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tensorflow/c/eager/parallel_device/parallel_device_lib.h
// A sequence of thread wrappers, one per device, for executing operations in // parallel. // // Conceptually this is a thread pool with one thread per device. It requires // less synchronization than a thread pool would for this task, since Execute // acquires each thread in order (and so only one Execute will schedule // blocking collective operations at a time), and avoids some dynamic
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tensorflow/c/eager/c_api.h
// tensors in `retvals`. // // 'retvals' must point to a pre-allocated array of TFE_TensorHandle* and // '*num_retvals' should be set to the size of this array. It is an error if // the size of 'retvals' is less than the number of outputs. This call sets // *num_retvals to the number of outputs. // // If async execution is enabled, the call may simply enqueue the execution
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tensorflow/c/c_api_experimental.h
// Platform-specific implementation to return an unused port. (This should used // in tests only.) TF_CAPI_EXPORT int TF_PickUnusedPortOrDie(void); // Fast path method that makes constructing a single scalar tensor require less // overhead and copies. TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromScalar( TF_DataType data_type, void* data, size_t len, TF_Status* status); // Specify the server_def that enables collective ops.
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tensorflow/c/eager/tape.h
// there isn't an intervening PushState. This is useful for ordering // ForwardAccumulators, where more deeply nested accumulators should not see // computations from less deeply nested accumulators. bool BusyAccumulating() const { return call_state_.top().accumulating; } // Fetches the current Jacobian-vector product associated with `tensor_id`, or // a nullptr if none is available.
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