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
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__log_softmax_0(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
    x3 = xindex
    x0 = xindex % 4
    x2 = xindex // 16
    tmp0 = tl.load(in_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + (x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp2 = tl.load(in_ptr0 + (4 + x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp4 = tl.load(in_ptr0 + (8 + x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp6 = tl.load(in_ptr0 + (12 + x0 + 16 * x2), 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
    tl.store(out_ptr0 + x3, tmp8, xmask)


@triton.jit
def triton_poi_fused__log_softmax_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
    x3 = xindex
    x0 = xindex % 4
    x2 = xindex // 16
    tmp0 = tl.load(in_ptr0 + (64 + x3), xmask)
    tmp1 = tl.load(in_ptr0 + (64 + x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp2 = tl.load(in_ptr0 + (68 + x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp4 = tl.load(in_ptr0 + (72 + x0 + 16 * x2), xmask, eviction_policy=
        'evict_last')
    tmp6 = tl.load(in_ptr0 + (76 + x0 + 16 * x2), 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
    tl.store(out_ptr0 + x3, tmp8, xmask)


@triton.jit
def triton_per_fused__log_softmax_add_div_mul_neg_sum_2(in_out_ptr0,
    in_ptr0, in_ptr1, in_ptr2, xnumel, rnumel, XBLOCK: tl.constexpr):
    RBLOCK: tl.constexpr = 64
    xoffset = tl.program_id(0) * XBLOCK
    xoffset + tl.arange(0, XBLOCK)[:, None]
    tl.full([XBLOCK, RBLOCK], True, tl.int1)
    rindex = tl.arange(0, RBLOCK)[None, :]
    tl.full([XBLOCK, RBLOCK], True, tl.int1)
    r3 = rindex
    r0 = rindex % 4
    r2 = rindex // 16
    r4 = rindex % 16
    tmp0 = tl.load(in_ptr0 + r3, None)
    tmp1 = tl.load(in_ptr0 + (r0 + 16 * r2), None, eviction_policy='evict_last'
        )
    tmp3 = tl.load(in_ptr0 + (4 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp6 = tl.load(in_ptr0 + (8 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp9 = tl.load(in_ptr0 + (12 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp14 = tl.load(in_ptr1 + (r4 + 64 * r2), None)
    tmp19 = tl.load(in_ptr2 + r3, None)
    tmp20 = tl.load(in_ptr2 + (r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp22 = tl.load(in_ptr2 + (4 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp25 = tl.load(in_ptr2 + (8 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp28 = tl.load(in_ptr2 + (12 + r0 + 16 * r2), None, eviction_policy=
        'evict_last')
    tmp33 = tl.load(in_ptr1 + (16 + r4 + 64 * r2), None)
    tmp2 = tl_math.exp(tmp1)
    tmp4 = tl_math.exp(tmp3)
    tmp5 = tmp2 + tmp4
    tmp7 = tl_math.exp(tmp6)
    tmp8 = tmp5 + tmp7
    tmp10 = tl_math.exp(tmp9)
    tmp11 = tmp8 + tmp10
    tmp12 = tl_math.log(tmp11)
    tmp13 = tmp0 - tmp12
    tmp15 = tmp13 * tmp14
    tmp16 = tl.broadcast_to(tmp15, [XBLOCK, RBLOCK])
    tmp18 = tl.sum(tmp16, 1)[:, None]
    tmp21 = tl_math.exp(tmp20)
    tmp23 = tl_math.exp(tmp22)
    tmp24 = tmp21 + tmp23
    tmp26 = tl_math.exp(tmp25)
    tmp27 = tmp24 + tmp26
    tmp29 = tl_math.exp(tmp28)
    tmp30 = tmp27 + tmp29
    tmp31 = tl_math.log(tmp30)
    tmp32 = tmp19 - tmp31
    tmp34 = tmp32 * tmp33
    tmp35 = tl.broadcast_to(tmp34, [XBLOCK, RBLOCK])
    tmp37 = tl.sum(tmp35, 1)[:, None]
    tmp38 = -tmp18
    tmp39 = 0.0625
    tmp40 = tmp38 * tmp39
    tmp41 = -tmp37
    tmp42 = tmp41 * tmp39
    tmp43 = tmp40 + tmp42
    tl.debug_barrier()
    tl.store(in_out_ptr0 + tl.full([XBLOCK, 1], 0, tl.int32), tmp43, 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), (16, 4, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused__log_softmax_0[grid(64)](arg0_1, buf0, 64, XBLOCK=
            64, num_warps=1, num_stages=1)
        buf2 = empty_strided_cuda((4, 4, 4), (16, 4, 1), torch.float32)
        triton_poi_fused__log_softmax_1[grid(64)](arg0_1, buf2, 64, XBLOCK=
            64, num_warps=1, num_stages=1)
        del arg0_1
        buf1 = empty_strided_cuda((), (), torch.float32)
        buf4 = buf1
        del buf1
        triton_per_fused__log_softmax_add_div_mul_neg_sum_2[grid(1)](buf4,
            buf0, arg1_1, buf2, 1, 64, XBLOCK=1, num_warps=2, num_stages=1)
        del arg1_1
        del buf0
        del buf2
    return buf4,


class CrossEntropyLossIITNew(nn.Module):

    def __init__(self):
        super().__init__()
        self.loss = nn.CrossEntropyLoss(reduction='mean')

    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: 0.01496