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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. 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.
*/
#include "wrapper/nnfw_api.hpp"
/*
* Create a new session instance
*
* @param session the session to be created
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_create_session(nnfw_session **session)
{
*session = new nnfw_session();
return NNFW_STATUS_NO_ERROR;
}
/*
* Close a session instance
*
* @param session the session to be closed
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_close_session(nnfw_session *session)
{
delete session;
return NNFW_STATUS_NO_ERROR;
}
#define NNFW_RETURN_ERROR_IF_NULL(p) \
do \
{ \
if ((p) == NULL) \
return NNFW_STATUS_ERROR; \
} while (0)
/*
* Load model from nnpackage file or directory
*
* @param session nnfw_session loading the given nnpackage file/dir
* @param package_file_path path to the nnpackage file or unzipped directory to be loaded
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_load_model_from_file(nnfw_session *session, const char *pacakge_file_path)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->load_model_from_file(pacakge_file_path);
}
/*
* Prepare session to be ready for inference
* This phase may finalize model compilation, scheduling, and additional settings.
*
* @param session the session to be prepared
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_prepare(nnfw_session *session)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->prepare();
}
/*
* Run inference
*
* @param session the session to run inference
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_run(nnfw_session *session)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->run();
}
/*
* Set input
*
* @param session session to the input is to be set
* @param index index of input to be set (0-indexed)
* @param type type of the input
* @param buffer raw buffer for input
* @param length size of bytes of output
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_set_input(nnfw_session *session, uint32_t index, NNFW_TYPE type,
const void *buffer, size_t length)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->set_input(index, type, buffer, length);
}
/*
* Set output
*
* @param session session from inference output is to be extracted
* @param index index of output to be set (0-indexed)
* @param type type of the output
* @param buffer raw buffer for output
* @param length size of bytes of output
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_set_output(nnfw_session *session, uint32_t index, NNFW_TYPE type, void *buffer,
size_t length)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->set_output(index, type, buffer, length);
}
/*
* Get the number of inputs
*
* @param[in] session session from input information is to be extracted
* @param[out] number variable which the number of inputs is put into
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_input_size(nnfw_session *session, uint32_t *number)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->input_size(number);
}
/*
* Get the number of outputs
*
* @param[in] session session from output information is to be extracted
* @param[out] number variable which the number of outputs is put into
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_output_size(nnfw_session *session, uint32_t *number)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->output_size(number);
}
/*
* Get i-th input tensor info
*
* @param[in] session session from input information is to be extracted
* @param[in] index index of input
* @param[out] tensor_info nnfw_tensor_info
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_input_tensorinfo(nnfw_session *session, uint32_t index,
nnfw_tensorinfo *tensor_info)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->input_tensorinfo(index, tensor_info);
}
/*
* Get i-th output tensor info
*
* @param[in] session session from output information is to be extracted
* @param[in] index index of output
* @param[out] tensor_info nnfw_tensor_info
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_output_tensorinfo(nnfw_session *session, uint32_t index,
nnfw_tensorinfo *tensor_info)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->output_tensorinfo(index, tensor_info);
}
/*
* Register custom operation
* @param session session to register this operation
* @param id operation id
* @param info registration info ( eval function, etc. )
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_register_custom_op_info(nnfw_session *session, const char *id,
custom_kernel_registration_info *info)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->register_custom_operation(id, info->eval_function);
}
/*
* Set default backend
*
* @param[in] session session to which a default backend is set
* @param[in] backend default backend
*/
NNFW_STATUS nnfw_set_default_backend(nnfw_session *session, const char *backend)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->set_default_backend(backend);
}
/*
* Set the operation's backend
*
* @param[in] session session to be modified
* @param[in] op operation to be set
* @param[in] backend bakcend on which operation run
*
* @return NNFW_STATUS_NO_ERROR if successful
*/
NNFW_STATUS nnfw_set_op_backend(nnfw_session *session, const char *op, const char *backend)
{
NNFW_RETURN_ERROR_IF_NULL(session);
return session->set_op_backend(op, backend);
}
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