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CONTRIBUTING.md
#### Running doctest for testable docstring There are two ways to test the code in the docstring locally: 1. If you are only changing the docstring of a class/function/method, then you can test it by passing that file's path to [tf_doctest.py](https://www.tensorflow.org/code/tensorflow/tools/docs/tf_doctest.py). For example: ```bash python tf_doctest.py --file=<file_path> ```
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tensorflow/c/BUILD
":tf_status_internal", ":tf_tensor_internal", "//tensorflow/core:protos_all_cc", "@com_google_absl//absl/status", ], ) filegroup( name = "pywrap_tf_session_hdrs", srcs = [ "python_api.h", ], visibility = [ "//tensorflow/core:__pkg__", "//tensorflow/python:__pkg__", ], ) cc_library(
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tensorflow/c/eager/c_api_test_util.cc
TFE_Context* CreateContext(const std::string& serialized_server_def, bool isolate_session_state, int64_t init_timeout_in_ms) { TF_Status* status = TF_NewStatus(); TFE_ContextOptions* opts = TFE_NewContextOptions(); opts->session_options.options.config.set_isolate_session_state( isolate_session_state); TFE_ContextOptionsSetAsync(opts, static_cast<unsigned char>(false));
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tensorflow/c/eager/c_api_experimental.h
TFE_Context* ctx, TF_Tensor* t, TF_Status* status); // Create a packed TensorHandle with the given list of TensorHandles. // If `handles` are on the same device, assign the same device to the packed // handle; if `handles` are on different deivces, assign a CompositeDevice to // it. TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_CreatePackedTensorHandle( TFE_Context* ctx, TFE_TensorHandle** handles, int* num_handles,
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tensorflow/c/eager/c_api.cc
void TFE_ContextOptionsSetConfig(TFE_ContextOptions* options, const void* proto, size_t proto_len, TF_Status* status) { TF_SetConfig(&options->session_options, proto, proto_len, status); } void TFE_ContextOptionsSetAsync(TFE_ContextOptions* options, unsigned char enable) { options->async = enable; }
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tensorflow/c/c_api_experimental.cc
} return ret; } TF_Tensor* TF_DequeueNamedTensor(TF_Session* session, int tensor_id, TF_Status* status) { assert(session); { tensorflow::mutex_lock c(session->graph->mu); VLOG(1) << "Dequeuing named tensor with id " << tensor_id << ", with input graph: " << session->graph->graph.ToGraphDefDebug().DebugString(); }
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