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[50/67] g++-12 -MMD -MF /tmp/pip-req-build-y8fv0d6c/build/temp.linux-x86_64-3.11/tmp/pip-req-build-y8fv0d6c/pytorch3d/csrc/
pulsar/host/renderer.norm_sphere_gradients.cpu.o.d -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -DWITH_CUDA -DTHRUST_IGNORE
_CUB_VERSION_CHECK -I/tmp/pip-req-build-y8fv0d6c/pytorch3d/csrc -I/home/rice/venvs/torchdrive3.11/lib/python3.11/site-packages/to
rch/include -I/home/rice/venvs/torchdrive3.11/lib/python3.11/site-packages/torch/include/torch/csrc/api/include -I/home/rice/venv
s/torchdrive3.11/lib/python3.11/site-packages/torch/include/TH -I/home/rice/venvs/torchdrive3.11/lib/python3.11/site-packages/tor
ch/include/THC -I/opt/cuda/include -I/home/rice/venvs/torchdrive3.11/include -I/home/rice/.pyenv/versions/3.11.4/include/python3.
11 -c -c /tmp/pip-req-build-y8fv0d6c/pytorch3d/csrc/pulsar/host/renderer.norm_sphere_gradients.cpu.cpp -o /tmp/pip-req-build-y8fv
0d6c/build/temp.linux-x86_64-3.11/tmp/pip-req-build-y8fv0d6c/pytorch3d/csrc/pulsar/host/renderer.norm_sphere_gradi
============================= test session starts ==============================
platform linux -- Python 3.11.4, pytest-7.4.2, pluggy-1.3.0
rootdir: /mnt/ext/torchdrive
plugins: anyio-4.0.0, typeguard-2.13.3, xdist-3.3.1
collected 2 items / 1 deselected / 1 selected
torchworld/transforms/test_sfm.py F [100%]
=================================== FAILURES ===================================
_____________________________ TestSFM.test_export ______________________________
Traceback (most recent call last):
File "/home/rice/Developer/test_torch_export.py", line 11, in <module>
compiled = export(foo, args=tuple())
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/rice/Developer/pytorch/torch/export/__init__.py", line 440, in export
return export__RC__(f, args, kwargs, dynamic_shapes=dynamic_shapes)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/rice/Developer/pytorch/torch/_export/__init__.py", line 252, in export__RC__
return _export(f, args, kwargs, constraints=constraints)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@d4l3k
d4l3k / LICENSE
Created February 17, 2023 18:03
A pytorch implementation of torch_gather_nd with multiple batch dim and multiple channel dim support.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
https://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and limitations under the License.
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""
For distributed training, TorchX relies on the scheduler's gang scheduling
capabilities to schedule ``n`` copies of nodes. Once launched, the application
is expected to be written in a way that leverages this topology, for instance,
@d4l3k
d4l3k / load_kallsyms.py
Last active December 29, 2020 02:58
Ghidra script to load kallsyms as labels
# load a kallsyms table
#@author d4l3k
#@category kernelscripts
USER_DEFINED = ghidra.program.model.symbol.SourceType.USER_DEFINED
baseAddress = currentProgram.getImageBase()
print("base address", baseAddress)

Mounting LVM partition from disk image

$ sudo losetup /dev/loop0 ./MTFC64GJVDN-4M_1BIT@LFBGA169_3731.BIN
$ sudo partx --update /dev/loop0
$ sudo lvmdiskscan
  /dev/nvme0n1         [    <476.94 GiB]
  /dev/loop0           [      59.28 GiB]
  /dev/mapper/cryptlvm [    <237.13 GiB] LVM physical volume
  /dev/nvme0n1p1       [     100.00 MiB]
package main
import (
"archive/zip"
"io"
"log"
"os"
"path/filepath"
"strings"
@d4l3k
d4l3k / ap.fbs
Last active June 15, 2020 06:03
Autopilot neural network weights flatbuffer schema file from Tesla Model 3 - version 2018.32.6
namespace fbs.ap;
table Root {
layers : [Layer];
}
table Layer {
name: string;
weights : [Weights];
}
package main
import (
"bytes"
"encoding/binary"
"flag"
"io"
"io/ioutil"
"log"
"os"