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._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
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_mul_0(in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK: tl.
    constexpr):
    xnumel = 64
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex
    x0 = xindex % 4
    tmp0 = tl.load(in_ptr0 + x2, xmask)
    tmp1 = tl.load(in_ptr1 + x0, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 * tmp1
    tl.store(out_ptr0 + x2, tmp2, xmask)


@triton.jit
def triton_poi_fused_clone_transpose_1(in_ptr0, out_ptr0, out_ptr1, ynumel,
    xnumel, YBLOCK: tl.constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 4
    yoffset = tl.program_id(1) * YBLOCK
    yindex = yoffset + tl.arange(0, YBLOCK)[None, :]
    ymask = yindex < ynumel
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:, None]
    xmask = xindex < xnumel
    x1 = xindex
    y0 = yindex
    y2 = yindex % 4
    y3 = yindex // 4
    tmp0 = tl.load(in_ptr0 + (x1 + 4 * y0), xmask & ymask, eviction_policy=
        'evict_last')
    tl.store(out_ptr0 + (x1 + 4 * y0), tmp0, xmask & ymask)
    tl.store(out_ptr1 + (y2 + 4 * x1 + 16 * y3), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused__softmax_add_max_2(in_ptr0, in_ptr1, in_ptr2, out_ptr0,
    out_ptr1, out_ptr2, out_ptr3, xnumel, XBLOCK: tl.constexpr):
    xnumel = 16
    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_ptr1 + 4 * x1, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr2 + 4 * x2, xmask, eviction_policy='evict_last')
    tmp5 = tl.load(in_ptr1 + (1 + 4 * x1), xmask, eviction_policy='evict_last')
    tmp7 = tl.load(in_ptr2 + (1 + 4 * x2), xmask, eviction_policy='evict_last')
    tmp10 = tl.load(in_ptr1 + (2 + 4 * x1), xmask, eviction_policy='evict_last'
        )
    tmp12 = tl.load(in_ptr2 + (2 + 4 * x2), xmask, eviction_policy='evict_last'
        )
    tmp15 = tl.load(in_ptr1 + (3 + 4 * x1), xmask, eviction_policy='evict_last'
        )
    tmp17 = tl.load(in_ptr2 + (3 + 4 * x2), xmask, eviction_policy='evict_last'
        )
    tmp2 = tmp0 + tmp1
    tmp4 = tmp2 + tmp3
    tmp6 = tmp0 + tmp5
    tmp8 = tmp6 + tmp7
    tmp9 = triton_helpers.maximum(tmp4, tmp8)
    tmp11 = tmp0 + tmp10
    tmp13 = tmp11 + tmp12
    tmp14 = triton_helpers.maximum(tmp9, tmp13)
    tmp16 = tmp0 + tmp15
    tmp18 = tmp16 + tmp17
    tmp19 = triton_helpers.maximum(tmp14, tmp18)
    tmp20 = tmp4 - tmp19
    tmp21 = tl_math.exp(tmp20)
    tmp22 = tmp8 - tmp19
    tmp23 = tl_math.exp(tmp22)
    tmp24 = tmp21 + tmp23
    tmp25 = tmp13 - tmp19
    tmp26 = tl_math.exp(tmp25)
    tmp27 = tmp24 + tmp26
    tmp28 = tmp18 - tmp19
    tmp29 = tl_math.exp(tmp28)
    tmp30 = tmp27 + tmp29
    tmp31 = tmp4 > tmp8
    tmp32 = tmp4 == tmp8
    tmp33 = tmp4 != tmp4
    tmp34 = tmp8 != tmp8
    tmp35 = tmp33 > tmp34
    tmp36 = tmp31 | tmp35
    tmp37 = tmp33 & tmp34
    tmp38 = tmp32 | tmp37
    tmp39 = tl.full([1], 0, tl.int64)
    tmp40 = tl.full([1], 1, tl.int64)
    tmp41 = tmp39 < tmp40
    tmp42 = tmp38 & tmp41
    tmp43 = tmp36 | tmp42
    tmp44 = tl.where(tmp43, tmp4, tmp8)
    tmp45 = tl.where(tmp43, tmp39, tmp40)
    tmp46 = tmp44 > tmp13
    tmp47 = tmp44 == tmp13
    tmp48 = tmp44 != tmp44
    tmp49 = tmp13 != tmp13
    tmp50 = tmp48 > tmp49
    tmp51 = tmp46 | tmp50
    tmp52 = tmp48 & tmp49
    tmp53 = tmp47 | tmp52
    tmp54 = tl.full([1], 2, tl.int64)
    tmp55 = tmp45 < tmp54
    tmp56 = tmp53 & tmp55
    tmp57 = tmp51 | tmp56
    tmp58 = tl.where(tmp57, tmp44, tmp13)
    tmp59 = tl.where(tmp57, tmp45, tmp54)
    tmp60 = tmp58 > tmp18
    tmp61 = tmp58 == tmp18
    tmp62 = tmp58 != tmp58
    tmp63 = tmp18 != tmp18
    tmp64 = tmp62 > tmp63
    tmp65 = tmp60 | tmp64
    tmp66 = tmp62 & tmp63
    tmp67 = tmp61 | tmp66
    tmp68 = tl.full([1], 3, tl.int64)
    tmp69 = tmp59 < tmp68
    tmp70 = tmp67 & tmp69
    tmp71 = tmp65 | tmp70
    tl.where(tmp71, tmp58, tmp18)
    tmp73 = tl.where(tmp71, tmp59, tmp68)
    tl.store(out_ptr0 + x2, tmp19, xmask)
    tl.store(out_ptr1 + x2, tmp30, xmask)
    tl.store(out_ptr2 + x2, tmp19, xmask)
    tl.store(out_ptr3 + x2, tmp73, xmask)


@triton.jit
def triton_poi_fused__softmax_add_3(in_out_ptr0, in_ptr0, in_ptr1, in_ptr2,
    in_ptr3, xnumel, XBLOCK: tl.constexpr):
    xnumel = 64
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex // 4
    x0 = xindex % 4
    x2 = xindex // 16
    x4 = xindex
    tmp0 = tl.load(in_ptr0 + x3, xmask, eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr1 + (x0 + 4 * x2), xmask, eviction_policy='evict_last'
        )
    tmp3 = tl.load(in_out_ptr0 + x4, xmask)
    tmp5 = tl.load(in_ptr2 + x3, xmask, eviction_policy='evict_last')
    tmp8 = tl.load(in_ptr3 + x3, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp4 = tmp2 + tmp3
    tmp6 = tmp4 - tmp5
    tmp7 = tl_math.exp(tmp6)
    tmp9 = tmp7 / tmp8
    tl.store(in_out_ptr0 + x4, tmp9, xmask)


@triton.jit
def triton_poi_fused__softmax_4(in_ptr0, out_ptr0, xnumel, XBLOCK: tl.constexpr
    ):
    xnumel = 16
    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_5(in_ptr0, out_ptr0, xnumel, XBLOCK: tl.constexpr
    ):
    xnumel = 16
    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 = tmp1 + tmp2
    tmp5 = tmp3 + tmp4
    tmp7 = tmp5 + tmp6
    tmp8 = tmp0 / tmp7
    tl.store(out_ptr0 + x2, tmp8, xmask)


@triton.jit
def triton_poi_fused_cat_6(in_ptr0, in_ptr1, in_ptr2, out_ptr0, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 16
    x3 = xindex // 16
    x2 = xindex // 64
    x4 = 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 * x3 + 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 * x3 + (-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_ptr0 + (4 * x3 + (-8 + x0)), tmp14 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp16 = tl.load(in_ptr1 + (4 * x3 + (-8 + x0)), tmp14 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp17 = tmp15 * tmp16
    tmp18 = tl.full(tmp17.shape, 0.0, tmp17.dtype)
    tmp19 = tl.where(tmp14, tmp17, tmp18)
    tmp20 = tmp0 >= tmp12
    tl.full([1], 16, tl.int64)
    tmp23 = tl.load(in_ptr2 + (4 * x2 + (-12 + x0)), tmp20 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp24 = tl.load(in_ptr1 + (4 * x3 + (-12 + x0)), tmp20 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp25 = tmp23 * tmp24
    tmp26 = tl.full(tmp25.shape, 0.0, tmp25.dtype)
    tmp27 = tl.where(tmp20, tmp25, tmp26)
    tmp28 = tl.where(tmp14, tmp19, tmp27)
    tmp29 = tl.where(tmp9, tmp10, tmp28)
    tmp30 = tl.where(tmp4, tmp5, tmp29)
    tl.store(out_ptr0 + x4, tmp30, 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), (16, 4, 1))
    assert_size_stride(primals_2, (4, 4, 4), (16, 4, 1))
    assert_size_stride(primals_3, (1, 4), (4, 1))
    assert_size_stride(primals_4, (1, 4), (4, 1))
    assert_size_stride(primals_5, (4,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((16, 1), (1, 1), torch.float32)
        extern_kernels.mm(reinterpret_tensor(primals_1, (16, 4), (4, 1), 0),
            reinterpret_tensor(primals_3, (4, 1), (1, 4), 0), out=buf0)
        del primals_3
        buf1 = empty_strided_cuda((16, 1), (1, 1), torch.float32)
        extern_kernels.mm(reinterpret_tensor(primals_2, (16, 4), (4, 1), 0),
            reinterpret_tensor(primals_4, (4, 1), (1, 4), 0), out=buf1)
        del primals_4
        buf2 = empty_strided_cuda((4, 4, 4), (16, 4, 1), torch.float32)
        get_raw_stream(0)
        triton_poi_fused_mul_0[grid(64)](primals_1, primals_5, buf2, 64,
            XBLOCK=64, num_warps=1, num_stages=1)
        del primals_5
        buf3 = empty_strided_cuda((4, 4, 4), (16, 1, 4), torch.float32)
        buf15 = empty_strided_cuda((4, 4, 4), (16, 1, 4), torch.float32)
        triton_poi_fused_clone_transpose_1[grid(16, 4)](primals_2, buf3,
            buf15, 16, 4, XBLOCK=4, YBLOCK=16, num_warps=1, num_stages=1)
        buf4 = empty_strided_cuda((4, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(buf2, buf3, out=buf4)
        del buf2
        buf5 = empty_strided_cuda((4, 4, 1), (4, 1, 16), torch.float32)
        buf6 = empty_strided_cuda((4, 4, 1), (4, 1, 16), torch.float32)
        buf9 = empty_strided_cuda((4, 4), (4, 1), torch.float32)
        buf10 = empty_strided_cuda((4, 4), (4, 1), torch.int64)
        triton_poi_fused__softmax_add_max_2[grid(16)](buf0, buf1, buf4,
            buf5, buf6, buf9, buf10, 16, XBLOCK=16, num_warps=1, num_stages=1)
        buf7 = buf4
        del buf4
        triton_poi_fused__softmax_add_3[grid(64)](buf7, buf0, buf1, buf5,
            buf6, 64, XBLOCK=64, num_warps=1, num_stages=1)
        del buf0
        del buf1
        del buf5
        buf8 = reinterpret_tensor(buf3, (4, 4, 4), (16, 4, 1), 0)
        del buf3
        extern_kernels.bmm(buf7, primals_2, out=buf8)
        buf11 = reinterpret_tensor(buf6, (4, 4), (4, 1), 0)
        del buf6
        triton_poi_fused__softmax_4[grid(16)](buf9, buf11, 16, XBLOCK=16,
            num_warps=1, num_stages=1)
        buf12 = buf9
        del buf9
        triton_poi_fused__softmax_5[grid(16)](buf11, buf12, 16, XBLOCK=16,
            num_warps=1, num_stages=1)
        buf13 = reinterpret_tensor(buf11, (4, 1, 4), (4, 4, 1), 0)
        del buf11
        extern_kernels.bmm(reinterpret_tensor(buf12, (4, 1, 4), (4, 4, 1), 
            0), primals_1, out=buf13)
        buf14 = empty_strided_cuda((4, 4, 16), (64, 16, 1), torch.float32)
        triton_poi_fused_cat_6[grid(256)](primals_1, buf8, buf13, buf14, 
            256, XBLOCK=256, num_warps=4, num_stages=1)
    return (buf14, primals_1, primals_2, buf7, buf8, buf12, buf13,
        reinterpret_tensor(buf10, (4, 4, 1), (4, 1, 1), 0), buf15)


class BiAttentionNew(nn.Module):

    def __init__(self, input_size, dropout):
        super().__init__()
        self.dropout = nn.Dropout(p=dropout)
        self.input_linear = nn.Linear(input_size, 1, bias=False)
        self.memory_linear = nn.Linear(input_size, 1, bias=False)
        self.dot_scale = nn.Parameter(torch.Tensor(input_size).uniform_(1.0 /
            input_size ** 0.5))

    def forward(self, input_0, input_1):
        primals_5 = self.dot_scale
        primals_3 = self.input_linear.weight
        primals_4 = self.memory_linear.weight
        primals_1 = input_0
        primals_2 = input_1
        output = call([primals_1, primals_2, primals_3, primals_4, primals_5])
        return output[0]


Measured latency_ms: 0.027048