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tensorflow/c/eager/tfe_executor_internal.h
#include "tensorflow/core/common_runtime/eager/eager_executor.h" struct TFE_Executor { explicit TFE_Executor(bool async, bool enable_streaming_enqueue, int in_flight_nodes_limit) : owned_executor(new tensorflow::EagerExecutor( async, enable_streaming_enqueue, in_flight_nodes_limit)) {} explicit TFE_Executor(tensorflow::EagerExecutor* executor) : owned_executor(nullptr), unowned_executor(executor) {}
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CODE_OF_CONDUCT.md
## Conflict Resolution Conflicts in an open source project can take many forms, from someone having a bad day and using harsh and hurtful language in the issue queue, to more serious instances such as sexist/racist statements or threats of violence, and everything in between. If the behavior is threatening or harassing, or for other reasons requires immediate escalation, please see below.
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tensorflow/c/eager/c_api_remote_test_util.cc
std::vector<TFE_TensorHandle*> handles_task0; if (heavy_load_on_streaming_rpc) { // Send 50 tensor copy requests to simulate that there have been some RPC // requests been enqueued. for (int i = 0; i < 50; ++i) { handles_task0.push_back(TestMatrixTensorHandle(ctx)); } } const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";
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