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CONTRIBUTING.md
your response for more than 2 weeks. **4. Approved** - Once the PR is approved, it gets `kokoro:force-run` label applied and it initiates CI/CD tests. - We can't move forward if these tests fail. - In such situations, we may request you to make further changes to your PR for the tests to pass. - Once the tests pass, we now bring all the code into the internal code base,
Plain Text - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Thu Mar 21 11:45:51 GMT 2024 - 15.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api_distributed_test.cc
} private: bool first_call_ = true; }; // After the graph pass is registered, it takes effect globally and can affect // other test cases. Define a static variable to switch it on and off. bool GraphErrorInjectionPass::enabled_ = false; // Test to ensure that a registered graph optimization pass is only executed
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tensorflow/c/eager/tape.h
void DeleteTrace(int64_t tensor_id); // Consumes the internal state of the tape (so cannot be called more than // once) and produces the gradient of the target tensors with respect to the // source tensors. The output gradients are used if not empty and not // null. The result is populated with one tensor per target element. // When running backward functions, builds zeros-like tensors for
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tensorflow/c/c_api_function.cc
auto& indices = iter->second; if (std::find(indices.begin(), indices.end(), idx) != indices.end()) { return InvalidArgument("TF_Output ", node->name(), ":", idx, " appears more than once in the input list"); } indices.push_back(idx); } } return absl::OkStatus(); } // Converts `noutputs` and `outputs` into `outputs_tensors` and does various // checks while doing so.
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tensorflow/c/eager/c_api_experimental.h
TF_Status* status); // ----------------------------------------------------------------------------- // Eager Executor APIs. typedef struct TFE_Executor TFE_Executor; // Creates a new eager Executor. Nodes in one executor are guaranteed to be // executed in sequence. Assigning nodes to different executors allows executing // nodes in parallel. // in_flight_nodes_limit: when is_async is true, this value controls the
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tensorflow/c/eager/c_api_experimental.cc
tensorflow::ImmediateExecutionTensorHandle* unwrapped_handle = tensorflow::unwrap(handles[i]); if (tensorflow::CustomDeviceTensorHandle::classof(unwrapped_handle)) { // One of the inputs we're trying to pack is on a custom device. We'll let // the first custom device we see handle all of the packing. auto* custom_device_handle =
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ci/official/utilities/code_check_full.bats
# Find all one-step dependencies of those tests which are from //tensorflow # (since external deps will come from Python-level pip dependencies), # excluding dependencies and files that are known to be unneccessary.
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tensorflow/c/eager/parallel_device/parallel_device_lib.cc
// Outputs: std::vector<TensorHandlePtr> op_outputs_ TF_GUARDED_BY(execution_mutex_); // TF_Status is an incomplete type and so can't be stack allocated. To avoid // unnecessary allocations each Execute call, we keep one heap-allocated // version for the thread. StatusPtr status_ TF_GUARDED_BY(execution_mutex_); const std::string device_; ExecutorPtr executor_ TF_GUARDED_BY(execution_mutex_);
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