import torch
from torch._inductor.select_algorithm import extern_kernels
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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_cat_0(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 1536
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 24
    x1 = xindex // 24
    x2 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (4 * x1 + x0), tmp4 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 8, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr1 + (4 * x1 + (-4 + x0)), tmp9 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp11 = tmp0 >= tmp7
    tmp12 = tl.full([1], 12, tl.int64)
    tmp13 = tmp0 < tmp12
    tmp14 = tmp11 & tmp13
    tmp15 = tl.load(in_ptr2 + (4 * x1 + (-8 + x0)), tmp14 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tmp0 >= tmp12
    tmp17 = tl.full([1], 16, tl.int64)
    tmp18 = tmp0 < tmp17
    tmp19 = tmp16 & tmp18
    tmp20 = tl.load(in_ptr0 + (4 * x1 + (-12 + x0)), tmp19 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp21 = tl.load(in_ptr1 + (4 * x1 + (-12 + x0)), tmp19 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp22 = tmp20 - tmp21
    tmp23 = tl.full(tmp22.shape, 0.0, tmp22.dtype)
    tmp24 = tl.where(tmp19, tmp22, tmp23)
    tmp25 = tmp0 >= tmp17
    tmp26 = tl.full([1], 20, tl.int64)
    tmp27 = tmp0 < tmp26
    tmp28 = tmp25 & tmp27
    tmp29 = tl.load(in_ptr0 + (4 * x1 + (-16 + x0)), tmp28 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp30 = tl.load(in_ptr2 + (4 * x1 + (-16 + x0)), tmp28 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp31 = tmp29 - tmp30
    tmp32 = tl.full(tmp31.shape, 0.0, tmp31.dtype)
    tmp33 = tl.where(tmp28, tmp31, tmp32)
    tmp34 = tmp0 >= tmp26
    tl.full([1], 24, tl.int64)
    tmp37 = tl.load(in_ptr1 + (4 * x1 + (-20 + x0)), tmp34 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp38 = tl.load(in_ptr2 + (4 * x1 + (-20 + x0)), tmp34 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp39 = tmp37 - tmp38
    tmp40 = tl.full(tmp39.shape, 0.0, tmp39.dtype)
    tmp41 = tl.where(tmp34, tmp39, tmp40)
    tmp42 = tl.where(tmp28, tmp33, tmp41)
    tmp43 = tl.where(tmp19, tmp24, tmp42)
    tmp44 = tl.where(tmp14, tmp15, tmp43)
    tmp45 = tl.where(tmp9, tmp10, tmp44)
    tmp46 = tl.where(tmp4, tmp5, tmp45)
    tl.store(out_ptr0 + x2, tmp46, xmask)


def call(args):
    primals_1, primals_2, primals_3, primals_4, primals_5 = args
    args.clear()
    assert_size_stride(primals_1, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_2, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_3, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_4, (4, 24), (24, 1))
    assert_size_stride(primals_5, (4,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((4, 4, 4, 24), (384, 96, 24, 1), torch.
            float32)
        get_raw_stream(0)
        triton_poi_fused_cat_0[grid(1536)](primals_1, primals_2, primals_3,
            buf0, 1536, XBLOCK=128, num_warps=4, num_stages=1)
        del primals_1
        del primals_2
        del primals_3
        buf1 = empty_strided_cuda((64, 4), (4, 1), torch.float32)
        extern_kernels.addmm(primals_5, reinterpret_tensor(buf0, (64, 24),
            (24, 1), 0), reinterpret_tensor(primals_4, (24, 4), (1, 24), 0),
            alpha=1, beta=1, out=buf1)
        del primals_4
        del primals_5
    return reinterpret_tensor(buf1, (4, 4, 4, 4), (64, 16, 4, 1), 0
        ), reinterpret_tensor(buf0, (64, 24), (24, 1), 0)


class Fusion3_MinusFCLayerNew(nn.Module):

    def __init__(self, input_dim):
        super(Fusion3_MinusFCLayerNew, self).__init__()
        self._norm_layer1 = nn.Linear(input_dim * 6, input_dim)

    def forward(self, input_0, input_1, input_2):
        primals_4 = self._norm_layer1.weight
        primals_5 = self._norm_layer1.bias
        primals_1 = input_0
        primals_2 = input_1
        primals_3 = input_2
        output = call([primals_1, primals_2, primals_3, primals_4, primals_5])
        return output[0]


Measured latency_ms: 0.026516