$ 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]
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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 |
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============================= 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 ______________________________ |
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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) | |
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ |
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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. |
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# 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, |
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# load a kallsyms table | |
#@author d4l3k | |
#@category kernelscripts | |
USER_DEFINED = ghidra.program.model.symbol.SourceType.USER_DEFINED | |
baseAddress = currentProgram.getImageBase() | |
print("base address", baseAddress) |
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package main | |
import ( | |
"archive/zip" | |
"io" | |
"log" | |
"os" | |
"path/filepath" | |
"strings" |
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namespace fbs.ap; | |
table Root { | |
layers : [Layer]; | |
} | |
table Layer { | |
name: string; | |
weights : [Weights]; | |
} |
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package main | |
import ( | |
"bytes" | |
"encoding/binary" | |
"flag" | |
"io" | |
"io/ioutil" | |
"log" | |
"os" |
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