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._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
from collections import OrderedDict
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__prelu_kernel_convolution_0(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 153760
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 3844 % 10
    x0 = xindex % 3844
    x4 = xindex // 3844
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + (x0 + 3872 * x4), tmp7, xmask)


@triton.jit
def triton_poi_fused_max_pool2d_with_indices_1(in_ptr0, out_ptr0, out_ptr1,
    xnumel, XBLOCK: tl.constexpr):
    xnumel = 38440
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 31
    x1 = xindex // 31 % 31
    x4 = xindex // 961
    x3 = xindex // 9610
    x5 = xindex % 9610
    tmp0 = tl.load(in_ptr0 + (2 * x0 + 124 * x1 + 3872 * x4), xmask,
        eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (1 + 2 * x0 + 124 * x1 + 3872 * x4), xmask,
        eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr0 + (62 + 2 * x0 + 124 * x1 + 3872 * x4), xmask,
        eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr0 + (63 + 2 * x0 + 124 * x1 + 3872 * x4), xmask,
        eviction_policy='evict_last')
    tmp2 = triton_helpers.maximum(tmp1, tmp0)
    tmp4 = triton_helpers.maximum(tmp3, tmp2)
    tmp6 = triton_helpers.maximum(tmp5, tmp4)
    tmp7 = tmp1 > tmp0
    tmp8 = tl.full([1], 1, tl.int8)
    tmp9 = tl.full([1], 0, tl.int8)
    tmp10 = tl.where(tmp7, tmp8, tmp9)
    tmp11 = tmp3 > tmp2
    tmp12 = tl.full([1], 2, tl.int8)
    tmp13 = tl.where(tmp11, tmp12, tmp10)
    tmp14 = tmp5 > tmp4
    tmp15 = tl.full([1], 3, tl.int8)
    tmp16 = tl.where(tmp14, tmp15, tmp13)
    tl.store(out_ptr0 + (x5 + 9632 * x3), tmp6, xmask)
    tl.store(out_ptr1 + (x5 + 9728 * x3), tmp16, xmask)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_2(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 53824
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 841 % 16
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + x3, tmp7, xmask)


@triton.jit
def triton_poi_fused__prelu_kernel_convolution_3(in_out_ptr0, in_ptr0,
    in_ptr1, out_ptr0, xnumel, XBLOCK: tl.constexpr):
    xnumel = 93312
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 729 % 32
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp3 = 0.0
    tmp4 = tmp2 > tmp3
    tmp6 = tmp5 * tmp2
    tmp7 = tl.where(tmp4, tmp2, tmp6)
    tl.store(in_out_ptr0 + x3, tmp2, xmask)
    tl.store(out_ptr0 + x3, tmp7, xmask)


@triton.jit
def triton_poi_fused_convolution_4(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 11664
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 729 % 4
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)


@triton.jit
def triton_poi_fused__softmax_convolution_5(in_ptr0, in_ptr1, out_ptr0,
    xnumel, XBLOCK: tl.constexpr):
    xnumel = 5832
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 729 % 2
    x0 = xindex % 729
    x2 = xindex // 1458
    x4 = xindex % 1458
    tmp0 = tl.load(in_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr1 + x1, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr0 + (x0 + 1458 * x2), xmask, eviction_policy=
        'evict_last')
    tmp4 = tl.load(in_ptr1 + 0)
    tmp5 = tl.broadcast_to(tmp4, [XBLOCK])
    tmp7 = tl.load(in_ptr0 + (729 + x0 + 1458 * x2), xmask, eviction_policy
        ='evict_last')
    tmp8 = tl.load(in_ptr1 + 1)
    tmp9 = tl.broadcast_to(tmp8, [XBLOCK])
    tmp2 = tmp0 + tmp1
    tmp6 = tmp3 + tmp5
    tmp10 = tmp7 + tmp9
    tmp11 = triton_helpers.maximum(tmp6, tmp10)
    tmp12 = tmp2 - tmp11
    tmp13 = tl_math.exp(tmp12)
    tl.store(out_ptr0 + (x4 + 1472 * x2), tmp13, xmask)


@triton.jit
def triton_poi_fused__softmax_6(in_ptr0, out_ptr0, xnumel, XBLOCK: tl.constexpr
    ):
    xnumel = 5832
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex // 1458
    x3 = xindex % 1458
    x0 = xindex % 729
    x4 = xindex
    tmp0 = tl.load(in_ptr0 + (x3 + 1472 * x2), xmask)
    tmp1 = tl.load(in_ptr0 + (x0 + 1472 * x2), xmask, eviction_policy=
        'evict_last')
    tmp2 = tl.load(in_ptr0 + (729 + x0 + 1472 * x2), xmask, eviction_policy
        ='evict_last')
    tmp3 = tmp1 + tmp2
    tmp4 = tmp0 / tmp3
    tl.store(out_ptr0 + x4, tmp4, xmask)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9, primals_10, primals_11, primals_12,
        primals_13, primals_14) = args
    args.clear()
    assert_size_stride(primals_1, (10, 3, 3, 3), (27, 9, 3, 1))
    assert_size_stride(primals_2, (10,), (1,))
    assert_size_stride(primals_3, (4, 3, 64, 64), (12288, 4096, 64, 1))
    assert_size_stride(primals_4, (10,), (1,))
    assert_size_stride(primals_5, (16, 10, 3, 3), (90, 9, 3, 1))
    assert_size_stride(primals_6, (16,), (1,))
    assert_size_stride(primals_7, (16,), (1,))
    assert_size_stride(primals_8, (32, 16, 3, 3), (144, 9, 3, 1))
    assert_size_stride(primals_9, (32,), (1,))
    assert_size_stride(primals_10, (32,), (1,))
    assert_size_stride(primals_11, (2, 32, 1, 1), (32, 1, 1, 1))
    assert_size_stride(primals_12, (2,), (1,))
    assert_size_stride(primals_13, (4, 32, 1, 1), (32, 1, 1, 1))
    assert_size_stride(primals_14, (4,), (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, 10, 62, 62), (38440, 3844, 62, 1))
        buf1 = buf0
        del buf0
        buf2 = empty_strided_cuda((4, 10, 62, 62), (38720, 3872, 62, 1),
            torch.float32)
        get_raw_stream(0)
        triton_poi_fused__prelu_kernel_convolution_0[grid(153760)](buf1,
            primals_2, primals_4, buf2, 153760, XBLOCK=512, num_warps=8,
            num_stages=1)
        del primals_2
        buf3 = empty_strided_cuda((4, 10, 31, 31), (9632, 961, 31, 1),
            torch.float32)
        buf4 = empty_strided_cuda((4, 10, 31, 31), (9728, 961, 31, 1),
            torch.int8)
        triton_poi_fused_max_pool2d_with_indices_1[grid(38440)](buf2, buf3,
            buf4, 38440, XBLOCK=512, num_warps=4, num_stages=1)
        buf5 = extern_kernels.convolution(buf3, primals_5, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf5, (4, 16, 29, 29), (13456, 841, 29, 1))
        buf6 = buf5
        del buf5
        buf7 = empty_strided_cuda((4, 16, 29, 29), (13456, 841, 29, 1),
            torch.float32)
        triton_poi_fused__prelu_kernel_convolution_2[grid(53824)](buf6,
            primals_6, primals_7, buf7, 53824, XBLOCK=512, num_warps=4,
            num_stages=1)
        del primals_6
        buf8 = extern_kernels.convolution(buf7, primals_8, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf8, (4, 32, 27, 27), (23328, 729, 27, 1))
        buf9 = buf8
        del buf8
        buf10 = empty_strided_cuda((4, 32, 27, 27), (23328, 729, 27, 1),
            torch.float32)
        triton_poi_fused__prelu_kernel_convolution_3[grid(93312)](buf9,
            primals_9, primals_10, buf10, 93312, XBLOCK=512, num_warps=8,
            num_stages=1)
        del primals_9
        buf11 = extern_kernels.convolution(buf10, primals_11, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf11, (4, 2, 27, 27), (1458, 729, 27, 1))
        buf12 = extern_kernels.convolution(buf10, primals_13, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf12, (4, 4, 27, 27), (2916, 729, 27, 1))
        buf13 = buf12
        del buf12
        triton_poi_fused_convolution_4[grid(11664)](buf13, primals_14, 
            11664, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_14
        buf14 = empty_strided_cuda((4, 2, 27, 27), (1472, 729, 27, 1),
            torch.float32)
        triton_poi_fused__softmax_convolution_5[grid(5832)](buf11,
            primals_12, buf14, 5832, XBLOCK=256, num_warps=4, num_stages=1)
        del primals_12
        buf15 = buf11
        del buf11
        triton_poi_fused__softmax_6[grid(5832)](buf14, buf15, 5832, XBLOCK=
            128, num_warps=4, num_stages=1)
        del buf14
    return (buf13, buf15, primals_1, primals_3, primals_4, primals_5,
        primals_7, primals_8, primals_10, primals_11, primals_13, buf1,
        buf2, buf3, buf4, buf6, buf7, buf9, buf10, buf15)


class PNetNew(nn.Module):

    def __init__(self):
        super(PNetNew, self).__init__()
        self.features = nn.Sequential(OrderedDict([('conv1', nn.Conv2d(3, 
            10, 3, 1)), ('prelu1', nn.PReLU(10)), ('pool1', nn.MaxPool2d(2,
            2, ceil_mode=True)), ('conv2', nn.Conv2d(10, 16, 3, 1)), (
            'prelu2', nn.PReLU(16)), ('conv3', nn.Conv2d(16, 32, 3, 1)), (
            'prelu3', nn.PReLU(32))]))
        self.conv4_1 = nn.Conv2d(32, 2, 1, 1)
        self.conv4_2 = nn.Conv2d(32, 4, 1, 1)

    def forward(self, input_0):
        primals_1 = self.features.conv1.weight
        primals_2 = self.features.conv1.bias
        primals_4 = self.features.prelu1.weight
        primals_5 = self.features.conv2.weight
        primals_6 = self.features.conv2.bias
        primals_7 = self.features.prelu2.weight
        primals_8 = self.features.conv3.weight
        primals_9 = self.features.conv3.bias
        primals_10 = self.features.prelu3.weight
        primals_11 = self.conv4_1.weight
        primals_12 = self.conv4_1.bias
        primals_13 = self.conv4_2.weight
        primals_14 = self.conv4_2.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])
        return output[0], output[1]


Measured latency_ms: 0.015431