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tensorflow/c/c_api.cc
"Creating while loops is not supported on mobile. File a bug at " "https://github.com/tensorflow/tensorflow/issues if this feature is " "important to you"); #else // If it appears the caller created or modified `params`, don't free resources if (!ValidateConstWhileParams(*params, status)) return; TF_FinishWhileHelper(params, status, outputs); FreeWhileResources(params);
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CONTRIBUTING.md
`tensorflow/python/saved_model/load_test.py`: (Requires `python>=3.7`) ```bash bazel test ${flags} //tensorflow/python/saved_model:load_test --test_filter=*LoadTest.test_capture_variables* ``` **Note:** You can add `--test_sharding_strategy=disabled` to the `flags` to disable the sharding so that all the test outputs are in one file. However,
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tensorflow/BUILD
"//tensorflow:windows": """ $(location @local_config_def_file_filter//:def_file_filter) \\ --input $(location :tensorflow_def_file) \\ --output $@ """, "//conditions:default": "touch $@", # Just a placeholder for Unix platforms }), tools = ["@local_config_def_file_filter//:def_file_filter"], visibility = ["//visibility:public"], )
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RELEASE.md
* Added a new field, `filter_parallelization`, to `tf.data.experimental.OptimizationOptions`. If it is set to `True`, tf.data will run `Filter` transformation with multiple threads. Its default value is `False` if not specified. * `tf.keras`:
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tensorflow/c/eager/tape.h
const std::vector<int64_t>& unneeded_gradients, gtl::ArraySlice<Gradient*> output_gradients, absl::Span<Gradient*> result) const = 0; // Builds a tensor filled with ones with the same shape and dtype as `t`. virtual Status BuildOnesLike(const TapeTensor& t, Gradient** result) const = 0; // Looks up the ID of a Gradient.
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tensorflow/c/c_api_experimental.cc
// scheduled on that same threadpool, causing a deadlock in cases where the // caller of event_mgr->ThenExecute() blocks on the completion of the callback // (as in the case of ConstOp kernel creation on GPU, which involves copying a // CPU tensor to GPU). // Setting a larger thread pool does not help with the Swift caller, as we use // a different TFE context for each thread of execution (for running graph
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.bazelrc
# https://github.com/bazelbuild/bazel/issues/3360 build:linux --experimental_guard_against_concurrent_changes # Configure short or long logs build:short_logs --output_filter=DONT_MATCH_ANYTHING build:verbose_logs --output_filter= # Instruction set optimizations # TODO(gunan): Create a feature in toolchains for avx/avx2 to # avoid having to define linux/win separately. build:avx_linux --copt=-mavx
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