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128 lines
4.1 KiB
128 lines
4.1 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#ifndef __PADDLE_CAPI_GRADIENT_MACHINE_H__
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#define __PADDLE_CAPI_GRADIENT_MACHINE_H__
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#include "arguments.h"
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#include "config.h"
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#include "error.h"
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#ifdef __cplusplus
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extern "C" {
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#endif
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/**
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* @brief GradientMachine means a neural network.
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*/
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typedef void* paddle_gradient_machine;
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/**
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* @brief Create a gradient machine used for model inference.
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* @param [out] machine that used for model inference.
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* @param [in] modelConfigProtobuf
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* @param [in] size
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* @return paddle_error
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*/
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PD_API paddle_error paddle_gradient_machine_create_for_inference(
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paddle_gradient_machine* machine, void* modelConfigProtobuf, int size);
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/**
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* @brief Create a gradient machine used for model inference, using config with
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* parameters which is generated by `paddle merge_model`.
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* Example:
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* paddle merge_model \
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* --model_dir="pass-00000" \
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* --model_file="merged_model.paddle"
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* @param [out] machine that used for model inference
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* @param [in] mergedModel
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* @param [in] size
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_create_for_inference_with_parameters(
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paddle_gradient_machine* machine, void* mergedModel, uint64_t size);
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/**
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* @brief Load parameter from disk.
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* @param machine Gradient Machine.
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* @param path local directory path.
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* @return paddle_error
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*/
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PD_API paddle_error paddle_gradient_machine_load_parameter_from_disk(
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paddle_gradient_machine machine, const char* path);
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/**
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* @brief Forward a gradient machine
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* @param machine Gradient machine
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* @param inArgs input arguments
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* @param outArgs output arguments
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* @param isTrain is train or not
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_forward(paddle_gradient_machine machine,
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paddle_arguments inArgs,
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paddle_arguments outArgs,
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bool isTrain);
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/**
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* @brief Create a gradient machine, which parameters are shared from another
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* gradient machine.
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* @param [in] origin gradient machine
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* @param [in] modelConfigProtobuf model config protobuf
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* @param [in] size of model config buffer.
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* @param [out] slave gradient machine, the output value.
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_create_shared_param(paddle_gradient_machine origin,
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void* modelConfigProtobuf,
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int size,
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paddle_gradient_machine* slave);
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PD_API paddle_error
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paddle_gradient_machine_randomize_param(paddle_gradient_machine machine);
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/**
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* @brief Destroy a gradient machine
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* @param machine that need to destroy
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_destroy(paddle_gradient_machine machine);
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/**
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* @brief Get the output of the layer named `layerName`.
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* @param [in] gradient machine that have run a inference
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* @param [in] layerName name of specified layer
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* @param [out] args output of the specified layer
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_get_layer_output(paddle_gradient_machine machine,
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const char* layerName,
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paddle_arguments args);
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/**
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* @brief Release the middle layer's output memory of the gradient machine.
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* @param [in] gradient machine that have run a inference
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* @return paddle_error
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*/
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PD_API paddle_error
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paddle_gradient_machine_release_layer_output(paddle_gradient_machine machine);
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#ifdef __cplusplus
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}
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#endif
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#endif
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