Skip to content

Instantly share code, notes, and snippets.

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
0x0000: ffff ffff ffff 08be ac02 fa75 0800 4500 ...........u..E.
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 ................
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
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
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
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)
# 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
# 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
# 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
This file has been truncated, but you can view the full file.
<!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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
# 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