# AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _align as align
from torch import device, empty_strided
from torch._inductor.async_compile import AsyncCompile
from torch._inductor.select_algorithm import extern_kernels
from torch._inductor.codegen.multi_kernel import MultiKernelCall
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid, split_scan_grid, grid_combo_kernels, start_graph, end_graph
from torch._C import _cuda_getCurrentRawStream as get_raw_stream

aten = torch.ops.aten
inductor_ops = torch.ops.inductor
_quantized = torch.ops._quantized
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cpu = torch._C._dynamo.guards._empty_strided_cpu
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
empty_strided_xpu = torch._C._dynamo.guards._empty_strided_xpu
reinterpret_tensor = torch._C._dynamo.guards._reinterpret_tensor
alloc_from_pool = torch.ops.inductor._alloc_from_pool
async_compile = AsyncCompile()


# kernel path: runs/run_shard_4/inductor_cache/df/cdf44hoqxi5iqenpbwcrawtackxxbo2leg7ntrbcx4c4yv73xeog.py
# Topologically Sorted Source Nodes: [iadd, mul_1, iadd_1, mul_2, iadd_2, mul_3, iadd_3], Original ATen: [aten.add, aten.mul]
# Source node to ATen node mapping:
#   iadd => mul
#   iadd_1 => add_1
#   iadd_2 => add_2
#   iadd_3 => add_3
#   mul_1 => mul_1
#   mul_2 => mul_2
#   mul_3 => mul_3
# Graph fragment:
#   %mul : [num_users=2] = call_function[target=torch.ops.aten.mul.Tensor](args = (%slice_5, %arg0_1), kwargs = {})
#   %mul_1 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%slice_33, %slice_37), kwargs = {})
#   %add_1 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%slice_41, %mul_1), kwargs = {})
#   %slice_scatter_default : [num_users=3] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%mul, %add_1, 3, 0, 3), kwargs = {})
#   %slice_scatter_default_1 : [num_users=2] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%slice_scatter_default, %slice_48, 3, 0, 3), kwargs = {})
#   %mul_2 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%slice_71, %slice_75), kwargs = {})
#   %add_2 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%slice_79, %mul_2), kwargs = {})
#   %slice_scatter_default_2 : [num_users=3] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%slice_scatter_default_1, %add_2, 3, 0, 2), kwargs = {})
#   %slice_scatter_default_3 : [num_users=2] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%slice_scatter_default_2, %slice_86, 3, 0, 2), kwargs = {})
#   %mul_3 : [num_users=1] = call_function[target=torch.ops.aten.mul.Tensor](args = (%slice_109, %slice_113), kwargs = {})
#   %add_3 : [num_users=1] = call_function[target=torch.ops.aten.add.Tensor](args = (%slice_117, %mul_3), kwargs = {})
#   %slice_scatter_default_4 : [num_users=3] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%slice_scatter_default_3, %add_3, 3, 0, 1), kwargs = {})
#   %slice_scatter_default_5 : [num_users=1] = call_function[target=torch.ops.aten.slice_scatter.default](args = (%slice_scatter_default_4, %slice_124, 3, 0, 1), kwargs = {})
triton_poi_fused_add_mul_0 = async_compile.triton('triton_poi_fused_add_mul_0', '''
import triton
import triton.language as tl
from triton.compiler.compiler import AttrsDescriptor

from torch._inductor.runtime import triton_helpers, triton_heuristics
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch._inductor.runtime.hints import AutotuneHint, ReductionHint, TileHint, instance_descriptor, DeviceProperties

@triton_heuristics.pointwise(
    size_hints=[256], 
    filename=__file__,
    triton_meta={'signature': {0: '*fp32', 1: '*fp32', 2: '*fp32', 3: 'i32'}, 'device': DeviceProperties(type='cuda', index=0, cc=80, major=8, regs_per_multiprocessor=65536, max_threads_per_multi_processor=2048, multi_processor_count=108), 'constants': {}, 'configs': [AttrsDescriptor(divisible_by_16=(0, 1, 2, 3), equal_to_1=())]},
    inductor_meta={'autotune_hints': set(), 'kernel_name': 'triton_poi_fused_add_mul_0', 'mutated_arg_names': ['in_out_ptr0'], 'no_x_dim': False, 'num_load': 26, 'num_reduction': 0, 'backend_hash': 'A9C866B4A14FD3277824029365D703C2427B2E685E54EC9B3EF4ADC8D1EEAC1D', 'are_deterministic_algorithms_enabled': False, 'assert_indirect_indexing': True, 'autotune_local_cache': True, 'autotune_pointwise': True, 'autotune_remote_cache': None, 'force_disable_caches': False, 'dynamic_scale_rblock': True, 'max_autotune': False, 'max_autotune_pointwise': False, 'min_split_scan_rblock': 256, 'spill_threshold': 16, 'store_cubin': False},
    min_elem_per_thread=0
)
@triton.jit
def triton_poi_fused_add_mul_0(in_out_ptr0, in_ptr0, in_ptr1, xnumel, XBLOCK : tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 4
    x3 = (xindex // 64)
    x4 = xindex % 16
    x5 = xindex
    x1 = (xindex // 4) % 4
    x6 = (xindex // 4)
    tmp61 = tl.load(in_ptr0 + (x4 + (64*x3)), xmask, eviction_policy='evict_last')
    tmp62 = tl.load(in_ptr1 + (x5), xmask)
    tmp0 = x0
    tmp1 = tl.full([1], 2, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = tl.full([1], 3, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tmp4 & tmp2
    tmp6 = tmp4 & tmp5
    tmp7 = tl.load(in_ptr0 + (x4 + (64*x3)), tmp6 & xmask, eviction_policy='evict_last', other=0.0)
    tmp8 = tl.load(in_ptr1 + (x5), tmp6 & xmask, other=0.0)
    tmp9 = tmp7 * tmp8
    tmp10 = tl.load(in_ptr0 + (16 + x4 + (64*x3)), tmp6 & xmask, eviction_policy='evict_last', other=0.0)
    tmp11 = tl.load(in_ptr1 + (1 + x5), tmp6 & xmask, other=0.0)
    tmp12 = tmp10 * tmp11
    tmp13 = tmp9 + tmp12
    tmp14 = tl.full(tmp13.shape, 0.0, tmp13.dtype)
    tmp15 = tl.where(tmp6, tmp13, tmp14)
    tmp16 = tl.load(in_ptr0 + (x4 + (64*x3)), tmp5 & xmask, eviction_policy='evict_last', other=0.0)
    tmp17 = tl.load(in_ptr1 + (x5), tmp5 & xmask, other=0.0)
    tmp18 = tmp16 * tmp17
    tmp19 = tl.where(tmp4, tmp15, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp5, tmp19, tmp20)
    tmp22 = tl.load(in_ptr0 + (16 + x4 + (64*x3)), tmp5 & xmask, eviction_policy='evict_last', other=0.0)
    tmp23 = tl.load(in_ptr1 + (1 + x5), tmp5 & xmask, other=0.0)
    tmp24 = tmp22 * tmp23
    tmp25 = tmp18 + tmp24
    tmp26 = tl.full(tmp25.shape, 0.0, tmp25.dtype)
    tmp27 = tl.where(tmp5, tmp25, tmp26)
    tmp28 = tl.load(in_ptr0 + (x4 + (64*x3)), tmp2 & xmask, eviction_policy='evict_last', other=0.0)
    tmp29 = tl.load(in_ptr1 + (x5), tmp2 & xmask, other=0.0)
    tmp30 = tmp28 * tmp29
    tmp31 = tl.where(tmp4, tmp27, tmp30)
    tmp32 = tl.where(tmp4, tmp21, tmp31)
    tmp33 = tl.load(in_ptr0 + (32 + x4 + (64*x3)), tmp2 & xmask, eviction_policy='evict_last', other=0.0)
    tmp34 = tl.load(in_ptr1 + (2 + x5), tmp2 & xmask, other=0.0)
    tmp35 = tmp33 * tmp34
    tmp36 = tmp32 + tmp35
    tmp37 = tl.full(tmp36.shape, 0.0, tmp36.dtype)
    tmp38 = tl.where(tmp2, tmp36, tmp37)
    tmp39 = tmp4 & tmp4
    tmp40 = tl.load(in_ptr0 + (x4 + (64*x3)), tmp39 & xmask, eviction_policy='evict_last', other=0.0)
    tmp41 = tl.load(in_ptr1 + (x5), tmp39 & xmask, other=0.0)
    tmp42 = tmp40 * tmp41
    tmp43 = tl.load(in_ptr0 + (16 + x4 + (64*x3)), tmp39 & xmask, eviction_policy='evict_last', other=0.0)
    tmp44 = tl.load(in_ptr1 + (1 + x5), tmp39 & xmask, other=0.0)
    tmp45 = tmp43 * tmp44
    tmp46 = tmp42 + tmp45
    tmp47 = tl.full(tmp46.shape, 0.0, tmp46.dtype)
    tmp48 = tl.where(tmp39, tmp46, tmp47)
    tmp49 = tl.load(in_ptr0 + (x4 + (64*x3)), tmp4 & xmask, eviction_policy='evict_last', other=0.0)
    tmp50 = tl.load(in_ptr1 + (x5), tmp4 & xmask, other=0.0)
    tmp51 = tmp49 * tmp50
    tmp52 = tl.where(tmp4, tmp48, tmp51)
    tmp53 = tl.full(tmp52.shape, 0.0, tmp52.dtype)
    tmp54 = tl.where(tmp4, tmp52, tmp53)
    tmp55 = tl.load(in_ptr0 + (16 + x4 + (64*x3)), tmp4 & xmask, eviction_policy='evict_last', other=0.0)
    tmp56 = tl.load(in_ptr1 + (1 + x5), tmp4 & xmask, other=0.0)
    tmp57 = tmp55 * tmp56
    tmp58 = tmp51 + tmp57
    tmp59 = tl.full(tmp58.shape, 0.0, tmp58.dtype)
    tmp60 = tl.where(tmp4, tmp58, tmp59)
    tmp63 = tmp61 * tmp62
    tmp64 = tl.where(tmp4, tmp60, tmp63)
    tmp65 = tl.where(tmp4, tmp54, tmp64)
    tmp66 = tl.where(tmp2, tmp38, tmp65)
    tmp67 = tl.full([1], 1, tl.int64)
    tmp68 = tmp0 < tmp67
    tmp69 = tmp68 & tmp68
    tmp70 = tmp2 & tmp69
    tmp71 = tl.where(tmp2, tmp66, tmp66)
    tmp72 = tl.load(in_ptr0 + (48 + (4*x1) + (64*x3)), tmp69 & xmask, eviction_policy='evict_last', other=0.0)
    tmp73 = tl.load(in_ptr1 + (3 + (4*x6)), tmp69 & xmask, eviction_policy='evict_last', other=0.0)
    tmp74 = tmp72 * tmp73
    tmp75 = tmp71 + tmp74
    tmp76 = tl.full(tmp75.shape, 0.0, tmp75.dtype)
    tmp77 = tl.where(tmp69, tmp75, tmp76)
    tmp78 = tmp2 & tmp68
    tmp79 = tl.where(tmp68, tmp77, tmp71)
    tmp80 = tl.full(tmp79.shape, 0.0, tmp79.dtype)
    tmp81 = tl.where(tmp68, tmp79, tmp80)
    tmp82 = tl.load(in_ptr0 + (48 + (4*x1) + (64*x3)), tmp68 & xmask, eviction_policy='evict_last', other=0.0)
    tmp83 = tl.load(in_ptr1 + (3 + (4*x6)), tmp68 & xmask, eviction_policy='evict_last', other=0.0)
    tmp84 = tmp82 * tmp83
    tmp85 = tmp71 + tmp84
    tmp86 = tl.full(tmp85.shape, 0.0, tmp85.dtype)
    tmp87 = tl.where(tmp68, tmp85, tmp86)
    tmp88 = tl.where(tmp68, tmp87, tmp71)
    tmp89 = tl.where(tmp68, tmp81, tmp88)
    tl.store(in_out_ptr0 + (x5), tmp89, xmask)
''', device_str='cuda')


async_compile.wait(globals())
del async_compile

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, 4), (64, 16, 4, 1), torch.float32)
        buf1 = buf0; del buf0  # reuse
        # Topologically Sorted Source Nodes: [iadd, mul_1, iadd_1, mul_2, iadd_2, mul_3, iadd_3], Original ATen: [aten.add, aten.mul]
        stream0 = get_raw_stream(0)
        triton_poi_fused_add_mul_0.run(buf1, arg1_1, arg0_1, 256, grid=grid(256), stream=stream0)
        del arg0_1
        del arg1_1
    return (buf1, )


def benchmark_compiled_module(times=10, repeat=10):
    from torch._dynamo.testing import rand_strided
    from torch._inductor.utils import print_performance
    arg0_1 = rand_strided((4, 4, 4, 4), (64, 16, 4, 1), device='cuda:0', dtype=torch.float32)
    arg1_1 = rand_strided((4, 4, 4, 4), (64, 16, 4, 1), device='cuda:0', dtype=torch.float32)
    fn = lambda: call([arg0_1, arg1_1])
    return print_performance(fn, times=times, repeat=repeat)


if __name__ == "__main__":
    from torch._inductor.wrapper_benchmark import compiled_module_main
    compiled_module_main('None', benchmark_compiled_module)

import torch
import torch.nn as nn


class dense_warp(nn.Module):

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

    def forward(self, h1, cost):
        g2 = torch.zeros_like(h1)
        clone_h1 = h1.detach()
        if h1.device.type == 'cuda':
            g2 = g2
            clone_h1 = clone_h1
        for d in range(cost.size()[-3]):
            g2[:, :, :, 0:cost.size()[-1] - d] += cost[:, d:d + 1, :, 0:
                cost.size()[-1] - d].mul(clone_h1[:, :, :, d:cost.size()[-1]])
        return g2


def get_inputs():
    return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]


def get_init_inputs():
    return [[], {}]

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_add_mul_0(in_out_ptr0, in_ptr0, in_ptr1, xnumel,
    XBLOCK: tl.constexpr):
    xnumel = 256
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex % 4
    x3 = xindex // 64
    x4 = xindex % 16
    x5 = xindex
    x1 = xindex // 4 % 4
    x6 = xindex // 4
    tmp61 = tl.load(in_ptr0 + (x4 + 64 * x3), xmask, eviction_policy=
        'evict_last')
    tmp62 = tl.load(in_ptr1 + x5, xmask)
    tmp0 = x0
    tmp1 = tl.full([1], 2, tl.int64)
    tmp2 = tmp0 < tmp1
    tmp3 = tl.full([1], 3, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tmp4 & tmp2
    tmp6 = tmp4 & tmp5
    tmp7 = tl.load(in_ptr0 + (x4 + 64 * x3), tmp6 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp8 = tl.load(in_ptr1 + x5, tmp6 & xmask, other=0.0)
    tmp9 = tmp7 * tmp8
    tmp10 = tl.load(in_ptr0 + (16 + x4 + 64 * x3), tmp6 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp11 = tl.load(in_ptr1 + (1 + x5), tmp6 & xmask, other=0.0)
    tmp12 = tmp10 * tmp11
    tmp13 = tmp9 + tmp12
    tmp14 = tl.full(tmp13.shape, 0.0, tmp13.dtype)
    tmp15 = tl.where(tmp6, tmp13, tmp14)
    tmp16 = tl.load(in_ptr0 + (x4 + 64 * x3), tmp5 & xmask, eviction_policy
        ='evict_last', other=0.0)
    tmp17 = tl.load(in_ptr1 + x5, tmp5 & xmask, other=0.0)
    tmp18 = tmp16 * tmp17
    tmp19 = tl.where(tmp4, tmp15, tmp18)
    tmp20 = tl.full(tmp19.shape, 0.0, tmp19.dtype)
    tmp21 = tl.where(tmp5, tmp19, tmp20)
    tmp22 = tl.load(in_ptr0 + (16 + x4 + 64 * x3), tmp5 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp23 = tl.load(in_ptr1 + (1 + x5), tmp5 & xmask, other=0.0)
    tmp24 = tmp22 * tmp23
    tmp25 = tmp18 + tmp24
    tmp26 = tl.full(tmp25.shape, 0.0, tmp25.dtype)
    tmp27 = tl.where(tmp5, tmp25, tmp26)
    tmp28 = tl.load(in_ptr0 + (x4 + 64 * x3), tmp2 & xmask, eviction_policy
        ='evict_last', other=0.0)
    tmp29 = tl.load(in_ptr1 + x5, tmp2 & xmask, other=0.0)
    tmp30 = tmp28 * tmp29
    tmp31 = tl.where(tmp4, tmp27, tmp30)
    tmp32 = tl.where(tmp4, tmp21, tmp31)
    tmp33 = tl.load(in_ptr0 + (32 + x4 + 64 * x3), tmp2 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp34 = tl.load(in_ptr1 + (2 + x5), tmp2 & xmask, other=0.0)
    tmp35 = tmp33 * tmp34
    tmp36 = tmp32 + tmp35
    tmp37 = tl.full(tmp36.shape, 0.0, tmp36.dtype)
    tmp38 = tl.where(tmp2, tmp36, tmp37)
    tmp39 = tmp4 & tmp4
    tmp40 = tl.load(in_ptr0 + (x4 + 64 * x3), tmp39 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp41 = tl.load(in_ptr1 + x5, tmp39 & xmask, other=0.0)
    tmp42 = tmp40 * tmp41
    tmp43 = tl.load(in_ptr0 + (16 + x4 + 64 * x3), tmp39 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp44 = tl.load(in_ptr1 + (1 + x5), tmp39 & xmask, other=0.0)
    tmp45 = tmp43 * tmp44
    tmp46 = tmp42 + tmp45
    tmp47 = tl.full(tmp46.shape, 0.0, tmp46.dtype)
    tmp48 = tl.where(tmp39, tmp46, tmp47)
    tmp49 = tl.load(in_ptr0 + (x4 + 64 * x3), tmp4 & xmask, eviction_policy
        ='evict_last', other=0.0)
    tmp50 = tl.load(in_ptr1 + x5, tmp4 & xmask, other=0.0)
    tmp51 = tmp49 * tmp50
    tmp52 = tl.where(tmp4, tmp48, tmp51)
    tmp53 = tl.full(tmp52.shape, 0.0, tmp52.dtype)
    tmp54 = tl.where(tmp4, tmp52, tmp53)
    tmp55 = tl.load(in_ptr0 + (16 + x4 + 64 * x3), tmp4 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp56 = tl.load(in_ptr1 + (1 + x5), tmp4 & xmask, other=0.0)
    tmp57 = tmp55 * tmp56
    tmp58 = tmp51 + tmp57
    tmp59 = tl.full(tmp58.shape, 0.0, tmp58.dtype)
    tmp60 = tl.where(tmp4, tmp58, tmp59)
    tmp63 = tmp61 * tmp62
    tmp64 = tl.where(tmp4, tmp60, tmp63)
    tmp65 = tl.where(tmp4, tmp54, tmp64)
    tmp66 = tl.where(tmp2, tmp38, tmp65)
    tmp67 = tl.full([1], 1, tl.int64)
    tmp68 = tmp0 < tmp67
    tmp69 = tmp68 & tmp68
    tmp2 & tmp69
    tmp71 = tl.where(tmp2, tmp66, tmp66)
    tmp72 = tl.load(in_ptr0 + (48 + 4 * x1 + 64 * x3), tmp69 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp73 = tl.load(in_ptr1 + (3 + 4 * x6), tmp69 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp74 = tmp72 * tmp73
    tmp75 = tmp71 + tmp74
    tmp76 = tl.full(tmp75.shape, 0.0, tmp75.dtype)
    tmp77 = tl.where(tmp69, tmp75, tmp76)
    tmp2 & tmp68
    tmp79 = tl.where(tmp68, tmp77, tmp71)
    tmp80 = tl.full(tmp79.shape, 0.0, tmp79.dtype)
    tmp81 = tl.where(tmp68, tmp79, tmp80)
    tmp82 = tl.load(in_ptr0 + (48 + 4 * x1 + 64 * x3), tmp68 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp83 = tl.load(in_ptr1 + (3 + 4 * x6), tmp68 & xmask, eviction_policy=
        'evict_last', other=0.0)
    tmp84 = tmp82 * tmp83
    tmp85 = tmp71 + tmp84
    tmp86 = tl.full(tmp85.shape, 0.0, tmp85.dtype)
    tmp87 = tl.where(tmp68, tmp85, tmp86)
    tmp88 = tl.where(tmp68, tmp87, tmp71)
    tmp89 = tl.where(tmp68, tmp81, tmp88)
    tl.store(in_out_ptr0 + x5, tmp89, 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, 4, 4, 4), (64, 16, 4, 1), torch.float32)
        buf1 = buf0
        del buf0
        get_raw_stream(0)
        triton_poi_fused_add_mul_0[grid(256)](buf1, arg1_1, arg0_1, 256,
            XBLOCK=128, num_warps=4, num_stages=1)
        del arg0_1
        del arg1_1
    return buf1,


class dense_warpNew(nn.Module):

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

    def forward(self, input_0, input_1):
        arg0_1 = input_0
        arg1_1 = input_1
        output = call([arg0_1, arg1_1])
        return output[0]
