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README.md
learning and neural networks. However, the framework is versatile enough to be used in other areas as well. TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python) and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a non-guaranteed backward compatible API for [other languages](https://www.tensorflow.org/api_docs).
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ci/official/utilities/setup.sh
# Therefore, "tfrun" commands cannot include pipes -- which is # probably for the better. If a pipe is necessary for something, it is probably # complex. Write a well-documented script under utilities/ to encapsulate the # functionality instead. tfrun() { "$@"; } # Run all "tfrun" commands under Docker. See setup_docker.sh for details if [[ "$TFCI_DOCKER_ENABLE" == 1 ]]; then
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tensorflow/c/eager/parallel_device/parallel_device_testlib.cc
#include "tensorflow/core/platform/test.h" // NOTE(allenl): These tests currently go through TFE_Execute and so are // integration testing rather than purely testing the parallel device. They // correspond fairly well to the implementation, but testing the C++ directly is // another option. namespace tensorflow { namespace parallel_device { Variable* Variable::Create(TFE_Context* context, TF_DataType type,
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tensorflow/c/eager/parallel_device/parallel_device_test.cc
#include "tensorflow/core/platform/test.h" // NOTE(allenl): These tests currently go through TFE_Execute and so are // integration testing rather than purely testing the parallel device. They // correspond fairly well to the implementation, but testing the C++ directly is // another option. namespace tensorflow { namespace parallel_device { using ::testing::HasSubstr; TEST(PARALLEL_DEVICE, TestBasicCPU) {
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