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CONTRIBUTING.md
![image](https://github.com/tensorflow/tensorflow/assets/52792999/3eea4ca5-daa0-4570-b0b5-2a2b03a724a3) ### Contributor License Agreements We'd love to accept your patches! Before we can take them, we have to jump a couple of legal hurdles. Please fill out either the individual or corporate Contributor License Agreement (CLA).
Plain Text - Registered: Tue Apr 23 12:39:09 GMT 2024 - Last Modified: Thu Mar 21 11:45:51 GMT 2024 - 15.6K bytes - Viewed (0) -
tensorflow/c/eager/immediate_execution_context.h
// List attributes of available devices virtual void ListDevices(std::vector<DeviceAttributes>* devices) = 0; // Add `devices` into context's device manager. Context's device manager // will take ownership and maintain devices' lifetime. virtual Status AddDevices(std::vector<std::unique_ptr<Device>> devices) = 0; // Block until all pending nodes are finished. virtual Status AsyncWait() = 0;
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tensorflow/c/eager/parallel_device/parallel_device_lib_test.cc
ParallelTensor::FromTensorHandles(parallel_device, std::move(mixed_handles), status.get()); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK); // Can't take the shape of a parallel tensor with varying numbers of axes, but // running operations on them is OK. TF_ASSERT_OK(unknown_length_vector->Shape(&shape)); EXPECT_THAT(*shape, ElementsAre(-1));
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tensorflow/c/c_api_experimental.cc
std::vector<Tensor> all_input_tensors; // Update the vector with information from `input_tensors` if provided. if (input_tensors != nullptr) { // Note that we take the address of the elements in `all_input_tensors` // below. Allocate enough space so that no reallocation happens, which will // make the pointers invalid. all_input_tensors.reserve(num_inputs);
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tensorflow/c/eager/tape.h
// Tensor passed to Accumulate goes out of scope. // // Not thread-safe. template <typename Gradient, typename BackwardFunction, typename TapeTensor> class ForwardAccumulator { public: // Does not take ownership of `vspace`, which must outlive the // ForwardAccumulator. explicit ForwardAccumulator( const VSpace<Gradient, BackwardFunction, TapeTensor>& vspace, bool use_batch)
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