/* Copyright 2020 The TensorFlow Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_ #define TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_ #include "tensorflow/c/eager/abstract_context.h" #include "tensorflow/c/eager/abstract_tensor_handle.h" #include "tensorflow/c/eager/c_api_test_util.h" #include "tensorflow/c/eager/c_api_unified_experimental.h" #include "tensorflow/c/eager/c_api_unified_experimental_internal.h" #include "tensorflow/c/tf_status_helper.h" #include "tensorflow/c/tf_tensor.h" #include "tensorflow/core/platform/status.h" namespace tensorflow { // Builds and returns a `TracingContext` using the default tracing impl. AbstractContext* BuildFunction(const char* fn_name); // Creates parameters (placeholders) in the tracing `ctx` using the shape and // dtype of `inputs`. absl::Status CreateParamsForInputs( AbstractContext* ctx, absl::Span inputs, std::vector* params); // A callable that takes tensor inputs and returns zero or more tensor outputs. using Model = std::function, absl::Span)>; // Runs `model` maybe wrapped in a function call op. This can be thought as // being equivalent to the following python code. // // if use_function: // outputs = tf.function(model)(inputs) // else: // outputs = model(inputs) absl::Status RunModel(Model model, AbstractContext* ctx, absl::Span inputs, absl::Span outputs, bool use_function); absl::Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx); // Return a tensor handle with given type, values and dimensions. template absl::Status TestTensorHandleWithDims(AbstractContext* ctx, const T* data, const int64_t* dims, int num_dims, AbstractTensorHandle** tensor) { std::unique_ptr status( TF_NewStatus(), TF_DeleteStatus); TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(wrap(ctx), status.get()); TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get())); TFE_TensorHandle* input_eager = TestTensorHandleWithDims(eager_ctx, data, dims, num_dims); *tensor = unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get())); return absl::OkStatus(); } // Return a scalar tensor handle with given value. template absl::Status TestScalarTensorHandle(AbstractContext* ctx, const T value, AbstractTensorHandle** tensor) { std::unique_ptr status( TF_NewStatus(), TF_DeleteStatus); TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(wrap(ctx), status.get()); TF_RETURN_IF_ERROR(StatusFromTF_Status(status.get())); TFE_TensorHandle* input_eager = TestScalarTensorHandle(eager_ctx, value); *tensor = unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get())); return absl::OkStatus(); } // Places data from `t` into *result_tensor. absl::Status GetValue(AbstractTensorHandle* t, TF_Tensor** result_tensor); } // namespace tensorflow #endif // TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_