df1ee5d551
Since this module now generates a dictionary to expose in tf.config, it doesn't make much sense to store only certain values in the build_info dictionary and others as module variables. This obsoletes a lot of code in gen_build_info.py and I've removed it. I also updated all the in-code references I've found to the build_info module. I think this may break whomever used to be using the build_info library, but since it wasn't part of the API, there was no guarantee that it would continue to be available.
115 lines
3.9 KiB
Python
Executable File
115 lines
3.9 KiB
Python
Executable File
# Lint as: python3
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# Copyright 2017 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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"""Generates a Python module containing information about the build."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import argparse
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import os
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import platform
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import sys
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import six
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from third_party.gpus import find_cuda_config
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def write_build_info(filename, key_value_list):
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"""Writes a Python that describes the build.
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Args:
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filename: filename to write to.
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key_value_list: A list of "key=value" strings that will be added to the
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module's "build_info" dictionary as additional entries.
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"""
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build_info = {}
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for arg in key_value_list:
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key, value = six.ensure_str(arg).split("=")
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if value.lower() == "true":
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build_info[key] = True
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elif value.lower() == "false":
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build_info[key] = False
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else:
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build_info[key] = value
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# Generate cuda_build_info, a dict describing the CUDA component versions
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# used to build TensorFlow.
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if build_info.get("is_cuda_build", False):
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libs = ["_", "cuda", "cudnn"]
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if platform.system() == "Linux":
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if os.environ.get("TF_NEED_TENSORRT", "0") == "1":
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libs.append("tensorrt")
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if "TF_NCCL_VERSION" in os.environ:
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libs.append("nccl")
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# find_cuda_config accepts libraries to inspect as argv from the command
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# line. We can work around this restriction by setting argv manually
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# before calling find_cuda_config.
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backup_argv = sys.argv
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sys.argv = libs
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cuda = find_cuda_config.find_cuda_config()
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build_info["cuda_version"] = cuda["cuda_version"]
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build_info["cudnn_version"] = cuda["cudnn_version"]
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build_info["tensorrt_version"] = cuda.get("tensorrt_version", None)
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build_info["nccl_version"] = cuda.get("nccl_version", None)
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sys.argv = backup_argv
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contents = f"""
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# 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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\"\"\"Auto-generated module providing information about the build.\"\"\""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from collections import namedtuple
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build_info = {build_info}
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"""
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open(filename, "w").write(contents)
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parser = argparse.ArgumentParser(
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description="""Build info injection into the PIP package.""")
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parser.add_argument("--raw_generate", type=str, help="Generate build_info.py")
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parser.add_argument(
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"--key_value", type=str, nargs="*", help="List of key=value pairs.")
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args = parser.parse_args()
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if args.raw_generate:
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print(args.key_value)
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write_build_info(args.raw_generate, args.key_value)
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else:
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raise RuntimeError(
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"--raw_generate must be used.")
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