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tensorflow/c/eager/c_api.h
// ops. TF_CAPI_EXPORT extern void TFE_ContextClearCaches(TFE_Context* ctx); // Sets a thread-local device placement policy. After this call, other calls to // TFE_Execute in the same thread will use the device policy specified here // instead of the device policy used to construct the context. This has no // effect on the device policy used by other program threads. TF_CAPI_EXPORT extern void TFE_ContextSetThreadLocalDevicePlacementPolicy(
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ci/official/containers/linux_arm64/devel.usertools/setup_venv_test.sh
set -euxo pipefail # Run this from inside the tensorflow github directory. # Usage: setup_venv_test.sh venv_and_symlink_name "glob pattern for one wheel file" # Example: setup_venv_test.sh bazel_pip "/tf/pkg/*.whl" # # This will create a venv with that wheel file installed in it, and a symlink # in ./venv_and_symlink_name/tensorflow to ./tensorflow. We use this for the # "pip" tests. python -m venv /$1
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tensorflow/c/c_test.c
#include "tensorflow/c/kernels.h" // A create function. This will never actually get called in this test, it's // just nice to know that it compiles. void* create(TF_OpKernelConstruction* ctx) { TF_DataType type; TF_Status* s = TF_NewStatus(); TF_OpKernelConstruction_GetAttrType(ctx, "foobar", &type, s); TF_DeleteStatus(s); return NULL; } // A compute function. This will never actually get called in this test, it's
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tensorflow/api_template.__init__.py
# ============================================================================== """ Top-level module of TensorFlow. By convention, we refer to this module as `tf` instead of `tensorflow`, following the common practice of importing TensorFlow via the command `import tensorflow as tf`. The primary function of this module is to import all of the public TensorFlow interfaces into a single place. The interfaces themselves are located in
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tensorflow/c/eager/immediate_execution_distributed_manager.h
// for remote workers. Currently this only works for resetting context. // TODO(b/289445025): Consider removing this when we find a proper fix. virtual Status InitializeLocalOnlyContext(const ServerDef& server_def, int keep_alive_secs) = 0; // Set up a multi-client distributed execution environment. Must be called // on all tasks in the cluster. This call internally coordinates with other
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tensorflow/c/eager/abstract_operation.h
// // WARNING: The destructor of this class is marked as protected to disallow // clients from directly destroying this object since it may manage it's own // lifetime through ref counting. Thus this must be allocated on the heap and // clients MUST call Release() in order to destroy an instance of this class. virtual void Release() = 0;
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CODE_OF_CONDUCT.md
## Scope
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ci/official/debug_tfci.sh
#!/bin/bash # Copyright 2023 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,
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ci/official/requirements_updater/updater.sh
#!/usr/bin/env bash # Copyright 2023 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,
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# bazel tests with a special flag "--define=no_tensorflow_py_deps=true", which # drops all the bazel dependencies for each py_test; this makes all the tests # use the wheel's TensorFlow installation instead of the one made available # through bazel. This must be done in a different root directory, //bazel_pip/..., # because "import tensorflow" run from the root directory would instead import
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