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
from torch._inductor.runtime.triton_helpers import math as tl_math
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__softmax_0(in_ptr0, out_ptr0, xnumel, XBLOCK: tl.constexpr
    ):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x1 = xindex // 4
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr0 + 4 * x1, xmask, eviction_policy='evict_last')
    tmp2 = tl.load(in_ptr0 + (1 + 4 * x1), xmask, eviction_policy='evict_last')
    tmp4 = tl.load(in_ptr0 + (2 + 4 * x1), xmask, eviction_policy='evict_last')
    tmp6 = tl.load(in_ptr0 + (3 + 4 * x1), xmask, eviction_policy='evict_last')
    tmp3 = triton_helpers.maximum(tmp1, tmp2)
    tmp5 = triton_helpers.maximum(tmp3, tmp4)
    tmp7 = triton_helpers.maximum(tmp5, tmp6)
    tmp8 = tmp0 - tmp7
    tmp9 = tl_math.exp(tmp8)
    tl.store(out_ptr0 + x2, tmp9, xmask)


@triton.jit
def triton_poi_fused__softmax_argmax_1(in_ptr0, out_ptr0, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 64
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 4
    x1 = xindex // 4
    x2 = xindex
    tmp0 = tl.load(in_ptr0 + (x0 + 16 * x1), xmask)
    tmp1 = tl.load(in_ptr0 + 16 * x1, xmask, eviction_policy='evict_last')
    tmp2 = tl.load(in_ptr0 + (1 + 16 * x1), xmask, eviction_policy='evict_last'
        )
    tmp4 = tl.load(in_ptr0 + (2 + 16 * x1), xmask, eviction_policy='evict_last'
        )
    tmp6 = tl.load(in_ptr0 + (3 + 16 * x1), xmask, eviction_policy='evict_last'
        )
    tmp9 = tl.load(in_ptr0 + (4 + x0 + 16 * x1), xmask)
    tmp10 = tl.load(in_ptr0 + (4 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp11 = tl.load(in_ptr0 + (5 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp13 = tl.load(in_ptr0 + (6 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp15 = tl.load(in_ptr0 + (7 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp33 = tl.load(in_ptr0 + (8 + x0 + 16 * x1), xmask)
    tmp34 = tl.load(in_ptr0 + (8 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp35 = tl.load(in_ptr0 + (9 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp37 = tl.load(in_ptr0 + (10 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp39 = tl.load(in_ptr0 + (11 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp56 = tl.load(in_ptr0 + (12 + x0 + 16 * x1), xmask)
    tmp57 = tl.load(in_ptr0 + (12 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp58 = tl.load(in_ptr0 + (13 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp60 = tl.load(in_ptr0 + (14 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp62 = tl.load(in_ptr0 + (15 + 16 * x1), xmask, eviction_policy=
        'evict_last')
    tmp3 = tmp1 + tmp2
    tmp5 = tmp3 + tmp4
    tmp7 = tmp5 + tmp6
    tmp8 = tmp0 / tmp7
    tmp12 = tmp10 + tmp11
    tmp14 = tmp12 + tmp13
    tmp16 = tmp14 + tmp15
    tmp17 = tmp9 / tmp16
    tmp18 = tmp8 > tmp17
    tmp19 = tmp8 == tmp17
    tmp20 = tmp8 != tmp8
    tmp21 = tmp17 != tmp17
    tmp22 = tmp20 > tmp21
    tmp23 = tmp18 | tmp22
    tmp24 = tmp20 & tmp21
    tmp25 = tmp19 | tmp24
    tmp26 = tl.full([1], 0, tl.int64)
    tmp27 = tl.full([1], 1, tl.int64)
    tmp28 = tmp26 < tmp27
    tmp29 = tmp25 & tmp28
    tmp30 = tmp23 | tmp29
    tmp31 = tl.where(tmp30, tmp8, tmp17)
    tmp32 = tl.where(tmp30, tmp26, tmp27)
    tmp36 = tmp34 + tmp35
    tmp38 = tmp36 + tmp37
    tmp40 = tmp38 + tmp39
    tmp41 = tmp33 / tmp40
    tmp42 = tmp31 > tmp41
    tmp43 = tmp31 == tmp41
    tmp44 = tmp31 != tmp31
    tmp45 = tmp41 != tmp41
    tmp46 = tmp44 > tmp45
    tmp47 = tmp42 | tmp46
    tmp48 = tmp44 & tmp45
    tmp49 = tmp43 | tmp48
    tmp50 = tl.full([1], 2, tl.int64)
    tmp51 = tmp32 < tmp50
    tmp52 = tmp49 & tmp51
    tmp53 = tmp47 | tmp52
    tmp54 = tl.where(tmp53, tmp31, tmp41)
    tmp55 = tl.where(tmp53, tmp32, tmp50)
    tmp59 = tmp57 + tmp58
    tmp61 = tmp59 + tmp60
    tmp63 = tmp61 + tmp62
    tmp64 = tmp56 / tmp63
    tmp65 = tmp54 > tmp64
    tmp66 = tmp54 == tmp64
    tmp67 = tmp54 != tmp54
    tmp68 = tmp64 != tmp64
    tmp69 = tmp67 > tmp68
    tmp70 = tmp65 | tmp69
    tmp71 = tmp67 & tmp68
    tmp72 = tmp66 | tmp71
    tmp73 = tl.full([1], 3, tl.int64)
    tmp74 = tmp55 < tmp73
    tmp75 = tmp72 & tmp74
    tmp76 = tmp70 | tmp75
    tl.where(tmp76, tmp54, tmp64)
    tmp78 = tl.where(tmp76, tmp55, tmp73)
    tl.store(out_ptr0 + x2, tmp78, xmask)


@triton.jit
def triton_per_fused_div_eq_sum_2(in_ptr0, in_ptr1, out_ptr1, xnumel, rnumel):
    XBLOCK: tl.constexpr = 1
    RBLOCK: tl.constexpr = 256
    xoffset = tl.program_id(0) * XBLOCK
    tl.full([1], xoffset, tl.int32)
    tl.full([RBLOCK], True, tl.int1)
    rindex = tl.arange(0, RBLOCK)[:]
    tl.full([RBLOCK], True, tl.int1)
    r0 = rindex % 64
    r2 = rindex
    tmp0 = tl.load(in_ptr0 + r0, None, eviction_policy='evict_last')
    tmp2 = tl.load(in_ptr1 + r2, None)
    tmp1 = tmp0.to(tl.float32)
    tmp3 = tmp1 == tmp2
    tmp4 = tmp3.to(tl.int64)
    tmp5 = tl.broadcast_to(tmp4, [RBLOCK])
    tmp7 = triton_helpers.promote_to_tensor(tl.sum(tmp5, 0))
    tmp8 = tmp7.to(tl.float32)
    tmp9 = 0.00390625
    tmp10 = tmp8 * tmp9
    tl.store(out_ptr1 + tl.full([1], 0, tl.int32), tmp10, None)


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, 4, 4), (64, 16, 4, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused__softmax_0[grid(256)](arg0_1, buf0, 256, XBLOCK=
            256, num_warps=4, num_stages=1)
        del arg0_1
        buf1 = empty_strided_cuda((4, 4, 4), (16, 4, 1), torch.int64)
        triton_poi_fused__softmax_argmax_1[grid(64)](buf0, buf1, 64, XBLOCK
            =64, num_warps=1, num_stages=1)
        del buf0
        buf3 = empty_strided_cuda((), (), torch.float32)
        triton_per_fused_div_eq_sum_2[grid(1)](buf1, arg1_1, buf3, 1, 256,
            num_warps=2, num_stages=1)
        del arg1_1
        del buf1
    return buf3,


class AccuracyNew(nn.Module):

    def __init__(self):
        super().__init__()

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


Measured latency_ms: 0.038989