# 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_8/inductor_cache/7i/c7ie5z5gkvggaw4eftbzxjyfxmnzr2dlnul2lhesydf52egofgee.py
# Topologically Sorted Source Nodes: [cat], Original ATen: [aten.cat]
# Source node to ATen node mapping:
#   cat => cat
# Graph fragment:
#   %cat : [num_users=1] = call_function[target=torch.ops.aten.cat.default](args = ([%index, %index_1, %index_2, %index_3],), kwargs = {})
triton_poi_fused_cat_0 = async_compile.triton('triton_poi_fused_cat_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=[16], 
    filename=__file__,
    triton_meta={'signature': {0: '*i64', 1: '*i64', 2: '*i64', 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_cat_0', 'mutated_arg_names': [], 'no_x_dim': False, 'num_load': 4, '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_cat_0(in_ptr0, in_ptr1, out_ptr0, xnumel, XBLOCK : tl.constexpr):
    xnumel = 16
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tmp1 = tl.full([1], 0, tl.int64)
    tmp2 = tmp0 >= tmp1
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + (x0), tmp4 & xmask, eviction_policy='evict_last', other=0.0)
    tmp6 = tl.full([XBLOCK], 4, tl.int32)
    tmp7 = tmp5 + tmp6
    tmp8 = tmp5 < 0
    tmp9 = tl.where(tmp8, tmp7, tmp5)
    tl.device_assert(((0 <= tl.broadcast_to(tmp9, [XBLOCK])) & (tl.broadcast_to(tmp9, [XBLOCK]) < 4)) | ~(tmp4 & xmask), "index out of bounds: 0 <= tl.broadcast_to(tmp9, [XBLOCK]) < 4")
    tmp11 = tl.load(in_ptr1 + (tl.broadcast_to(tmp9, [XBLOCK])), tmp4 & xmask, eviction_policy='evict_last', other=0.0)
    tmp12 = tmp0 >= tmp3
    tmp13 = tl.full([1], 8, tl.int64)
    tmp14 = tmp0 < tmp13
    tmp15 = tmp12 & tmp14
    tmp16 = tl.load(in_ptr0 + (4 + ((-4) + x0)), tmp15 & xmask, eviction_policy='evict_last', other=0.0)
    tmp17 = tmp16 + tmp6
    tmp18 = tmp16 < 0
    tmp19 = tl.where(tmp18, tmp17, tmp16)
    tl.device_assert(((0 <= tl.broadcast_to(tmp19, [XBLOCK])) & (tl.broadcast_to(tmp19, [XBLOCK]) < 4)) | ~(tmp15 & xmask), "index out of bounds: 0 <= tl.broadcast_to(tmp19, [XBLOCK]) < 4")
    tmp21 = tl.load(in_ptr1 + (tl.broadcast_to(4 + tmp19, [XBLOCK])), tmp15 & xmask, eviction_policy='evict_last', other=0.0)
    tmp22 = tmp0 >= tmp13
    tmp23 = tl.full([1], 12, tl.int64)
    tmp24 = tmp0 < tmp23
    tmp25 = tmp22 & tmp24
    tmp26 = tl.load(in_ptr0 + (8 + ((-8) + x0)), tmp25 & xmask, eviction_policy='evict_last', other=0.0)
    tmp27 = tmp26 + tmp6
    tmp28 = tmp26 < 0
    tmp29 = tl.where(tmp28, tmp27, tmp26)
    tl.device_assert(((0 <= tl.broadcast_to(tmp29, [XBLOCK])) & (tl.broadcast_to(tmp29, [XBLOCK]) < 4)) | ~(tmp25 & xmask), "index out of bounds: 0 <= tl.broadcast_to(tmp29, [XBLOCK]) < 4")
    tmp31 = tl.load(in_ptr1 + (tl.broadcast_to(8 + tmp29, [XBLOCK])), tmp25 & xmask, eviction_policy='evict_last', other=0.0)
    tmp32 = tmp0 >= tmp23
    tmp33 = tl.full([1], 16, tl.int64)
    tmp34 = tmp0 < tmp33
    tmp35 = tl.load(in_ptr0 + (12 + ((-12) + x0)), tmp32 & xmask, eviction_policy='evict_last', other=0.0)
    tmp36 = tmp35 + tmp6
    tmp37 = tmp35 < 0
    tmp38 = tl.where(tmp37, tmp36, tmp35)
    tl.device_assert(((0 <= tl.broadcast_to(tmp38, [XBLOCK])) & (tl.broadcast_to(tmp38, [XBLOCK]) < 4)) | ~(tmp32 & xmask), "index out of bounds: 0 <= tl.broadcast_to(tmp38, [XBLOCK]) < 4")
    tmp40 = tl.load(in_ptr1 + (tl.broadcast_to(12 + tmp38, [XBLOCK])), tmp32 & xmask, eviction_policy='evict_last', other=0.0)
    tmp41 = tl.where(tmp25, tmp31, tmp40)
    tmp42 = tl.where(tmp15, tmp21, tmp41)
    tmp43 = tl.where(tmp4, tmp11, tmp42)
    tl.store(out_ptr0 + (x0), tmp43, 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, 1))
    assert_size_stride(arg1_1, (4, 4), (4, 1))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((16, ), (1, ), torch.int64)
        # Topologically Sorted Source Nodes: [cat], Original ATen: [aten.cat]
        stream0 = get_raw_stream(0)
        triton_poi_fused_cat_0.run(arg1_1, arg0_1, buf0, 16, grid=grid(16), stream=stream0)
        del arg0_1
        del arg1_1
    return (buf0, )


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, 1), device='cuda:0', dtype=torch.int64)
    arg1_1 = rand_strided((4, 4), (4, 1), device='cuda:0', dtype=torch.int64)
    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
import torch.utils.dlpack


class OutputLayer(nn.Module):

    def __init__(self, voxel_size=1.0):
        super(OutputLayer, self).__init__()

    def forward(self, features_list, index_map_list):
        out = []
        for feat, index_map in zip(features_list, index_map_list):
            out.append(feat[index_map])
        return torch.cat(out, 0)


def get_inputs():
    return [torch.ones([4, 4], dtype=torch.int64), torch.ones([4, 4], dtype
        =torch.int64)]


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
import torch.utils.dlpack
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 = 16
    xoffset = tl.program_id(0) * XBLOCK
    xindex = xoffset + tl.arange(0, XBLOCK)[:]
    xmask = xindex < xnumel
    x0 = xindex
    tmp0 = x0
    tl.full([1], 0, tl.int64)
    tmp3 = tl.full([1], 4, tl.int64)
    tmp4 = tmp0 < tmp3
    tmp5 = tl.load(in_ptr0 + x0, tmp4 & xmask, eviction_policy='evict_last',
        other=0.0)
    tmp6 = tl.full([XBLOCK], 4, tl.int32)
    tmp7 = tmp5 + tmp6
    tmp8 = tmp5 < 0
    tmp9 = tl.where(tmp8, tmp7, tmp5)
    tl.device_assert((0 <= tl.broadcast_to(tmp9, [XBLOCK])) & (tl.
        broadcast_to(tmp9, [XBLOCK]) < 4) | ~(tmp4 & xmask),
        'index out of bounds: 0 <= tl.broadcast_to(tmp9, [XBLOCK]) < 4')
    tmp11 = tl.load(in_ptr1 + tl.broadcast_to(tmp9, [XBLOCK]), tmp4 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp12 = tmp0 >= tmp3
    tmp13 = tl.full([1], 8, tl.int64)
    tmp14 = tmp0 < tmp13
    tmp15 = tmp12 & tmp14
    tmp16 = tl.load(in_ptr0 + (4 + (-4 + x0)), tmp15 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp17 = tmp16 + tmp6
    tmp18 = tmp16 < 0
    tmp19 = tl.where(tmp18, tmp17, tmp16)
    tl.device_assert((0 <= tl.broadcast_to(tmp19, [XBLOCK])) & (tl.
        broadcast_to(tmp19, [XBLOCK]) < 4) | ~(tmp15 & xmask),
        'index out of bounds: 0 <= tl.broadcast_to(tmp19, [XBLOCK]) < 4')
    tmp21 = tl.load(in_ptr1 + tl.broadcast_to(4 + tmp19, [XBLOCK]), tmp15 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp22 = tmp0 >= tmp13
    tmp23 = tl.full([1], 12, tl.int64)
    tmp24 = tmp0 < tmp23
    tmp25 = tmp22 & tmp24
    tmp26 = tl.load(in_ptr0 + (8 + (-8 + x0)), tmp25 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp27 = tmp26 + tmp6
    tmp28 = tmp26 < 0
    tmp29 = tl.where(tmp28, tmp27, tmp26)
    tl.device_assert((0 <= tl.broadcast_to(tmp29, [XBLOCK])) & (tl.
        broadcast_to(tmp29, [XBLOCK]) < 4) | ~(tmp25 & xmask),
        'index out of bounds: 0 <= tl.broadcast_to(tmp29, [XBLOCK]) < 4')
    tmp31 = tl.load(in_ptr1 + tl.broadcast_to(8 + tmp29, [XBLOCK]), tmp25 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp32 = tmp0 >= tmp23
    tl.full([1], 16, tl.int64)
    tmp35 = tl.load(in_ptr0 + (12 + (-12 + x0)), tmp32 & xmask,
        eviction_policy='evict_last', other=0.0)
    tmp36 = tmp35 + tmp6
    tmp37 = tmp35 < 0
    tmp38 = tl.where(tmp37, tmp36, tmp35)
    tl.device_assert((0 <= tl.broadcast_to(tmp38, [XBLOCK])) & (tl.
        broadcast_to(tmp38, [XBLOCK]) < 4) | ~(tmp32 & xmask),
        'index out of bounds: 0 <= tl.broadcast_to(tmp38, [XBLOCK]) < 4')
    tmp40 = tl.load(in_ptr1 + tl.broadcast_to(12 + tmp38, [XBLOCK]), tmp32 &
        xmask, eviction_policy='evict_last', other=0.0)
    tmp41 = tl.where(tmp25, tmp31, tmp40)
    tmp42 = tl.where(tmp15, tmp21, tmp41)
    tmp43 = tl.where(tmp4, tmp11, tmp42)
    tl.store(out_ptr0 + x0, tmp43, xmask)


def call(args):
    arg0_1, arg1_1 = args
    args.clear()
    assert_size_stride(arg0_1, (4, 4), (4, 1))
    assert_size_stride(arg1_1, (4, 4), (4, 1))
    with torch.cuda._DeviceGuard(0):
        torch.cuda.set_device(0)
        buf0 = empty_strided_cuda((16,), (1,), torch.int64)
        get_raw_stream(0)
        triton_poi_fused_cat_0[grid(16)](arg1_1, arg0_1, buf0, 16, XBLOCK=
            16, num_warps=1, num_stages=1)
        del arg0_1
        del arg1_1
    return buf0,


class OutputLayerNew(nn.Module):

    def __init__(self, voxel_size=1.0):
        super(OutputLayerNew, self).__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]
