2 * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
8 * http://www.apache.org/licenses/LICENSE-2.0
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
17 #include "nnfw_api_internal.h"
18 #include "nnfw_version.h"
20 // Double-check enum value changes
22 #define STATIC_ASSERT_ENUM_CHECK(ENUM, VAL) static_assert((ENUM) == (VAL), #ENUM " has changed")
24 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_FLOAT32, 0);
25 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_INT32, 1);
26 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_QUANT8_ASYMM, 2);
27 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_BOOL, 3);
28 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_UINT8, 4);
29 STATIC_ASSERT_ENUM_CHECK(NNFW_TYPE_TENSOR_INT64, 5);
31 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_NO_ERROR, 0);
32 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_ERROR, 1);
33 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_UNEXPECTED_NULL, 2);
34 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_INVALID_STATE, 3);
35 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_OUT_OF_MEMORY, 4);
36 STATIC_ASSERT_ENUM_CHECK(NNFW_STATUS_INSUFFICIENT_OUTPUT_SIZE, 5);
38 STATIC_ASSERT_ENUM_CHECK(NNFW_LAYOUT_NONE, 0);
39 STATIC_ASSERT_ENUM_CHECK(NNFW_LAYOUT_CHANNELS_LAST, 1);
40 STATIC_ASSERT_ENUM_CHECK(NNFW_LAYOUT_CHANNELS_FIRST, 2);
42 STATIC_ASSERT_ENUM_CHECK(NNFW_INFO_ID_VERSION, 0);
44 #undef STATIC_ASSERT_ENUM_CHECK
46 #define NNFW_RETURN_ERROR_IF_NULL(p) \
50 return NNFW_STATUS_UNEXPECTED_NULL; \
54 * Create a new session instance
56 * @param session the session to be created
57 * @return NNFW_STATUS_NO_ERROR if successful
59 NNFW_STATUS nnfw_create_session(nnfw_session **session)
61 NNFW_RETURN_ERROR_IF_NULL(session);
63 *session = new (std::nothrow) nnfw_session();
64 if (*session == nullptr)
65 return NNFW_STATUS_OUT_OF_MEMORY;
66 return NNFW_STATUS_NO_ERROR;
70 * Close a session instance
72 * @param session the session to be closed
73 * @return NNFW_STATUS_NO_ERROR if successful
75 NNFW_STATUS nnfw_close_session(nnfw_session *session)
78 return NNFW_STATUS_NO_ERROR;
82 * Load model from nnpackage file or directory
84 * @param session nnfw_session loading the given nnpackage file/dir
85 * @param package_file_path path to the nnpackage file or unzipped directory to be loaded
87 * @return NNFW_STATUS_NO_ERROR if successful
89 NNFW_STATUS nnfw_load_model_from_file(nnfw_session *session, const char *pacakge_file_path)
91 NNFW_RETURN_ERROR_IF_NULL(session);
92 return session->load_model_from_file(pacakge_file_path);
96 * Prepare session to be ready for inference
97 * This phase may finalize model compilation, scheduling, and additional settings.
99 * @param session the session to be prepared
100 * @return NNFW_STATUS_NO_ERROR if successful
102 NNFW_STATUS nnfw_prepare(nnfw_session *session)
104 NNFW_RETURN_ERROR_IF_NULL(session);
105 return session->prepare();
111 * @param session the session to run inference
112 * @return NNFW_STATUS_NO_ERROR if successful
114 NNFW_STATUS nnfw_run(nnfw_session *session)
116 NNFW_RETURN_ERROR_IF_NULL(session);
117 return session->run();
120 NNFW_STATUS nnfw_run_async(nnfw_session *session)
122 NNFW_RETURN_ERROR_IF_NULL(session);
123 return session->run_async();
126 NNFW_STATUS nnfw_await(nnfw_session *session)
128 NNFW_RETURN_ERROR_IF_NULL(session);
129 return session->await();
135 * @param session session to the input is to be set
136 * @param index index of input to be set (0-indexed)
137 * @param type type of the input
138 * @param buffer raw buffer for input
139 * @param length size of bytes of input
141 * @return NNFW_STATUS_NO_ERROR if successful
144 NNFW_STATUS nnfw_set_input(nnfw_session *session, uint32_t index, NNFW_TYPE type,
145 const void *buffer, size_t length)
147 NNFW_RETURN_ERROR_IF_NULL(session);
148 return session->set_input(index, type, buffer, length);
154 * @param session session from inference output is to be extracted
155 * @param index index of output to be set (0-indexed)
156 * @param type type of the output
157 * @param buffer raw buffer for output
158 * @param length size of bytes of output
160 * @return NNFW_STATUS_NO_ERROR if successful
163 NNFW_STATUS nnfw_set_output(nnfw_session *session, uint32_t index, NNFW_TYPE type, void *buffer,
166 NNFW_RETURN_ERROR_IF_NULL(session);
167 return session->set_output(index, type, buffer, length);
171 * Get the number of inputs
173 * @param[in] session session from input information is to be extracted
174 * @param[out] number variable which the number of inputs is put into
176 * @return NNFW_STATUS_NO_ERROR if successful
179 NNFW_STATUS nnfw_input_size(nnfw_session *session, uint32_t *number)
181 NNFW_RETURN_ERROR_IF_NULL(session);
182 return session->input_size(number);
186 * Get the number of outputs
188 * @param[in] session session from output information is to be extracted
189 * @param[out] number variable which the number of outputs is put into
191 * @return NNFW_STATUS_NO_ERROR if successful
193 NNFW_STATUS nnfw_output_size(nnfw_session *session, uint32_t *number)
195 NNFW_RETURN_ERROR_IF_NULL(session);
196 return session->output_size(number);
200 * Set the layout of an input
201 * @note The input that does not call this has NNFW_LAYOUT_CHANNELS_LAST layout
203 * @param[in] session session from inference input is to be extracted
204 * @param[in] index index of input to be set (0-indexed)
205 * @param[in] layout layout to set to target input
207 * @return NNFW_STATUS_NO_ERROR if successful
209 NNFW_STATUS nnfw_set_input_layout(nnfw_session *session, uint32_t index, NNFW_LAYOUT layout)
211 NNFW_RETURN_ERROR_IF_NULL(session);
212 return session->set_input_layout(index, layout);
216 * Set the layout of an output
217 * @note The output that does not call this has NNFW_LAYOUT_CHANNELS_LAST layout
219 * @param[in] session session from inference output is to be extracted
220 * @param[in] index index of output to be set (0-indexed)
221 * @param[in] layout layout to set to target output
223 * @return NNFW_STATUS_NO_ERROR if successful
225 NNFW_STATUS nnfw_set_output_layout(nnfw_session *session, uint32_t index, NNFW_LAYOUT layout)
227 NNFW_RETURN_ERROR_IF_NULL(session);
228 return session->set_output_layout(index, layout);
232 * Get i-th input tensor info
234 * @param[in] session session from input information is to be extracted
235 * @param[in] index index of input
236 * @param[out] tensor_info nnfw_tensor_info
238 * @return NNFW_STATUS_NO_ERROR if successful
240 NNFW_STATUS nnfw_input_tensorinfo(nnfw_session *session, uint32_t index,
241 nnfw_tensorinfo *tensor_info)
243 NNFW_RETURN_ERROR_IF_NULL(session);
244 return session->input_tensorinfo(index, tensor_info);
248 * Get i-th output tensor info
250 * @param[in] session session from output information is to be extracted
251 * @param[in] index index of output
252 * @param[out] tensor_info nnfw_tensor_info
254 * @return NNFW_STATUS_NO_ERROR if successful
256 NNFW_STATUS nnfw_output_tensorinfo(nnfw_session *session, uint32_t index,
257 nnfw_tensorinfo *tensor_info)
259 NNFW_RETURN_ERROR_IF_NULL(session);
260 return session->output_tensorinfo(index, tensor_info);
264 * Register custom operation
265 * @param session session to register this operation
266 * @param id operation id
267 * @param info registration info ( eval function, etc. )
268 * @return NNFW_STATUS_NO_ERROR if successful
270 NNFW_STATUS nnfw_register_custom_op_info(nnfw_session *session, const char *id,
271 custom_kernel_registration_info *info)
273 NNFW_RETURN_ERROR_IF_NULL(session);
274 return session->register_custom_operation(id, info->eval_function);
277 NNFW_STATUS nnfw_apply_tensorinfo(nnfw_session *session, uint32_t index,
278 nnfw_tensorinfo tensor_info)
280 NNFW_RETURN_ERROR_IF_NULL(session);
281 return session->apply_tensorinfo(index, tensor_info);
284 NNFW_STATUS nnfw_set_input_tensorinfo(nnfw_session *session, uint32_t index,
285 const nnfw_tensorinfo *tensor_info)
287 NNFW_RETURN_ERROR_IF_NULL(session);
288 return session->set_input_tensorinfo(index, tensor_info);
292 * Set available backends
294 * @param[in] session session to which a avilable backends are set
295 * @param[in] backends available backends on which nnfw uses
297 NNFW_STATUS nnfw_set_available_backends(nnfw_session *session, const char *backends)
299 NNFW_RETURN_ERROR_IF_NULL(session);
300 return session->set_available_backends(backends);
304 * Set the operation's backend
306 * @param[in] session session to be modified
307 * @param[in] op operation to be set
308 * @param[in] backend bakcend on which operation run
310 * @return NNFW_STATUS_NO_ERROR if successful
312 NNFW_STATUS nnfw_set_op_backend(nnfw_session *session, const char *op, const char *backend)
314 NNFW_RETURN_ERROR_IF_NULL(session);
315 return session->set_op_backend(op, backend);
319 * Retrieve uint32 type of nnfw information for given information ID.
321 * @param[in] session session to be queried on
322 * @param[in] information ID to be queried
323 * @param[out] val uint32 value to be returned
325 * @return @c NNFW_STATUS_NO_ERROR if successful
327 NNFW_STATUS nnfw_query_info_u32(nnfw_session *session, NNFW_INFO_ID id, uint32_t *val)
332 case NNFW_INFO_ID_VERSION:
336 return NNFW_STATUS_NO_ERROR;
340 return NNFW_STATUS_ERROR;
342 // It should not be reached.
343 return NNFW_STATUS_ERROR;
346 NNFW_STATUS nnfw_load_circle_from_buffer(nnfw_session *session, uint8_t *buffer, size_t size)
348 NNFW_RETURN_ERROR_IF_NULL(session);
349 return session->load_circle_from_buffer(buffer, size);
352 NNFW_STATUS nnfw_input_tensorindex(nnfw_session *session, const char *tensorname, uint32_t *index)
354 NNFW_RETURN_ERROR_IF_NULL(session);
355 return session->input_tensorindex(tensorname, index);
358 NNFW_STATUS nnfw_output_tensorindex(nnfw_session *session, const char *tensorname, uint32_t *index)
360 NNFW_RETURN_ERROR_IF_NULL(session);
361 return session->output_tensorindex(tensorname, index);