/**
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* @license
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* Copyright 2018 Google LLC. All Rights Reserved.
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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* =============================================================================
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*/
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#ifndef TF_NODEJS_TFJS_BACKEND_H_
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#define TF_NODEJS_TFJS_BACKEND_H_
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#include <node_api.h>
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#include <memory>
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#include <string>
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#include <unordered_map>
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#include "tensorflow/c/c_api.h"
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#include "tensorflow/c/eager/c_api.h"
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namespace tfnodejs {
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class TFJSBackend {
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public:
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~TFJSBackend();
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// Creates, initializes, and returns a TFJSBackend instance. If initialization
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// fails, a nullptr is returned.
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static TFJSBackend *Create(napi_env env);
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// Creates a new Tensor with given shape and data and returns an ID that
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// refernces the new Tensor.
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// - shape_value (number[])
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// - dtype_value (number)
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// - array_value (TypedArray|Array)
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napi_value CreateTensor(napi_env env, napi_value shape_value,
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napi_value dtype_value, napi_value array_value);
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// Deletes a created Tensor.
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// - tensor_id_value (number)
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void DeleteTensor(napi_env env, napi_value tensor_id_value);
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// Returns a typed-array as a `napi_value` with the data associated with the
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// TF/TFE pointers.
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// - tensor_id_value (number)
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napi_value GetTensorData(napi_env env, napi_value tensor_id_value);
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// Executes a TFE Op and returns an array of objects containing tensor
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// attributes (id, dtype, shape).
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// - op_name_value (string)
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// - op_attr_inputs (array of TFE Op attributes)
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// - input_tensor_ids (array of input tensor IDs)
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// - num_output_values (number)
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napi_value ExecuteOp(napi_env env, napi_value op_name_value,
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napi_value op_attr_inputs, napi_value input_tensor_ids,
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napi_value num_output_values);
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// Load a SavedModel from a path:
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// - export_dir (string)
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// - tags_value (string)
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napi_value LoadSavedModel(napi_env env, napi_value export_dir,
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napi_value tags_value);
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// Delete the SavedModel corresponding TF_Session and TF_Graph
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// - saved_model_id (number)
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void DeleteSavedModel(napi_env env, napi_value saved_model_id);
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// Execute a session from SavedModel with the provided inputs:
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// - saved_model_id (number)
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// - input_tensor_ids (array of input tensor IDs)
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// - input_op_names (array of input op names)
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// - output_op_names (array of output op names)
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napi_value RunSavedModel(napi_env env, napi_value saved_model_id,
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napi_value input_tensor_ids,
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napi_value input_op_names,
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napi_value output_op_names);
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// Get number of loaded SavedModel in the backend:
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napi_value GetNumOfSavedModels(napi_env env);
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// Get number of tensor handles in the backend:
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napi_value GetNumOfTensors(napi_env env);
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private:
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TFJSBackend(napi_env env);
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int32_t InsertHandle(TFE_TensorHandle *tfe_handle);
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int32_t InsertSavedModel(TF_Session *tf_session, TF_Graph *tf_graph);
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napi_value GenerateOutputTensorInfo(napi_env env, TFE_TensorHandle *handle);
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TFE_Context *tfe_context_;
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std::unordered_map<int32_t, TFE_TensorHandle *> tfe_handle_map_;
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std::unordered_map<int32_t, std::pair<TF_Session *, TF_Graph *>>
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tf_savedmodel_map_;
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int32_t next_tensor_id_;
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int32_t next_savedmodel_id_;
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std::string device_name;
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public:
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bool is_gpu_device;
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};
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} // namespace tfnodejs
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#endif // TF_NODEJS_TFJS_BACKEND_H_
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