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 libdevice, math as tl_math
import torch.utils.data
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
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor


@triton.jit
def triton_poi_fused_convolution_0(in_out_ptr0, in_ptr0, xnumel, XBLOCK: tl
    .constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 4
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tl.store(in_out_ptr0 + x3, tmp2, xmask)


@triton.jit
def triton_poi_fused_clone_1(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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
    x2 = xindex % 4
    x3 = xindex // 4
    y0 = yindex % 4
    y1 = yindex // 4
    x5 = xindex
    y4 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x3 + 16 * x2 + 64 * y1), xmask & ymask)
    tmp1 = libdevice.tanh(tmp0)
    tl.store(out_ptr0 + (x5 + 16 * y4), tmp1, xmask & ymask)


@triton.jit
def triton_poi_fused_clone_2(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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
    x2 = xindex
    y0 = yindex % 4
    y1 = yindex // 4
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x2 + 64 * y1), xmask & ymask)
    tmp1 = libdevice.tanh(tmp0)
    tl.store(out_ptr0 + (x2 + 16 * y3), tmp1, xmask & ymask)


@triton.jit
def triton_poi_fused__softmax_clone_3(in_ptr0, out_ptr0, out_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x4 = xindex
    x1 = xindex // 4
    x0 = xindex % 4
    x3 = xindex // 16
    tmp0 = tl.load(in_ptr0 + x4, 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')
    tmp10 = tl.load(in_ptr0 + (x0 + 16 * x3), xmask, eviction_policy=
        'evict_last')
    tmp11 = tl.load(in_ptr0 + (4 + x0 + 16 * x3), xmask, eviction_policy=
        'evict_last')
    tmp13 = tl.load(in_ptr0 + (8 + x0 + 16 * x3), xmask, eviction_policy=
        'evict_last')
    tmp15 = tl.load(in_ptr0 + (12 + x0 + 16 * x3), 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)
    tmp12 = triton_helpers.maximum(tmp10, tmp11)
    tmp14 = triton_helpers.maximum(tmp12, tmp13)
    tmp16 = triton_helpers.maximum(tmp14, tmp15)
    tmp17 = tmp0 - tmp16
    tmp18 = tl_math.exp(tmp17)
    tl.store(out_ptr0 + x4, tmp9, xmask)
    tl.store(out_ptr1 + x4, tmp18, xmask)


@triton.jit
def triton_poi_fused_clone_4(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 = tmp1 + tmp2
    tmp5 = tmp3 + tmp4
    tmp7 = tmp5 + tmp6
    tmp8 = tmp0 / tmp7
    tl.store(out_ptr0 + x2, tmp8, xmask)


@triton.jit
def triton_poi_fused_clone_5(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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
    x2 = xindex
    y0 = yindex % 4
    y1 = yindex // 4
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x2 + 64 * y1), xmask & ymask)
    tl.store(out_ptr0 + (x2 + 16 * y3), tmp0, xmask & ymask)


@triton.jit
def triton_poi_fused_clone_6(in_ptr0, in_ptr1, out_ptr0, ynumel, xnumel,
    YBLOCK: tl.constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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
    x2 = xindex
    y0 = yindex % 4
    y1 = yindex // 4
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x2 + 64 * y1), xmask & ymask)
    tmp3 = tl.load(in_ptr1 + (x2 + 16 * y3), xmask & ymask)
    tmp1 = 4.0
    tmp2 = tmp0 * tmp1
    tmp4 = -3.0
    tmp5 = tmp3 * tmp4
    tmp6 = tmp2 + tmp5
    tl.store(out_ptr0 + (x2 + 16 * y3), tmp6, xmask & ymask)


@triton.jit
def triton_poi_fused_clone_7(in_ptr0, out_ptr0, ynumel, xnumel, YBLOCK: tl.
    constexpr, XBLOCK: tl.constexpr):
    ynumel = 64
    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
    x2 = xindex
    y0 = yindex % 4
    y1 = yindex // 4
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x2 + 16 * y1), xmask & ymask,
        eviction_policy='evict_last')
    tmp1 = tl.load(in_ptr0 + (y0 + 16 * y1), ymask, eviction_policy=
        'evict_last')
    tmp2 = tl.load(in_ptr0 + (4 + y0 + 16 * y1), ymask, eviction_policy=
        'evict_last')
    tmp4 = tl.load(in_ptr0 + (8 + y0 + 16 * y1), ymask, eviction_policy=
        'evict_last')
    tmp6 = tl.load(in_ptr0 + (12 + y0 + 16 * y1), ymask, eviction_policy=
        'evict_last')
    tmp3 = tmp1 + tmp2
    tmp5 = tmp3 + tmp4
    tmp7 = tmp5 + tmp6
    tmp8 = tmp0 / tmp7
    tl.store(out_ptr0 + (x2 + 4 * y3), tmp8, xmask & ymask)


@triton.jit
def triton_poi_fused_clone_8(in_ptr0, in_ptr1, in_ptr2, out_ptr0, out_ptr1,
    ynumel, xnumel, YBLOCK: tl.constexpr, XBLOCK: tl.constexpr):
    ynumel = 16
    xnumel = 16
    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
    x2 = xindex
    y0 = yindex % 4
    y1 = yindex // 4
    y3 = yindex
    tmp0 = tl.load(in_ptr0 + (y0 + 4 * x2 + 64 * y1), xmask & ymask)
    tmp3 = tl.load(in_ptr1 + (x2 + 16 * y3), xmask & ymask)
    tmp7 = tl.load(in_ptr2 + (x2 + 16 * y3), xmask & ymask)
    tmp1 = 4.0
    tmp2 = tmp0 * tmp1
    tmp4 = -3.0
    tmp5 = tmp3 * tmp4
    tmp6 = tmp2 + tmp5
    tmp8 = tmp7 * tmp4
    tmp9 = tmp2 + tmp8
    tl.store(out_ptr0 + (x2 + 16 * y3), tmp6, xmask & ymask)
    tl.store(out_ptr1 + (x2 + 16 * y3), tmp9, xmask & ymask)


@triton.jit
def triton_poi_fused_cat_9(in_ptr0, in_ptr1, in_ptr2, in_ptr3, in_ptr4,
    in_ptr5, in_ptr6, in_ptr7, in_ptr8, out_ptr0, out_ptr1, xnumel, XBLOCK:
    tl.constexpr):
    xnumel = 1280
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x2 = xindex // 16 % 20
    x3 = xindex // 320
    x4 = xindex % 16
    x0 = xindex % 4
    x1 = xindex // 4 % 4
    x5 = xindex
    tmp0 = x2
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x4 + 16 * x2 + 64 * x3), tmp4 & xmask, other=0.0)
    tmp6 = tmp0 >= tmp3
    tmp7 = tl.full([1], 8, tl.int64)
    tmp8 = tmp0 < tmp7
    tmp9 = tmp6 & tmp8
    tmp10 = tl.load(in_ptr0 + (x4 + 16 * (-4 + x2) + 64 * x3), tmp9 & xmask,
        other=0.0)
    tmp11 = 4.0
    tmp12 = tmp10 * tmp11
    tmp13 = tl.load(in_ptr1 + (x1 + 4 * (-4 + x2) + 16 * x0 + 64 * x3), 
        tmp9 & xmask, eviction_policy='evict_last', other=0.0)
    tmp14 = -3.0
    tmp15 = tmp13 * tmp14
    tmp16 = tmp12 + tmp15
    tmp17 = tl.full(tmp16.shape, 0.0, tmp16.dtype)
    tmp18 = tl.where(tmp9, tmp16, tmp17)
    tmp19 = tmp0 >= tmp7
    tmp20 = tl.full([1], 12, tl.int64)
    tmp21 = tmp0 < tmp20
    tmp22 = tmp19 & tmp21
    tmp23 = tl.load(in_ptr0 + (x4 + 16 * (-8 + x2) + 64 * x3), tmp22 &
        xmask, other=0.0)
    tmp24 = tmp23 * tmp11
    tmp25 = tl.load(in_ptr2 + (x1 + 4 * (-8 + x2) + 16 * x0 + 64 * x3), 
        tmp22 & xmask, eviction_policy='evict_last', other=0.0)
    tmp26 = tmp25 * tmp14
    tmp27 = tmp24 + tmp26
    tmp28 = tl.full(tmp27.shape, 0.0, tmp27.dtype)
    tmp29 = tl.where(tmp22, tmp27, tmp28)
    tmp30 = tmp0 >= tmp20
    tmp31 = tl.full([1], 16, tl.int64)
    tmp32 = tmp0 < tmp31
    tmp33 = tmp30 & tmp32
    tmp34 = tl.load(in_ptr0 + (x4 + 16 * (-12 + x2) + 64 * x3), tmp33 &
        xmask, other=0.0)
    tmp35 = tmp34 * tmp11
    tmp36 = tl.load(in_ptr3 + (x1 + 4 * (-12 + x2) + 16 * x0 + 64 * x3), 
        tmp33 & xmask, eviction_policy='evict_last', other=0.0)
    tmp37 = tmp36 * tmp14
    tmp38 = tmp35 + tmp37
    tmp39 = tl.full(tmp38.shape, 0.0, tmp38.dtype)
    tmp40 = tl.where(tmp33, tmp38, tmp39)
    tmp41 = tmp0 >= tmp31
    tl.full([1], 20, tl.int64)
    tmp44 = tl.load(in_ptr0 + (x4 + 16 * (-16 + x2) + 64 * x3), tmp41 &
        xmask, other=0.0)
    tmp45 = tmp44 * tmp11
    tmp46 = tl.load(in_ptr4 + (x1 + 4 * (-16 + x2) + 16 * x0 + 64 * x3), 
        tmp41 & xmask, eviction_policy='evict_last', other=0.0)
    tmp47 = tmp46 * tmp14
    tmp48 = tmp45 + tmp47
    tmp49 = tl.full(tmp48.shape, 0.0, tmp48.dtype)
    tmp50 = tl.where(tmp41, tmp48, tmp49)
    tmp51 = tl.where(tmp33, tmp40, tmp50)
    tmp52 = tl.where(tmp22, tmp29, tmp51)
    tmp53 = tl.where(tmp9, tmp18, tmp52)
    tmp54 = tl.where(tmp4, tmp5, tmp53)
    tmp55 = tl.load(in_ptr5 + (x1 + 4 * (-4 + x2) + 16 * x0 + 64 * x3), 
        tmp9 & xmask, eviction_policy='evict_last', other=0.0)
    tmp56 = tmp55 * tmp14
    tmp57 = tmp12 + tmp56
    tmp58 = tl.full(tmp57.shape, 0.0, tmp57.dtype)
    tmp59 = tl.where(tmp9, tmp57, tmp58)
    tmp60 = tl.load(in_ptr6 + (x1 + 4 * (-8 + x2) + 16 * x0 + 64 * x3), 
        tmp22 & xmask, eviction_policy='evict_last', other=0.0)
    tmp61 = tmp60 * tmp14
    tmp62 = tmp24 + tmp61
    tmp63 = tl.full(tmp62.shape, 0.0, tmp62.dtype)
    tmp64 = tl.where(tmp22, tmp62, tmp63)
    tmp65 = tl.load(in_ptr7 + (x1 + 4 * (-12 + x2) + 16 * x0 + 64 * x3), 
        tmp33 & xmask, eviction_policy='evict_last', other=0.0)
    tmp66 = tmp65 * tmp14
    tmp67 = tmp35 + tmp66
    tmp68 = tl.full(tmp67.shape, 0.0, tmp67.dtype)
    tmp69 = tl.where(tmp33, tmp67, tmp68)
    tmp70 = tl.load(in_ptr8 + (x1 + 4 * (-16 + x2) + 16 * x0 + 64 * x3), 
        tmp41 & xmask, eviction_policy='evict_last', other=0.0)
    tmp71 = tmp70 * tmp14
    tmp72 = tmp45 + tmp71
    tmp73 = tl.full(tmp72.shape, 0.0, tmp72.dtype)
    tmp74 = tl.where(tmp41, tmp72, tmp73)
    tmp75 = tl.where(tmp33, tmp69, tmp74)
    tmp76 = tl.where(tmp22, tmp64, tmp75)
    tmp77 = tl.where(tmp9, tmp59, tmp76)
    tmp78 = tl.where(tmp4, tmp5, tmp77)
    tl.store(out_ptr0 + x5, tmp54, xmask)
    tl.store(out_ptr1 + x5, tmp78, xmask)


@triton.jit
def triton_poi_fused_add_convolution_10(in_out_ptr0, in_ptr0, in_ptr1,
    in_ptr2, xnumel, XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x3 = xindex
    x1 = xindex // 16 % 4
    tmp0 = tl.load(in_out_ptr0 + x3, xmask)
    tmp1 = tl.load(in_ptr0 + x1, xmask, eviction_policy='evict_last')
    tmp3 = tl.load(in_ptr1 + x3, xmask)
    tmp4 = tl.load(in_ptr2 + x1, xmask, eviction_policy='evict_last')
    tmp2 = tmp0 + tmp1
    tmp5 = tmp3 + tmp4
    tmp6 = tmp2 + tmp5
    tl.store(in_out_ptr0 + x3, tmp6, xmask)


def call(args):
    (primals_1, primals_2, primals_3, primals_4, primals_5, primals_6,
        primals_7, primals_8, primals_9) = args
    args.clear()
    assert_size_stride(primals_1, (4, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_2, (4,), (1,))
    assert_size_stride(primals_3, (4, 4, 4, 4), (64, 16, 4, 1))
    assert_size_stride(primals_4, (4, 4, 1, 1), (4, 1, 1, 1))
    assert_size_stride(primals_5, (4,), (1,))
    assert_size_stride(primals_6, (4, 20, 1, 1), (20, 1, 1, 1))
    assert_size_stride(primals_7, (4,), (1,))
    assert_size_stride(primals_8, (4, 20, 1, 1), (20, 1, 1, 1))
    assert_size_stride(primals_9, (4,), (1,))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = extern_kernels.convolution(primals_3, primals_1, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf0, (4, 4, 4, 4), (64, 16, 4, 1))
        buf1 = buf0
        del buf0
        get_raw_stream(0)
        triton_poi_fused_convolution_0[grid(256)](buf1, primals_2, 256,
            XBLOCK=256, num_warps=4, num_stages=1)
        del primals_2
        buf2 = extern_kernels.convolution(primals_3, primals_4, stride=(1, 
            1), padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf2, (4, 4, 4, 4), (64, 16, 4, 1))
        buf3 = buf2
        del buf2
        triton_poi_fused_convolution_0[grid(256)](buf3, primals_5, 256,
            XBLOCK=256, num_warps=4, num_stages=1)
        del primals_5
        buf4 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1), torch
            .float32)
        triton_poi_fused_clone_1[grid(16, 16)](buf1, buf4, 16, 16, XBLOCK=
            16, YBLOCK=16, num_warps=4, num_stages=1)
        buf5 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1), torch
            .float32)
        triton_poi_fused_clone_2[grid(16, 16)](buf3, buf5, 16, 16, XBLOCK=
            16, YBLOCK=16, num_warps=4, num_stages=1)
        buf6 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf4, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf5, (16, 4, 4), (16, 4, 1), 0), out=buf6)
        buf7 = empty_strided_cuda((4, 4, 4, 4), (64, 4, 1, 16), torch.float32)
        buf8 = empty_strided_cuda((4, 4, 4, 4), (64, 1, 4, 16), torch.float32)
        triton_poi_fused__softmax_clone_3[grid(256)](buf6, buf7, buf8, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        buf9 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1), torch
            .float32)
        triton_poi_fused_clone_4[grid(256)](buf7, buf9, 256, XBLOCK=256,
            num_warps=4, num_stages=1)
        buf10 = reinterpret_tensor(buf7, (4, 4, 4, 4, 1), (64, 16, 4, 1, 1), 0)
        del buf7
        triton_poi_fused_clone_5[grid(16, 16)](primals_3, buf10, 16, 16,
            XBLOCK=16, YBLOCK=16, num_warps=4, num_stages=1)
        buf11 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf10, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf9, (16, 4, 4), (16, 4, 1), 0), out=buf11)
        buf12 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_6[grid(16, 16)](primals_3, buf11, buf12, 16,
            16, XBLOCK=16, YBLOCK=16, num_warps=4, num_stages=1)
        buf13 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf12, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf9, (16, 4, 4), (16, 4, 1), 0), out=buf13)
        buf14 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_6[grid(16, 16)](primals_3, buf13, buf14, 16,
            16, XBLOCK=16, YBLOCK=16, num_warps=4, num_stages=1)
        buf15 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf14, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf9, (16, 4, 4), (16, 4, 1), 0), out=buf15)
        buf20 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_7[grid(64, 4)](buf8, buf20, 64, 4, XBLOCK=4,
            YBLOCK=32, num_warps=4, num_stages=1)
        buf21 = reinterpret_tensor(buf8, (16, 4, 4), (16, 4, 1), 0)
        del buf8
        extern_kernels.bmm(reinterpret_tensor(buf10, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf20, (16, 4, 4), (16, 4, 1), 0), out=buf21
            )
        buf16 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        buf22 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_8[grid(16, 16)](primals_3, buf15, buf21,
            buf16, buf22, 16, 16, XBLOCK=16, YBLOCK=16, num_warps=4,
            num_stages=1)
        buf17 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf16, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf9, (16, 4, 4), (16, 4, 1), 0), out=buf17)
        buf23 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf22, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf20, (16, 4, 4), (16, 4, 1), 0), out=buf23
            )
        buf24 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_6[grid(16, 16)](primals_3, buf23, buf24, 16,
            16, XBLOCK=16, YBLOCK=16, num_warps=4, num_stages=1)
        buf25 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf24, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf20, (16, 4, 4), (16, 4, 1), 0), out=buf25
            )
        buf26 = empty_strided_cuda((4, 4, 4, 4, 1), (64, 16, 4, 1, 1),
            torch.float32)
        triton_poi_fused_clone_6[grid(16, 16)](primals_3, buf25, buf26, 16,
            16, XBLOCK=16, YBLOCK=16, num_warps=4, num_stages=1)
        buf27 = empty_strided_cuda((16, 4, 4), (16, 4, 1), torch.float32)
        extern_kernels.bmm(reinterpret_tensor(buf26, (16, 4, 4), (16, 4, 1),
            0), reinterpret_tensor(buf20, (16, 4, 4), (16, 4, 1), 0), out=buf27
            )
        buf18 = empty_strided_cuda((4, 20, 4, 4), (320, 16, 4, 1), torch.
            float32)
        buf28 = empty_strided_cuda((4, 20, 4, 4), (320, 16, 4, 1), torch.
            float32)
        triton_poi_fused_cat_9[grid(1280)](primals_3, buf11, buf13, buf15,
            buf17, buf21, buf23, buf25, buf27, buf18, buf28, 1280, XBLOCK=
            256, num_warps=4, num_stages=1)
        del buf11
        del buf13
        del buf15
        del buf17
        del buf21
        del buf23
        del buf25
        del buf27
        buf19 = extern_kernels.convolution(buf18, primals_6, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf19, (4, 4, 4, 4), (64, 16, 4, 1))
        buf29 = extern_kernels.convolution(buf28, primals_8, stride=(1, 1),
            padding=(0, 0), dilation=(1, 1), transposed=False,
            output_padding=(0, 0), groups=1, bias=None)
        assert_size_stride(buf29, (4, 4, 4, 4), (64, 16, 4, 1))
        buf30 = buf19
        del buf19
        triton_poi_fused_add_convolution_10[grid(256)](buf30, primals_7,
            buf29, primals_9, 256, XBLOCK=128, num_warps=4, num_stages=1)
        del buf29
        del primals_7
        del primals_9
    return (buf30, primals_1, primals_3, primals_4, primals_6, primals_8,
        buf1, buf3, buf6, buf18, buf28, reinterpret_tensor(buf26, (16, 4, 4
        ), (16, 1, 4), 0), reinterpret_tensor(buf20, (16, 4, 4), (16, 1, 4),
        0), reinterpret_tensor(buf24, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf22, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf10, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf16, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf9, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf14, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf12, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf4, (16, 4, 4), (16, 1, 4), 0),
        reinterpret_tensor(buf5, (16, 4, 4), (16, 1, 4), 0))


class linear(nn.Module):

    def __init__(self, c_in, c_out, bias=True):
        super(linear, self).__init__()
        self.mlp = torch.nn.Conv2d(c_in, c_out, kernel_size=(1, 1), padding
            =(0, 0), stride=(1, 1), bias=bias)

    def forward(self, x):
        return self.mlp(x)


class dy_nconv(nn.Module):

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

    def forward(self, x, A):
        x = torch.einsum('ncvl,nvwl->ncwl', (x, A))
        return x.contiguous()


class dy_mixpropNew(nn.Module):

    def __init__(self, c_in, c_out, gdep, dropout, alpha):
        super(dy_mixpropNew, self).__init__()
        self.nconv = dy_nconv()
        self.mlp1 = linear((gdep + 1) * c_in, c_out)
        self.mlp2 = linear((gdep + 1) * c_in, c_out)
        self.gdep = gdep
        self.dropout = dropout
        self.alpha = alpha
        self.lin1 = linear(c_in, c_in)
        self.lin2 = linear(c_in, c_in)

    def forward(self, input_0):
        primals_6 = self.mlp1.mlp.weight
        primals_2 = self.mlp1.mlp.bias
        primals_8 = self.mlp2.mlp.weight
        primals_5 = self.mlp2.mlp.bias
        primals_1 = self.lin1.mlp.weight
        primals_7 = self.lin1.mlp.bias
        primals_4 = self.lin2.mlp.weight
        primals_9 = self.lin2.mlp.bias
        primals_3 = input_0
        output = call([primals_1, primals_2, primals_3, primals_4,
            primals_5, primals_6, primals_7, primals_8, primals_9])
        return output[0]


Measured latency_ms: 0.021611