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SECURITY.md
programs that TensorFlow executes. TensorFlow programs are encoded as computation [**graphs**](https://developers.google.com/machine-learning/glossary/#graph). Since models are practically programs that TensorFlow executes, using untrusted models or graphs is equivalent to running untrusted code. If you need to run untrusted models, execute them inside a
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ci/official/README.md
2. Running the CI scripts locally, as explained below 3. **Google employees only**: Google employees can use an internal-only tool called "MLCI" that makes testing more convenient: it can execute any full CI job against a pending change. Search for "MLCI" internally to find it. You may invoke a CI script of your choice by following these instructions: ```bash cd tensorflow-git-dir
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CONTRIBUTING.md
disable the sharding so that all the test outputs are in one file. However, it may slow down the tests for not running in parallel and may cause the test to timeout but it could be useful when you need to execute a single test or more in general your filtered/selected tests have a very low execution time and the sharding
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tensorflow/c/eager/BUILD
"//tensorflow/c:conversion_macros", "//tensorflow/core:framework", ], ) cc_library( name = "tfe_executor_internal", hdrs = ["tfe_executor_internal.h"], visibility = ["//visibility:private"], deps = [ "//tensorflow/core/common_runtime/eager:eager_executor", ], ) cc_library( name = "tfe_monitoring_internal", hdrs = ["tfe_monitoring_internal.h"],
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tensorflow/c/BUILD
"//tensorflow:android": [ "//tensorflow/c/experimental/stream_executor:stream_executor_hdrs", "//tensorflow/core:portable_tensorflow_lib_lite", ], "//conditions:default": [ ":tf_tensor", "//tensorflow/c/experimental/stream_executor", "//tensorflow/c/experimental/stream_executor:stream_executor_internal", "//tensorflow/core:framework",
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RELEASE.md
* Add an option `disable_eager_executer_streaming_enqueue` to `tensorflow.ConfigProto.Experimental` to control the eager runtime's behavior around parallel remote function invocations; when set to `True`, the eager runtime will be allowed to execute multiple function invocations in parallel. * `tf.constant_initializer`
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.bazelrc
# to make sure all Genrule targets are excuted locally. build:rbe_cross_compile_base_xla --config=rbe_cross_compile_base build:rbe_cross_compile_base_xla --strategy=Genrule=standalone # Due to the above strategy, all Genrule commands are executed locally, but the # following actions invoke tools (E.g `flatc`, `llvm-tblgen`, etc.) that are # only executabe on the RBE (x86) machine, so the strategy_regexp options are
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tensorflow/BUILD
otherwise = [ "@local_xla//xla/stream_executor/cuda:all_runtime", "@local_xla//xla/stream_executor/cuda:cuda_driver", "@local_xla//xla/stream_executor/cuda:cuda_platform", "@local_xla//xla/stream_executor/cuda:cudnn_plugin", "@local_xla//xla/stream_executor/cuda:cufft_plugin", "@local_xla//xla/stream_executor:cuda_platform", ], ),
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LICENSE
this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor,
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