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tensorflow/BUILD
) config_setting( name = "using_rocm_hipcc", define_values = {"using_rocm_hipcc": "true"}, ) config_setting( name = "override_eigen_strong_inline", define_values = {"override_eigen_strong_inline": "true"}, visibility = ["//visibility:public"], ) # This flag specifies whether TensorFlow 2.0 API should be built instead
Plain Text - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Apr 09 18:15:11 GMT 2024 - 53.4K bytes - Viewed (8) -
RELEASE.md
* This does not change the minimum required version for building TensorFlow from source on Windows, but builds enabling `EIGEN_STRONG_INLINE` can take over 48 hours to compile without this flag. Refer to `configure.py` for more information about `EIGEN_STRONG_INLINE` and `/d2ReducedOptimizeHugeFunctions`. * If either of the required DLLs, `msvcp140.dll` (old) or `msvcp140_1.dll`
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configure.py
) if get_var( environ_cp, 'TF_OVERRIDE_EIGEN_STRONG_INLINE', 'Eigen strong inline', True, ('Would you like to override eigen strong inline for some C++ ' 'compilation to reduce the compilation time?'), 'Eigen strong inline overridden.', 'Not overriding eigen strong inline, ' 'some compilations could take more than 20 mins.'):
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Mon Apr 15 18:25:36 GMT 2024 - 53.8K bytes - Viewed (1) -
ci/official/utilities/code_check_full.bats
} # This test ensures that all the targets built into the Python package include # their dependencies. It's a rewritten version of the "smoke test", an older # Python script that was very difficult to understand. See # https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/pip_package/pip_smoke_test.py @test "Pip package includes all required //tensorflow dependencies" { # grep patterns for packages whose dependencies can be ignored
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.bazelrc
# Don't build the python zip archive in the RBE build. build:rbe_win_base --remote_download_minimal build:rbe_win_base --enable_runfiles build:rbe_win_base --nobuild_python_zip build:rbe_win_base --define=override_eigen_strong_inline=true build:rbe_win_clang --config=rbe_win_base build:rbe_win_clang --crosstool_top="//tensorflow/tools/toolchains/win/20240424:toolchain"
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ci/official/utilities/extract_resultstore_links.py
log_lines = f.read().splitlines() result_store_links: ResultDictType = {} current_url = None for i in range(len(log_lines)): line = log_lines[i] result_store_line_match = re.search(RESULT_STORE_LINK_RE, line) if not result_store_line_match: continue url = result_store_line_match.group(1) url_lines = result_store_links.setdefault(url, {})
Python - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Nov 08 17:50:27 GMT 2023 - 10.9K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.cc
TF_TensorByteSize(theta_tensor)); // Initialize space for the numerical gradient. vector<float> dtheta_approx(num_elems); // Get theta shape and store in theta_dims. int num_dims = TF_NumDims(theta_tensor); vector<int64_t> theta_dims(num_dims); GetDims(theta_tensor, theta_dims.data()); // Initialize auxilary data structures.
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7.3K bytes - Viewed (0) -
tensorflow/c/c_api.h
// // Questions left to address: // * Might at some point need a way for callers to provide their own Env. // * Maybe add TF_TensorShape that encapsulates dimension info. // // Design decisions made: // * Backing store for tensor memory has an associated deallocation // function. This deallocation function will point to client code // for tensors populated by the client. So the client can do things // like shadowing a numpy array.
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