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
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_avg_pool2d_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 + 2 * 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 + 2 * x0
    tmp7 = tmp6 >= tmp1
    tmp8 = tmp6 < tmp3
    tmp9 = tmp7 & tmp8
    tmp10 = tmp5 & tmp9
    tmp11 = tl.load(in_ptr0 + (-5 + 2 * x0 + 8 * x1 + 16 * x2), tmp10 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp12 = 2 * x0
    tmp13 = tmp12 >= tmp1
    tmp14 = tmp12 < tmp3
    tmp15 = tmp13 & tmp14
    tmp16 = tmp5 & tmp15
    tmp17 = tl.load(in_ptr0 + (-4 + 2 * x0 + 8 * x1 + 16 * x2), tmp16 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp18 = tmp17 + tmp11
    tmp19 = 2 * x1
    tmp20 = tmp19 >= tmp1
    tmp21 = tmp19 < tmp3
    tmp22 = tmp20 & tmp21
    tmp23 = tmp22 & tmp9
    tmp24 = tl.load(in_ptr0 + (-1 + 2 * x0 + 8 * x1 + 16 * x2), tmp23 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp25 = tmp24 + tmp18
    tmp26 = tmp22 & tmp15
    tmp27 = tl.load(in_ptr0 + (2 * x0 + 8 * x1 + 16 * x2), tmp26 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp28 = tmp27 + tmp25
    tmp29 = 1 + -2 * x0 + -2 * x1 + (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) *
        (1 + 2 * x0 < 5)) * (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 *
        x1 < 5)) + -2 * x0 * (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 *
        x1 < 5)) + -2 * x1 * (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) * (1 + 2 *
        x0 < 5)) + 4 * x0 * x1 + (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) * (1 +
        2 * x0 < 5)) + (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 * x1 < 5)
        )
    tmp30 = tmp28 / tmp29
    tl.store(out_ptr0 + x4, tmp30, xmask)


@triton.jit
def triton_poi_fused_avg_pool2d_div_1(in_out_ptr0, in_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
    x3 = xindex
    tmp0 = -1 + 2 * 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 + 2 * x0
    tmp7 = tmp6 >= tmp1
    tmp8 = tmp6 < tmp3
    tmp9 = tmp7 & tmp8
    tmp10 = tmp5 & tmp9
    tmp11 = tl.load(in_ptr0 + (-5 + 2 * x0 + 8 * x1 + 16 * x2), tmp10 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp12 = 2 * x0
    tmp13 = tmp12 >= tmp1
    tmp14 = tmp12 < tmp3
    tmp15 = tmp13 & tmp14
    tmp16 = tmp5 & tmp15
    tmp17 = tl.load(in_ptr0 + (-4 + 2 * x0 + 8 * x1 + 16 * x2), tmp16 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp18 = tmp17 + tmp11
    tmp19 = 2 * x1
    tmp20 = tmp19 >= tmp1
    tmp21 = tmp19 < tmp3
    tmp22 = tmp20 & tmp21
    tmp23 = tmp22 & tmp9
    tmp24 = tl.load(in_ptr0 + (-1 + 2 * x0 + 8 * x1 + 16 * x2), tmp23 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp25 = tmp24 + tmp18
    tmp26 = tmp22 & tmp15
    tmp27 = tl.load(in_ptr0 + (2 * x0 + 8 * x1 + 16 * x2), tmp26 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp28 = tmp27 + tmp25
    tmp29 = 1 + -2 * x0 + -2 * x1 + (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) *
        (1 + 2 * x0 < 5)) * (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 *
        x1 < 5)) + -2 * x0 * (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 *
        x1 < 5)) + -2 * x1 * (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) * (1 + 2 *
        x0 < 5)) + 4 * x0 * x1 + (5 * (5 <= 1 + 2 * x0) + (1 + 2 * x0) * (1 +
        2 * x0 < 5)) + (5 * (5 <= 1 + 2 * x1) + (1 + 2 * x1) * (1 + 2 * x1 < 5)
        )
    tmp30 = tmp28 / tmp29
    tmp31 = 0.0625
    tmp32 = tmp30 * tmp31
    tmp33 = tmp32 * tmp31
    tl.store(in_out_ptr0 + x3, tmp33, xmask)


def call(args):
    arg0_1, arg1_1 = args
    args.clear()
    assert_size_stride(arg0_1, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(arg1_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_avg_pool2d_0[grid(144)](arg0_1, buf0, 144, XBLOCK=
            128, num_warps=4, num_stages=1)
        del arg0_1
        buf1 = empty_strided_cuda((4, 4, 3, 3), (36, 9, 3, 1), torch.float32)
        buf2 = buf1
        del buf1
        triton_poi_fused_avg_pool2d_div_1[grid(144)](buf2, arg1_1, 144,
            XBLOCK=128, num_warps=4, num_stages=1)
        del arg1_1
    return buf0, buf2


def keep_variance_fn(x):
    return x + 0.001


class AvgPool2dNew(nn.Module):

    def __init__(self, keep_variance_fn=None, kernel_size=2):
        super(AvgPool2dNew, self).__init__()
        self._keep_variance_fn = keep_variance_fn
        self.kernel_size = kernel_size

    def forward(self, input_0, input_1):
        arg0_1 = input_0
        arg1_1 = input_1
        output = call([arg0_1, arg1_1])
        return output[0], output[1]


Measured latency_ms: 0.016622