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_cat_0(in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK: tl.
    constexpr):
    xnumel = 512
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x1 = xindex // 16 % 8
    x0 = xindex % 16
    x2 = xindex // 128
    x3 = xindex
    tmp0 = x1
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 1, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0 + 64 * x2), tmp4 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 2, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (x0 + 64 * x2), tmp9 & xmask, eviction_policy
        ='evict_last', other=0.0)
    tmp11 = tmp0 >= tmp7
    tmp12 = tl.full([1], 3, tl.int64)
    tmp13 = tmp0 < tmp12
    tmp14 = tmp11 & tmp13
    tmp15 = tl.load(in_ptr0 + (16 + x0 + 64 * x2), tmp14 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tmp0 >= tmp12
    tmp17 = tl.full([1], 4, tl.int64)
    tmp18 = tmp0 < tmp17
    tmp19 = tmp16 & tmp18
    tmp20 = tl.load(in_ptr1 + (16 + x0 + 64 * x2), tmp19 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp21 = tmp0 >= tmp17
    tmp22 = tl.full([1], 5, tl.int64)
    tmp23 = tmp0 < tmp22
    tmp24 = tmp21 & tmp23
    tmp25 = tl.load(in_ptr0 + (32 + x0 + 64 * x2), tmp24 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp26 = tmp0 >= tmp22
    tmp27 = tl.full([1], 6, tl.int64)
    tmp28 = tmp0 < tmp27
    tmp29 = tmp26 & tmp28
    tmp30 = tl.load(in_ptr1 + (32 + x0 + 64 * x2), tmp29 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp31 = tmp0 >= tmp27
    tmp32 = tl.full([1], 7, tl.int64)
    tmp33 = tmp0 < tmp32
    tmp34 = tmp31 & tmp33
    tmp35 = tl.load(in_ptr0 + (48 + x0 + 64 * x2), tmp34 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp36 = tmp0 >= tmp32
    tl.full([1], 8, tl.int64)
    tmp39 = tl.load(in_ptr1 + (48 + x0 + 64 * x2), tmp36 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp40 = tl.where(tmp34, tmp35, tmp39)
    tmp41 = tl.where(tmp29, tmp30, tmp40)
    tmp42 = tl.where(tmp24, tmp25, tmp41)
    tmp43 = tl.where(tmp19, tmp20, tmp42)
    tmp44 = tl.where(tmp14, tmp15, tmp43)
    tmp45 = tl.where(tmp9, tmp10, tmp44)
    tmp46 = tl.where(tmp4, tmp5, tmp45)
    tl.store(out_ptr0 + x3, tmp46, 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, 8, 4, 4), (128, 16, 4, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_cat_0[grid(512)](arg0_1, arg1_1, buf0, 512, XBLOCK
            =128, num_warps=4, num_stages=1)
        del arg0_1
        del arg1_1
    return buf0,


class ShuffleCatChunkNew(nn.Module):

    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: 0.015085