_helpers.maximum(tmp1, tmp0)
    tmp8 = tmp7 > tmp6
    tmp9 = tl.full([1], 2, tl.int8)
    tmp10 = tl.where(tmp8, tmp9, tmp5)
    tmp11 = triton_helpers.maximum(tmp7, tmp6)
    tmp13 = tmp12 > tmp11
    tmp14 = tl.full([1], 3, tl.int8)
    tmp15 = tl.where(tmp13, tmp14, tmp10)
    tmp16 = triton_helpers.maximum(tmp12, tmp11)
    tmp17 = tl.full([1], 0, tl.int32)
    tmp18 = triton_helpers.maximum(tmp17, tmp16)
    tmp19 = 0.0
    tmp20 = tmp18 <= tmp19
    tl.store(out_ptr0 + x3, tmp15, xmask)
    tl.store(out_ptr1 + x3, tmp18, xmask)
    tl.store(out_ptr2 + x3, tmp20, xmask)


@triton.jit
def triton_poi_fused_relu_4(in_out_ptr0, in_out_ptr1, in_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 39200
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 200
    tmp0 = tl.load(in_out_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr0 + x0, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_out_ptr1 + x2, xmask)
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = tmp5 + tmp1
    tmp7 = triton_helpers.maximum(tmp3, tmp6)
    tl.store(in_out_ptr0 + x2, tmp4, xmask)
    tl.store(in_out_ptr1 + x2, tmp7, xmask)


@triton.jit
def triton_poi_fused_cat_5(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 3920
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 20
    x1 = xindex // 20
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 10, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (10 * 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], 20, tl.int64)
    tmp15 = tl.load(in_ptr2 + (10 * x1 + (-10 + x0)), tmp12 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.load(in_ptr1 + (-10 + x0), tmp12 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp17 = tmp15 + tmp16
    tmp18 = triton_helpers.maximum(tmp8, tmp17)
    tmp19 = tl.full(tmp18.shape, 0.0, tmp18.dtype)
    tmp20 = tl.where(tmp12, tmp18, tmp19)
    tmp21 = tl.where(tmp4, tmp11, tmp20)
    tl.store(out_ptr0 + x2, tmp21, xmask)


@triton.jit
def triton_poi_fused_sigmoid_6(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl.
    constexpr):
    xnumel = 392
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 2
    tmp0 = tl.load(in_out_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr0 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = tl.sigmoid(tmp2)
    tl.store(in_out_ptr0 + x2, tmp3, xmask)


@triton.jit
def triton_poi_fused_relu_threshold_backward_7(in_ptr0, in_ptr1, in_ptr2,
    out_ptr0, out_ptr1, xnumel, XBLOCK: tl.constexpr):
    xnumel = 1960
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 10
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp7 = tl.load(in_ptr2 + x2, xmask)
    tmp2 = tmp0 + tmp1
    tmp3 = tl.full([1], 0, tl.int32)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp5 = 0.0
    tmp6 = tmp4 <= tmp5
    tmp8 = tmp7 + tmp1
    tmp9 = triton_helpers.maximum(tmp3, tmp8)
    tmp10 = tmp9 <= tmp5
    tl.store(out_ptr0 + x2, tmp6, xmask)
    tl.store(out_ptr1 + x2, tmp10, 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
        ) = args
    args.clear()
    assert_size_stride(primals_1, (32, 1, 3, 3), (9, 9, 3, 1))
    assert_size_stride(primals_2, (32,), (1,))
    assert_size_stride(primals_3, (4, 1, 64, 64), (4096, 4096, 64, 1))
    assert_size_stride(primals_4, (64, 32, 3, 3), (288, 9, 3, 1))
    assert_size_stride(primals_5, (64,), (1,))
    assert_size_stride(primals_6, (200, 256), (256, 1))
    assert_size_stride(primals_7, (200,), (1,))
    assert_size_stride(primals_8, (10, 200), (200, 1))
    assert_size_stride(primals_9, (10,), (1,))
    assert_size_stride(primals_10, (4, 1, 64, 64), (4096, 4096, 64, 1))
    assert_size_stride(primals_11, (2, 20), (20, 1))
    assert_size_stride(primals_12, (2,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = extern_kernels.convolution(primals_3, primals_1, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf0, (4, 32, 62, 62), (123008, 3844, 62, 1))
        buf11 = extern_kernels.convolution(primals_10, primals_1, stride=(1,
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf11, (4, 32, 62, 62), (123008, 3844, 62, 1))
        buf1 = buf0
        del buf0
        buf12 = buf11
        del buf11
        get_raw_stream(0)
        triton_poi_fused_convolution_0[grid(492032)](buf1, buf12, primals_2,
            492032, XBLOCK=1024, num_warps=4, num_stages=1)
        del primals_2
        buf2 = empty_strided_cuda((4, 32, 31, 31), (30848, 961, 31, 1),
            torch.int8)
        buf3 = empty_strided_cuda((4, 32, 31, 31), (30752, 961, 31, 1),
            torch.float32)
        triton_poi_fused_max_pool2d_with_indices_relu_1[grid(123008)](buf1,
            buf2, buf3, 123008, XBLOCK=512, num_warps=8, num_stages=1)
        buf4 = extern_kernels.convolution(buf3, primals_4, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf4, (4, 64, 29, 29), (53824, 841, 29, 1))
        buf13 = empty_strided_cuda((4, 32, 31, 31), (30848, 961, 31, 1),
            torch.int8)
        buf14 = empty_strided_cuda((4, 32, 31, 31), (30752, 961, 31, 1),
            torch.float32)
        triton_poi_fused_max_pool2d_with_indices_relu_1[grid(123008)](buf12,
            buf13, buf14, 123008, XBLOCK=512, num_warps=8, num_stages=1)
        buf15 = extern_kernels.convolution(buf14, primals_4, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf15, (4, 64, 29, 29), (53824, 841, 29, 1))
        buf5 = buf4
        del buf4
        buf16 = buf15
        del buf15
        triton_poi_fused_convolution_2[grid(215296)](buf5, buf16, primals_5,
            215296, XBLOCK=512, num_warps=8, num_stages=1)
        del primals_5
        buf6 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.int8)
        buf7 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.float32)
        buf28 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.bool)
        triton_poi_fused_max_pool2d_with_indices_relu_threshold_backward_3[grid
            (50176)](buf5, buf6, buf7, buf28, 50176, XBLOCK=512, num_warps=
            4, num_stages=1)
        buf8 = empty_strided_cuda((196, 200), (200, 1), torch.float32)
        extern_kernels.mm(reinterpret_tensor(buf7, (196, 256), (256, 1), 0),
            reinterpret_tensor(primals_6, (256, 200), (1, 256), 0), out=buf8)
        buf17 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.int8)
        buf18 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.float32)
        buf26 = empty_strided_cuda((4, 64, 14, 14), (12544, 196, 14, 1),
            torch.bool)
        triton_poi_fused_max_pool2d_with_indices_relu_threshold_backward_3[grid
            (50176)](buf16, buf17, buf18, buf26, 50176, XBLOCK=512,
            num_warps=4, num_stages=1)
        buf19 = empty_strided_cuda((196, 200), (200, 1), torch.float32)
        extern_kernels.mm(reinterpret_tensor(buf18, (196, 256), (256, 1), 0
            ), reinterpret_tensor(primals_6, (256, 200), (1, 256), 0), out=
            buf19)
        buf9 = buf8
        del buf8
        buf20 = buf19
        del buf19
        triton_poi_fused_relu_4[grid(39200)](buf9, buf20, primals_7, 39200,
            XBLOCK=512, num_warps=4, num_stages=1)
        del primals_7
        buf10 = empty_strided_cuda((196, 10), (10, 1), torch.float32)
        extern_kernels.mm(buf9, reinterpret_tensor(primals_8, (200, 10), (1,
            200), 0), out=buf10)
        buf21 = empty_strided_cuda((196, 10), (10, 1), torch.float32)
        extern_kernels.mm(buf20, reinterpret_tensor(primals_8, (200, 10), (
            1, 200), 0), out=buf21)
        buf22 = empty_strided_cuda((196, 20), (20, 1), torch.float32)
        triton_poi_fused_cat_5[grid(3920)](buf10, primals_9, buf21, buf22, 
            3920, XBLOCK=128, num_warps=4, num_stages=1)
        buf23 = empty_strided_cuda((196, 2), (2, 1), torch.float32)
        extern_kernels.mm(buf22, reinterpret_tensor(primals_11, (20, 2), (1,
            20), 0), out=buf23)
        buf24 = buf23
        del buf23
        triton_poi_fused_sigmoid_6[grid(392)](buf24, primals_12, 392,
            XBLOCK=128, num_warps=4, num_stages=1)
        del primals_12
        buf25 = empty_strided_cuda((196, 10), (10, 1), torch.bool)
        buf27 = empty_strided_cuda((196, 10), (10, 1), torch.bool)
        triton_poi_fused_relu_threshold_backward_7[grid(1960)](buf21,
            primals_9, buf10, buf25, buf27, 1960, XBLOCK=128, num_warps=4,
            num_stages=1)
        del buf10
        del buf21
        del primals_9
    return (buf24, primals_1, primals_3, primals_4, primals_10, buf1, buf2,
        buf3, buf5, buf6, reinterpret_tensor(buf7, (196, 256), (256, 1), 0),
        buf9, buf12, buf13, buf14, buf16, buf17, reinterpret_tensor(buf18,
        (196, 256), (256, 1), 0), buf20, buf22, buf24, primals_11, buf25,
        primals_8, primals_6, buf26, buf27, buf28)


class SiameseCNNNew(nn.Module):
    """
    basic structure similar to the CNN
    input is splited into two 1*14*14 images for separating training, share the same parameters
    """

    def __init__(self):
        super(SiameseCNNNew, self).__init__()
        self.conv1 = nn.Conv2d(1, 32, kernel_size=3)
        self.conv2 = nn.Conv2d(32, 64, kernel_size=3)
        self.fc1 = nn.Linear(256, 200)
        self.fc2 = nn.Linear(200, 10)
        self.fc3 = nn.Linear(20, 2)

    def convs(self, x):
        x = F.relu(F.max_pool2d(self.conv1(x), kernel_size=2))
        x = F.relu(F.max_pool2d(self.conv2(x), kernel_size=2))
        return x

    def forward(self, input_0, input_1):
        primals_1 = self.conv1.weight
        primals_2 = self.conv1.bias
        primals_4 = self.conv2.weight
        primals_5 = self.conv2.bias
        primals_6 = self.fc1.weight
        primals_7 = self.fc1.bias
        primals_8 = self.fc2.weight
        primals_9 = self.fc2.bias
        primals_11 = self.fc3.weight
        primals_12 = self.fc3.bias
        primals_3 = input_0
        primals_10 = input_1
        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])
        return output[0]


Measured latency_ms: 0.058409