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ISSUES.md
If you open a GitHub Issue, here is our policy: 1. It must be a bug/performance issue or a feature request or a build issue or a documentation issue (for small doc fixes please send a PR instead). 1. Make sure the Issue Template is filled out. 1. The issue should be related to the repo it is created in. **Here's why we have this policy:** We want to focus on the work that benefits the whole community, e.g., fixing bugs and adding features. Individual support
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tensorflow/c/eager/c_api_remote_test_util.h
#ifndef TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_ #define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_ // Run a function containing a MatMul op and check its output. // If heavy_load_on_streaming_rpc is true, send some rpc requests before the one // which creates a remote input, to simulate a scenario that the remote input // is not ready when we start running an op or a function.
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ci/official/utilities/setup_macos.sh
# inside the TensorFlow root directory. We then define them as a filegroup # target inside "tensorflow/tools/toolchains/cross_compile/cc" so that Bazel # can register it as an input to compile/link actions and send it to the remote # VMs when needed. # TODO(b/316932689): Avoid copying and replace with a local repository rule. if [[ "$TFCI_MACOS_CROSS_COMPILE_ENABLE" == 1 ]]; then mkdir -p "${TFCI_MACOS_CROSS_COMPILE_SDK_DEST}/usr"
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tensorflow/c/eager/c_api_remote_test_util.cc
TFE_TensorHandle* h0_task0 = TestMatrixTensorHandle(ctx); TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx); 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)); } }
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tensorflow/c/eager/c_api_test_util.h
// Return a SendOp op `op_name` with send input tensor `in` and attributes // `send_device`, `recv_device`, and `send_device_incarnation` set. TFE_Op* SendOp(TFE_Context* ctx, TFE_TensorHandle* in, const std::string& op_name, const std::string& send_device, const std::string& recv_device, tensorflow::uint64 send_device_incarnation);
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