import torch
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
import torch.optim
import torch.utils.data
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_max_pool2d_with_indices_0(in_ptr0, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 144
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 3 % 3
    x0 = xindex % 3
    x2 = xindex // 9
    x4 = xindex
    tmp0 = -1 + x1
    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 + x0
    tmp7 = tmp6 >= tmp1
    tmp8 = tmp6 < tmp3
    tmp9 = tmp7 & tmp8
    tmp10 = tmp5 & tmp9
    tmp11 = tl.load(in_ptr0 + (-5 + x0 + 4 * x1 + 16 * x2), tmp10 & xmask,
        other=float('-inf'))
    tmp12 = x0
    tmp13 = tmp12 >= tmp1
    tmp14 = tmp12 < tmp3
    tmp15 = tmp13 & tmp14
    tmp16 = tmp5 & tmp15
    tmp17 = tl.load(in_ptr0 + (-4 + x0 + 4 * x1 + 16 * x2), tmp16 & xmask,
        other=float('-inf'))
    tmp18 = triton_helpers.maximum(tmp17, tmp11)
    tmp19 = 1 + x0
    tmp20 = tmp19 >= tmp1
    tmp21 = tmp19 < tmp3
    tmp22 = tmp20 & tmp21
    tmp23 = tmp5 & tmp22
    tmp24 = tl.load(in_ptr0 + (-3 + x0 + 4 * x1 + 16 * x2), tmp23 & xmask,
        other=float('-inf'))
    tmp25 = triton_helpers.maximum(tmp24, tmp18)
    tmp26 = 2 + x0
    tmp27 = tmp26 >= tmp1
    tmp28 = tmp26 < tmp3
    tmp29 = tmp27 & tmp28
    tmp30 = tmp5 & tmp29
    tmp31 = tl.load(in_ptr0 + (-2 + x0 + 4 * x1 + 16 * x2), tmp30 & xmask,
        other=float('-inf'))
    tmp32 = triton_helpers.maximum(tmp31, tmp25)
    tmp33 = x1
    tmp34 = tmp33 >= tmp1
    tmp35 = tmp33 < tmp3
    tmp36 = tmp34 & tmp35
    tmp37 = tmp36 & tmp9
    tmp38 = tl.load(in_ptr0 + (-1 + x0 + 4 * x1 + 16 * x2), tmp37 & xmask,
        other=float('-inf'))
    tmp39 = triton_helpers.maximum(tmp38, tmp32)
    tmp40 = tmp36 & tmp15
    tmp41 = tl.load(in_ptr0 + (x0 + 4 * x1 + 16 * x2), tmp40 & xmask, other
        =float('-inf'))
    tmp42 = triton_helpers.maximum(tmp41, tmp39)
    tmp43 = tmp36 & tmp22
    tmp44 = tl.load(in_ptr0 + (1 + x0 + 4 * x1 + 16 * x2), tmp43 & xmask,
        other=float('-inf'))
    tmp45 = triton_helpers.maximum(tmp44, tmp42)
    tmp46 = tmp36 & tmp29
    tmp47 = tl.load(in_ptr0 + (2 + x0 + 4 * x1 + 16 * x2), tmp46 & xmask,
        other=float('-inf'))
    tmp48 = triton_helpers.maximum(tmp47, tmp45)
    tmp49 = 1 + x1
    tmp50 = tmp49 >= tmp1
    tmp51 = tmp49 < tmp3
    tmp52 = tmp50 & tmp51
    tmp53 = tmp52 & tmp9
    tmp54 = tl.load(in_ptr0 + (3 + x0 + 4 * x1 + 16 * x2), tmp53 & xmask,
        other=float('-inf'))
    tmp55 = triton_helpers.maximum(tmp54, tmp48)
    tmp56 = tmp52 & tmp15
    tmp57 = tl.load(in_ptr0 + (4 + x0 + 4 * x1 + 16 * x2), tmp56 & xmask,
        other=float('-inf'))
    tmp58 = triton_helpers.maximum(tmp57, tmp55)
    tmp59 = tmp52 & tmp22
    tmp60 = tl.load(in_ptr0 + (5 + x0 + 4 * x1 + 16 * x2), tmp59 & xmask,
        other=float('-inf'))
    tmp61 = triton_helpers.maximum(tmp60, tmp58)
    tmp62 = tmp52 & tmp29
    tmp63 = tl.load(in_ptr0 + (6 + x0 + 4 * x1 + 16 * x2), tmp62 & xmask,
        other=float('-inf'))
    tmp64 = triton_helpers.maximum(tmp63, tmp61)
    tmp65 = 2 + x1
    tmp66 = tmp65 >= tmp1
    tmp67 = tmp65 < tmp3
    tmp68 = tmp66 & tmp67
    tmp69 = tmp68 & tmp9
    tmp70 = tl.load(in_ptr0 + (7 + x0 + 4 * x1 + 16 * x2), tmp69 & xmask,
        other=float('-inf'))
    tmp71 = triton_helpers.maximum(tmp70, tmp64)
    tmp72 = tmp68 & tmp15
    tmp73 = tl.load(in_ptr0 + (8 + x0 + 4 * x1 + 16 * x2), tmp72 & xmask,
        other=float('-inf'))
    tmp74 = triton_helpers.maximum(tmp73, tmp71)
    tmp75 = tmp68 & tmp22
    tmp76 = tl.load(in_ptr0 + (9 + x0 + 4 * x1 + 16 * x2), tmp75 & xmask,
        other=float('-inf'))
    tmp77 = triton_helpers.maximum(tmp76, tmp74)
    tmp78 = tmp68 & tmp29
    tmp79 = tl.load(in_ptr0 + (10 + x0 + 4 * x1 + 16 * x2), tmp78 & xmask,
        other=float('-inf'))
    tmp80 = triton_helpers.maximum(tmp79, tmp77)
    tl.store(out_ptr0 + x4, tmp80, xmask)


def call(args):
    arg0_1, = args
    args.clear()
    assert_size_stride(arg0_1, (4, 4, 4, 4), (64, 16, 4, 1))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((4, 4, 3, 3), (36, 9, 3, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_max_pool2d_with_indices_0[grid(144)](arg0_1, buf0,
            144, XBLOCK=128, num_warps=4, num_stages=1)
        del arg0_1
    return buf0,


class MaxPoolNew(nn.Module):

    def __init__(self, kernel_size, stride=1, padding=1, zero_pad=False):
        super(MaxPoolNew, self).__init__()
        self.zero_pad = nn.ZeroPad2d((1, 0, 1, 0)) if zero_pad else None
        self.pool = nn.MaxPool2d(kernel_size, stride=stride, padding=padding)

    def forward(self, input_0):
        arg0_1 = input_0
        output = call([arg0_1])
        return output[0]


Measured latency_ms: 0.013978