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11:28:49.532232 IP 192.168.1.153.68 > 255.255.255.255.67: BOOTP/DHCP, Request from 08:be:ac:02:fa:75, length 247 | |
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0x0010: 0113 45c7 4000 4011 31d2 c0a8 0199 ffff ..E.@.@.1....... | |
0x0020: ffff 0044 0043 00ff b707 0101 0600 cf84 ...D.C.......... | |
0x0030: 1142 0000 0000 0000 0000 0000 0000 0000 .B.............. | |
0x0040: 0000 0000 0000 08be ac02 fa75 0000 0000 ...........u.... | |
0x0050: 0000 0000 0000 0000 0000 0000 0000 0000 ................ | |
0x0060: 0000 0000 0000 0000 0000 0000 0000 0000 ................ | |
0x0070: 0000 0000 0000 0000 0000 0000 0000 0000 ................ | |
0x0080: 0000 0000 0000 0000 0000 0000 0000 0000 ................ |
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llvm dialect: | |
module attributes {"triton_gpu.compute-capability" = 90 : i32, "triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 : i32, triton_gpu.shared = 0 : i32, "triton_gpu.threads-per-warp" = 32 : i32} { | |
llvm.mlir.global external @global_smem() {addr_space = 3 : i32, alignment = 16 : i64} : !llvm.array<0 x i8> | |
llvm.func @pointwise_fn(%arg0: !llvm.ptr<1>, %arg1: !llvm.ptr<1>, %arg2: !llvm.ptr<1>, %arg3: i32) attributes {noinline = false, nvvm.kernel = 1 : ui1, nvvm.maxntid = array<i32: 128>} { | |
%0 = llvm.mlir.constant(true) : i1 | |
%1 = llvm.mlir.constant(0 : i32) : i32 | |
%2 = llvm.mlir.constant(1 : i32) : i32 | |
%3 = llvm.mlir.constant(0 : index) : i32 | |
%4 = llvm.mlir.constant(32 : i32) : i32 | |
%5 = llvm.inline_asm asm_dialect = att operand_attrs = [] "mov.u32 $0, %ctaid.x;", "=r" : () -> i32 |
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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 | |
from torch._dynamo.testing import rand_strided |
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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 | |
from torch._dynamo.testing import rand_strided |
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import torch | |
import torch._inductor.config as inductor_config | |
inductor_config.optimize_scatter_upon_const_tensor = False | |
torch.set_default_device("cuda") | |
M, N = 1024, 2048 | |
x = torch.randint(0, N, (M,), dtype=torch.int64) |
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# AOT ID: ['0_backward'] | |
from ctypes import c_void_p, c_long | |
import torch | |
import math | |
import random | |
import os | |
import tempfile | |
from math import inf, nan | |
from torch._inductor.hooks import run_intermediate_hooks |
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# AOT ID: ['0_backward'] | |
from ctypes import c_void_p, c_long | |
import torch | |
import math | |
import random | |
import os | |
import tempfile | |
from math import inf, nan | |
from torch._inductor.hooks import run_intermediate_hooks |
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# AOT ID: ['0_inference'] | |
from ctypes import c_void_p, c_long | |
import torch | |
import math | |
import random | |
import os | |
import tempfile | |
from math import inf, nan | |
from torch._inductor.hooks import run_intermediate_hooks |
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<!DOCTYPE html> | |
<html> | |
<head> | |
</head> | |
<body> | |
<script type="module"> | |
import {add_local_files} from "https://cdn.jsdelivr.net/gh/pytorch/pytorch@main/torch/utils/viz/MemoryViz.js" | |
const local_files = [{"name": "snapshot.pickle", "base64": "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 |
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# AOT ID: ['0_backward'] | |
from ctypes import c_void_p, c_long | |
import torch | |
import math | |
import random | |
import os | |
import tempfile | |
from math import inf, nan | |
from torch._inductor.hooks import run_intermediate_hooks |
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