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1) Hermetic CUDA rules allow building wheels with GPU support on a machine without GPUs, as well as running Bazel GPU tests on a machine with only GPUs and NVIDIA driver installed. When `--config=cuda` is provided in Bazel options, Bazel will download CUDA, CUDNN and NCCL redistributions in the cache, and use them during build and test phases.
[Default location of CUNN redistributions](https://developer.download.nvidia.com/compute/cudnn/redist/)
[Default location of CUDA redistributions](https://developer.download.nvidia.com/compute/cuda/redist/)
[Default location of NCCL redistributions](https://pypi.org/project/nvidia-nccl-cu12/#history)
2) To include hermetic CUDA rules in your project, add the following in the WORKSPACE of the downstream project dependent on XLA.
Note: use `@local_tsl` instead of `@tsl` in Tensorflow project.
```
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_json_init_repository.bzl",
"cuda_json_init_repository",
)
cuda_json_init_repository()
load(
"@cuda_redist_json//:distributions.bzl",
"CUDA_REDISTRIBUTIONS",
"CUDNN_REDISTRIBUTIONS",
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_redist_init_repositories.bzl",
"cuda_redist_init_repositories",
"cudnn_redist_init_repository",
)
cuda_redist_init_repositories(
cuda_redistributions = CUDA_REDISTRIBUTIONS,
)
cudnn_redist_init_repository(
cudnn_redistributions = CUDNN_REDISTRIBUTIONS,
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_configure.bzl",
"cuda_configure",
)
cuda_configure(name = "local_config_cuda")
load(
"@tsl//third_party/nccl/hermetic:nccl_redist_init_repository.bzl",
"nccl_redist_init_repository",
)
nccl_redist_init_repository()
load(
"@tsl//third_party/nccl/hermetic:nccl_configure.bzl",
"nccl_configure",
)
nccl_configure(name = "local_config_nccl")
```
PiperOrigin-RevId: 662981325
92 lines
3.0 KiB
Python
92 lines
3.0 KiB
Python
# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Verifies that a list of libraries is installed on the system.
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NB: DEPRECATED! This script is a part of the deprecated `cuda_configure` rule.
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Please use `hermetic/cuda_configure` instead.
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Takes a list of arguments with every two subsequent arguments being a logical
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tuple of (path, check_soname). The path to the library and either True or False
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to indicate whether to check the soname field on the shared library.
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Example Usage:
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./check_cuda_libs.py /path/to/lib1.so True /path/to/lib2.so False
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"""
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import os
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import os.path
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import platform
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import subprocess
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import sys
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# pylint: disable=g-import-not-at-top,g-importing-member
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try:
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from shutil import which
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except ImportError:
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from distutils.spawn import find_executable as which
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# pylint: enable=g-import-not-at-top,g-importing-member
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class ConfigError(Exception):
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pass
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def _is_windows():
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return platform.system() == "Windows"
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def check_cuda_lib(path, check_soname=True):
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"""Tests if a library exists on disk and whether its soname matches the filename.
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Args:
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path: the path to the library.
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check_soname: whether to check the soname as well.
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Raises:
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ConfigError: If the library does not exist or if its soname does not match
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the filename.
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"""
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if not os.path.isfile(path):
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raise ConfigError("No library found under: " + path)
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objdump = which("objdump")
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if check_soname and objdump is not None and not _is_windows():
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# Decode is necessary as in py3 the return type changed from str to bytes
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output = subprocess.check_output([objdump, "-p", path]).decode("utf-8")
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output = [line for line in output.splitlines() if "SONAME" in line]
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sonames = [line.strip().split(" ")[-1] for line in output]
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if not any(soname == os.path.basename(path) for soname in sonames):
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raise ConfigError("None of the libraries match their SONAME: " + path)
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def main():
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try:
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args = [argv for argv in sys.argv[1:]]
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if len(args) % 2 == 1:
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raise ConfigError("Expected even number of arguments")
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checked_paths = []
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for i in range(0, len(args), 2):
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path = args[i]
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check_cuda_lib(path, check_soname=args[i + 1] == "True")
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checked_paths.append(path)
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# pylint: disable=superfluous-parens
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print(os.linesep.join(checked_paths))
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# pylint: enable=superfluous-parens
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except ConfigError as e:
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sys.stderr.write(str(e))
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sys.exit(1)
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if __name__ == "__main__":
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main()
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