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* cmake versions > 3.6 will quote -D__VERSION__=\"MSVC\" as -D"__VERSION__=\"MSVC\"" which nvcc stubles over. Since this is only used by version.cc we apply this only core/framework so nvcc will never see it. * - support for tf.load_library() on windows - support for linking against tensorflow.dll to access c/c++ api - switched contrib/rnn to use .so's - added add tests in contrib/rnn * Address review feedback. Changes: - Some style changes - TF_COMPILE_LIBRARY define controls exports from the tensorflow.dll. If TF_COMPILE_LIBRARY is defined we compile tensorflow, if undefined we compile a user op. - On windows user ops have now a .dll extension. The resource loader will take care of finding it. - pywrap_tensorflow_internal.lib that is needed to build a user op on windows comes with the wheel * fix linux build * fix linux build * keep //tensorflow/tools/test:check_futures_test happy * add copyright
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
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| # Copyright 2017 The TensorFlow Authors. All Rights Reserved. | ||
| # | ||
| # 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 | ||
| # | ||
| # http://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. | ||
| # ============================================================================== | ||
|
|
||
| """ | ||
| create_def_file.py - tool to create a windows def file to export | ||
| symbols from tensorflow.dll to enable tf.load_library(). | ||
| Because the linker allows only 64K symbols to be exported per dll | ||
| we filter the symbols down to the essentials. The regular expressions | ||
| we use for this are specific to tensorflow. | ||
| TODO: this works fine but there is an issue with exporting | ||
| 'const char * const' and importing it from a user_ops. The problem is | ||
| on the importing end and using __declspec(dllimport) works around it. | ||
| """ | ||
| from __future__ import absolute_import | ||
| from __future__ import division | ||
| from __future__ import print_function | ||
|
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||
| import argparse | ||
| import io | ||
| import os | ||
| import re | ||
| import sys | ||
| import tempfile | ||
| from subprocess import Popen, PIPE | ||
|
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||
| # External tools we use that come with visual studio sdk and | ||
| # we assume that the caller has the correct PATH to the sdk | ||
| UNDNAME = "undname.exe" | ||
| DUMPBIN = "dumpbin.exe" | ||
|
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| # Exclude if matched | ||
| EXCLUDE_RE = re.compile(r"deleting destructor|::internal::") | ||
|
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| # Include if matched before exclude | ||
| INCLUDEPRE_RE = re.compile(r"tensorflow::internal::LogMessage|" + | ||
| r"tensorflow::internal::CheckOpMessageBuilder") | ||
|
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| # Include if matched after exclude | ||
| INCLUDE_RE = re.compile(r"^(TF_\w*)$|" + | ||
| r"tensorflow::|" + | ||
| r"functor::|" + | ||
| r"perftools::gputools") | ||
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|
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| def get_args(): | ||
| """Parse command line.""" | ||
| parser = argparse.ArgumentParser() | ||
| parser.add_argument("--input", help="input library", required=True) | ||
| parser.add_argument("--output", help="output deffile", required=True) | ||
| args = parser.parse_args() | ||
| return args | ||
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| def main(): | ||
| """main.""" | ||
| args = get_args() | ||
|
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| # Pipe dumpbin to extract all linkable symbols from a lib. | ||
| # Good symbols are collected in candidates and also written to | ||
| # a temp file. | ||
| candidates = [] | ||
| tmpfile = tempfile.NamedTemporaryFile(mode="w", delete=False) | ||
| proc = Popen([DUMPBIN, "/nologo", "/linkermember:1", args.input], stdout=PIPE) | ||
| for line in io.TextIOWrapper(proc.stdout, encoding="utf-8"): | ||
| cols = line.split() | ||
| if len(cols) < 2: | ||
| continue | ||
| sym = cols[1] | ||
| tmpfile.file.write(sym + "\n") | ||
| candidates.append(sym) | ||
| tmpfile.file.close() | ||
| exit_code = proc.wait() | ||
| if exit_code != 0: | ||
| print("{} failed, exit={}".format(DUMPBIN, exit_code)) | ||
| return exit_code | ||
|
|
||
| # Run the symbols through undname to get their undecorated name | ||
| # so we can filter on something readable. | ||
| with open(args.output, "w") as def_fp: | ||
| # track dupes | ||
| taken = set() | ||
|
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| # Header for the def file. Since the tensorflow.dll is actually called | ||
| # _pywrap_tensorflow.pyd in the python wheel, hint that in the def file. | ||
| def_fp.write("LIBRARY _pywrap_tensorflow_internal.pyd\n") | ||
| def_fp.write("EXPORTS\n") | ||
| def_fp.write("\t ??1OpDef@tensorflow@@UEAA@XZ\n") | ||
|
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| # Each symbols returned by undname matches the same position in candidates. | ||
| # We compare on undname but use the decorated name from candidates. | ||
| dupes = 0 | ||
| proc = Popen([UNDNAME, tmpfile.name], stdout=PIPE) | ||
| for idx, line in enumerate(io.TextIOWrapper(proc.stdout, encoding="utf-8")): | ||
| decorated = candidates[idx] | ||
| if decorated in taken: | ||
| # Symbol is already in output, done. | ||
| dupes += 1 | ||
| continue | ||
|
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| if not INCLUDEPRE_RE.search(line): | ||
| if EXCLUDE_RE.search(line): | ||
| continue | ||
| if not INCLUDE_RE.search(line): | ||
| continue | ||
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| def_fp.write("\t" + decorated + "\n") | ||
| taken.add(decorated) | ||
| exit_code = proc.wait() | ||
| if exit_code != 0: | ||
| print("{} failed, exit={}".format(UNDNAME, exit_code)) | ||
| return exit_code | ||
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| os.unlink(tmpfile.name) | ||
|
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| print("symbols={}, taken={}, dupes={}" | ||
| .format(len(candidates), len(taken), dupes)) | ||
| return 0 | ||
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| if __name__ == "__main__": | ||
| sys.exit(main()) |
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