codekingpro/portable-devtools
114k
1/*
2 * SPDX-FileCopyrightText: Copyright (c) 1993-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
3 * SPDX-License-Identifier: Apache-2.0
4 *
5 * Licensed under the Apache License, Version 2.0 (the "License");
6 * you may not use this file except in compliance with the License.
7 * You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17
18#ifndef NV_ONNX_PARSER_H
19#define NV_ONNX_PARSER_H
20
21#include "NvInfer.h"
22#include <stddef.h>
23#include <string>
24#include <vector>
25
26//!
27//! \file NvOnnxParser.h
28//!
29//! This is the API for the ONNX Parser
30//!
31
32#define NV_ONNX_PARSER_MAJOR 0
33#define NV_ONNX_PARSER_MINOR 1
34#define NV_ONNX_PARSER_PATCH 0
35
36static constexpr int32_t NV_ONNX_PARSER_VERSION
37 = ((NV_ONNX_PARSER_MAJOR * 10000) + (NV_ONNX_PARSER_MINOR * 100) + NV_ONNX_PARSER_PATCH);
38
39//!
40//! \typedef SubGraph_t
41//!
42//! \brief The data structure containing the parsing capability of
43//! a set of nodes in an ONNX graph.
44//!
45typedef std::pair<std::vector<size_t>, bool> SubGraph_t;
46
47//!
48//! \typedef SubGraphCollection_t
49//!
50//! \brief The data structure containing all SubGraph_t partitioned
51//! out of an ONNX graph.
52//!
53typedef std::vector<SubGraph_t> SubGraphCollection_t;
54
55//!
56//! \namespace nvonnxparser
57//!
58//! \brief The TensorRT ONNX parser API namespace
59//!
60namespace nvonnxparser
61{
62
63//! \return the numerical value of the highest-valued enumerator for type T.
64//! It must be specialized for each enum type that uses it.
65//! {$nv-internal-release begin}
66//! \note This is different from nvinfer1::EnumMax<T>(), which is one more than that.
67//! {$nv-internal-release end}
68template <typename T>
69constexpr int32_t EnumMax() noexcept = delete;
70
71//!
72//! \enum ErrorCode
73//!
74//! \brief The type of error that the parser or refitter may return
75//!
76enum class ErrorCode : int
77{
78 kSUCCESS = 0,
79 kINTERNAL_ERROR = 1,
80 kMEM_ALLOC_FAILED = 2,
81 kMODEL_DESERIALIZE_FAILED = 3,
82 kINVALID_VALUE = 4,
83 kINVALID_GRAPH = 5,
84 kINVALID_NODE = 6,
85 kUNSUPPORTED_GRAPH = 7,
86 kUNSUPPORTED_NODE = 8,
87 kUNSUPPORTED_NODE_ATTR = 9,
88 kUNSUPPORTED_NODE_INPUT = 10,
89 kUNSUPPORTED_NODE_DATATYPE = 11,
90 kUNSUPPORTED_NODE_DYNAMIC = 12,
91 kUNSUPPORTED_NODE_SHAPE = 13,
92 kREFIT_FAILED = 14
93};
94
95//! Specialization. See `nvonnxparser::EnumMax()` for details.
96template <>
97constexpr int32_t EnumMax<ErrorCode>() noexcept
98{
99 return 14;
100}
101
102//!
103//! \brief Represents one or more OnnxParserFlag values using binary OR
104//! operations, e.g., 1U << OnnxParserFlag::kNATIVE_INSTANCENORM
105//!
106//! \see IParser::setFlags() and IParser::getFlags()
107//!
108using OnnxParserFlags
109 = uint32_t;
110
111enum class OnnxParserFlag : int32_t
112{
113 //! Parse the ONNX model into the INetworkDefinition with the intention of using TensorRT's native layer
114 //! implementation over the plugin implementation for InstanceNormalization nodes.
115 //! This flag is required when building version-compatible or hardware-compatible engines.
116 //! This flag is set to be ON by default.
117 kNATIVE_INSTANCENORM = 0,
118 //! Enable UINT8 as a quantization data type and asymmetric quantization with non-zero zero-point values
119 //! in Quantize and Dequantize nodes. This flag is set to be OFF by default.
120 //! The resulting engine must be built targeting DLA version >= 3.16.
121 kENABLE_UINT8_AND_ASYMMETRIC_QUANTIZATION_DLA = 1,
122 //! Parse the ONNX model with per-node validation for DLA. If the model is not fully supported by DLA, then
123 //! parsing will fail. If this flag is set, isSubGraphSupported() will also return capability in the context of DLA
124 //! support. When this flag is set, a valid IBuilderConfig must be provided to the parser via setBuilderConfig().
125 // This flag is set to be OFF by default.
126 kREPORT_CAPABILITY_DLA = 2,
127 //! Allow a loaded plugin with the same name as an ONNX operator type to override the default ONNX implementation,
128 //! even if the plugin namespace attribute is not set.
129 //! Useful for custom plugins that replace standard ONNX operators, such as alternative implementations for better
130 //! performance. This flag is set to be OFF by default.
131 kENABLE_PLUGIN_OVERRIDE = 3,
132 //! Opportunistically rewrite or modify layers to make them more amenable to running on DLA.
133 kADJUST_FOR_DLA = 4
134};
135
136//! Specialization. See `nvonnxparser::EnumMax()` for details.
137template <>
138constexpr int32_t EnumMax<OnnxParserFlag>() noexcept
139{
140 return 3;
141}
142
143//!
144//! \class IParserError
145//!
146//! \brief an object containing information about an error
147//!
148class IParserError
149{
150public:
151 //!
152 //!\brief the error code.
153 //!
154 virtual ErrorCode code() const = 0;
155 //!
156 //!\brief description of the error.
157 //!
158 virtual char const* desc() const = 0;
159 //!
160 //!\brief source file in which the error occurred.
161 //!
162 virtual char const* file() const = 0;
163 //!
164 //!\brief source line at which the error occurred.
165 //!
166 virtual int line() const = 0;
167 //!
168 //!\brief source function in which the error occurred.
169 //!
170 virtual char const* func() const = 0;
171 //!
172 //!\brief index of the ONNX model node in which the error occurred.
173 //!
174 virtual int node() const = 0;
175 //!
176 //!\brief name of the node in which the error occurred.
177 //!
178 virtual char const* nodeName() const = 0;
179 //!
180 //!\brief name of the node operation in which the error occurred.
181 //!
182 virtual char const* nodeOperator() const = 0;
183 //!
184 //!\brief A list of the local function names, from the top level down, constituting the current
185 //! stack trace in which the error occurred. A top-level node that is not inside any
186 //! local function would return a nullptr.
187 //!
188 virtual char const* const* localFunctionStack() const = 0;
189 //!
190 //!\brief The size of the stack of local functions at the point where the error occurred.
191 //! A top-level node that is not inside any local function would correspond to
192 // a stack size of 0.
193 //!
194 virtual int32_t localFunctionStackSize() const = 0;
195
196protected:
197 virtual ~IParserError() {}
198};
199
200//!
201//! \class IParser
202//!
203//! \brief an object for parsing ONNX models into a TensorRT network definition
204//!
205//! \warning If the ONNX model has a graph output with the same name as a graph input,
206//! the output will be renamed by prepending "__".
207//!
208//! \warning Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.
209//!
210class IParser
211{
212public:
213 //!
214 //! \brief Parse a serialized ONNX model into the TensorRT network.
215 //! This method has very limited diagnostics. If parsing the serialized model
216 //! fails for any reason (e.g. unsupported IR version, unsupported opset, etc.)
217 //! it the user responsibility to intercept and report the error.
218 //! To obtain a better diagnostic, use the parseFromFile method below.
219 //!
220 //! \param serialized_onnx_model Pointer to the serialized ONNX model. Can be freed after this function returns.
221 //! \param serialized_onnx_model_size Size of the serialized ONNX model
222 //! in bytes
223 //! \param model_path Absolute path to the model file for loading external weights if required
224 //! \return true if the model was parsed successfully
225 //! \see getNbErrors() getError()
226 //!
227 virtual bool parse(
228 void const* serialized_onnx_model, size_t serialized_onnx_model_size, const char* model_path = nullptr) noexcept
229 = 0;
230
231 //!
232 //! \brief Parse an onnx model file, which can be a binary protobuf or a text onnx model
233 //! calls parse method inside.
234 //!
235 //! \param onnxModelFile name
236 //! \param verbosity Level
237 //!
238 //! \return true if the model was parsed successfully
239 //!
240 //!
241 virtual bool parseFromFile(const char* onnxModelFile, int verbosity) noexcept = 0;
242
243 //!
244 //! [DEPRECATED] Deprecated in TensorRT 10.1. See supportsModelV2.
245 //!
246 //! \brief Check whether TensorRT supports a particular ONNX model.
247 //! If the function returns True, one can proceed to engine building
248 //! without having to call \p parse or \p parseFromFile.
249 //!
250 //! \param serialized_onnx_model Pointer to the serialized ONNX model. Can be freed after this function returns.
251 //! \param serialized_onnx_model_size Size of the serialized ONNX model
252 //! in bytes
253 //! \param sub_graph_collection Container to hold supported subgraphs
254 //! \param model_path Absolute path to the model file for loading external weights if required
255 //! \return true if the model is supported
256 //!
257 TRT_DEPRECATED virtual bool supportsModel(void const* serialized_onnx_model, size_t serialized_onnx_model_size,
258 SubGraphCollection_t& sub_graph_collection, const char* model_path = nullptr) noexcept = 0;
259
260 //!
261 //! [DEPRECATED] Deprecated in TensorRT 10.13. See loadInitializer().
262 //!
263 //!\brief Parse a serialized ONNX model into the TensorRT network
264 //! with consideration of user provided weights
265 //!
266 //! \param serialized_onnx_model Pointer to the serialized ONNX model. Can be freed after this function returns.
267 //! \param serialized_onnx_model_size Size of the serialized ONNX model
268 //! in bytes
269 //! \return true if the model was parsed successfully
270 //! \see getNbErrors() getError()
271 //!
272 TRT_DEPRECATED virtual bool parseWithWeightDescriptors(
273 void const* serialized_onnx_model, size_t serialized_onnx_model_size) noexcept = 0;
274
275 //!
276 //!\brief Returns whether the specified operator may be supported by the
277 //! parser.
278 //!
279 //! Note that a result of true does not guarantee that the operator will be
280 //! supported in all cases (i.e., this function may return false-positives).
281 //!
282 //! \param op_name The name of the ONNX operator to check for support
283 //!
284 virtual bool supportsOperator(const char* op_name) const noexcept = 0;
285
286 //!
287 //!\brief Get the number of errors that occurred during prior calls to
288 //! \p parse
289 //!
290 //! \see getError() clearErrors() IParserError
291 //!
292 virtual int getNbErrors() const noexcept = 0;
293
294 //!
295 //!\brief Get an error that occurred during prior calls to \p parse
296 //!
297 //! \see getNbErrors() clearErrors() IParserError
298 //!
299 virtual IParserError const* getError(int index) const noexcept = 0;
300
301 //!
302 //!\brief Clear errors from prior calls to \p parse
303 //!
304 //! \see getNbErrors() getError() IParserError
305 //!
306 virtual void clearErrors() noexcept = 0;
307
308 virtual ~IParser() noexcept = default;
309
310 //!
311 //! \brief Query the plugin libraries needed to implement operations used by the parser in a version-compatible
312 //! engine.
313 //!
314 //! This provides a list of plugin libraries on the filesystem needed to implement operations
315 //! in the parsed network. If you are building a version-compatible engine using this network,
316 //! provide this list to IBuilderConfig::setPluginsToSerialize to serialize these plugins along
317 //! with the version-compatible engine, or, if you want to ship these plugin libraries externally
318 //! to the engine, ensure that IPluginRegistry::loadLibrary is used to load these libraries in the
319 //! appropriate runtime before deserializing the corresponding engine.
320 //!
321 //! \param[out] nbPluginLibs Returns the number of plugin libraries in the array, or -1 if there was an error.
322 //! \return Array of `nbPluginLibs` C-strings describing plugin library paths on the filesystem if nbPluginLibs > 0,
323 //! or nullptr otherwise. This array is owned by the IParser, and the pointers in the array are only valid until
324 //! the next call to parse(), supportsModel(), parseFromFile(), or parseWithWeightDescriptors().
325 //!
326 virtual char const* const* getUsedVCPluginLibraries(int64_t& nbPluginLibs) const noexcept = 0;
327
328 //!
329 //! \brief Set the parser flags.
330 //!
331 //! The flags are listed in the OnnxParserFlag enum.
332 //!
333 //! \param OnnxParserFlags The flags used when parsing an ONNX model.
334 //!
335 //! \note This function will override the previous set flags, rather than bitwise ORing the new flag.
336 //!
337 //! \see getFlags()
338 //!
339 virtual void setFlags(OnnxParserFlags onnxParserFlags) noexcept = 0;
340
341 //!
342 //! \brief Get the parser flags. Defaults to 0.
343 //!
344 //! \return The parser flags as a bitmask.
345 //!
346 //! \see setFlags()
347 //!
348 virtual OnnxParserFlags getFlags() const noexcept = 0;
349
350 //!
351 //! \brief clear a parser flag.
352 //!
353 //! clears the parser flag from the enabled flags.
354 //!
355 //! \see setFlags()
356 //!
357 virtual void clearFlag(OnnxParserFlag onnxParserFlag) noexcept = 0;
358
359 //!
360 //! \brief Set a single parser flag.
361 //!
362 //! Add the input parser flag to the already enabled flags.
363 //!
364 //! \see setFlags()
365 //!
366 virtual void setFlag(OnnxParserFlag onnxParserFlag) noexcept = 0;
367
368 //!
369 //! \brief Returns true if the parser flag is set
370 //!
371 //! \see getFlags()
372 //!
373 //! \return True if flag is set, false if unset.
374 //!
375 virtual bool getFlag(OnnxParserFlag onnxParserFlag) const noexcept = 0;
376
377 //!
378 //!\brief Return the i-th output ITensor object for the ONNX layer "name".
379 //!
380 //! Return the i-th output ITensor object for the ONNX layer "name".
381 //! If "name" is not found or i is out of range, return nullptr.
382 //! In the case of multiple nodes sharing the same name this function will return
383 //! the output tensors of the first instance of the node in the ONNX graph.
384 //!
385 //! \param name The name of the ONNX layer.
386 //!
387 //! \param i The index of the output. i must be in range [0, layer.num_outputs).
388 //!
389 virtual nvinfer1::ITensor const* getLayerOutputTensor(char const* name, int64_t i) noexcept = 0;
390
391 //!
392 //! \brief Check whether TensorRT supports a particular ONNX model.
393 //! If the function returns True, one can proceed to engine building
394 //! without having to call \p parse or \p parseFromFile.
395 //! Results can be queried through \p getNbSubgraphs, \p isSubgraphSupported,
396 //! \p getSubgraphNodes.
397 //!
398 //! \param serializedOnnxModel Pointer to the serialized ONNX model. Can be freed after this function returns.
399 //! \param serializedOnnxModelSize Size of the serialized ONNX model in bytes
400 //! \param modelPath Absolute path to the model file for loading external weights if required
401 //! \return true if the model is supported
402 //!
403 virtual bool supportsModelV2(
404 void const* serializedOnnxModel, size_t serializedOnnxModelSize, char const* modelPath = nullptr) noexcept = 0;
405
406 //!
407 //! \brief Get the number of subgraphs. Calling this function before calling \p supportsModelV2 results in undefined
408 //! behavior.
409 //!
410 //!
411 //! \return Number of subgraphs.
412 //!
413 virtual int64_t getNbSubgraphs() noexcept = 0;
414
415 //!
416 //! \brief Returns whether the subgraph is supported. Calling this function before calling \p supportsModelV2
417 //! results in undefined behavior.
418 //!
419 //!
420 //! \param index Index of the subgraph.
421 //! \return Whether the subgraph is supported.
422 //!
423 virtual bool isSubgraphSupported(int64_t const index) noexcept = 0;
424
425 //!
426 //! \brief Get the nodes of the specified subgraph. Calling this function before calling \p supportsModelV2 results
427 //! in undefined behavior.
428 //!
429 //!
430 //! \param index Index of the subgraph.
431 //! \param subgraphLength Returns the length of the subgraph as reference.
432 //!
433 //! \return Pointer to the subgraph nodes array. This pointer is owned by the Parser.
434 //!
435 virtual int64_t* getSubgraphNodes(int64_t const index, int64_t& subgraphLength) noexcept = 0;
436
437 //!
438 //! \brief Load a serialized ONNX model into the parser. Unlike the parse(), parseFromFile(), or
439 //! parseWithWeightDescriptors() functions, this function does not immediately convert the model into a TensorRT
440 //! INetworkDefinition. Using this function allows users to provide their own initializers for the ONNX model
441 //! through the loadInitializer() function.
442 //!
443 //! Only one model can be loaded at a time. Subsequent calls to loadModelProto() will result in an error.
444 //!
445 //! To begin the conversion of the model into a TensorRT INetworkDefinition, use parseModelProto().
446 //!
447 //! \param serializedOnnxModel Pointer to the serialized ONNX model. Can be freed after this function returns.
448 //! \param serializedOnnxModelSize Size of the serialized ONNX model in bytes.
449 //! \param modelPath Absolute path to the model file for loading external weights if required.
450 //! \return true if the model was loaded successfully
451 //! \see getNbErrors() getError()
452 //!
453 virtual bool loadModelProto(
454 void const* serializedOnnxModel, size_t serializedOnnxModelSize, char const* modelPath = nullptr) noexcept = 0;
455
456 //!
457 //! \brief Prompt the ONNX parser to load an initializer with user-provided binary data.
458 //! The lifetime of the data must exceed the lifetime of the parser.
459 //!
460 //! All user-provided initializers must be provided prior to calling refitModelProto().
461 //!
462 //! This function can be called multiple times to specify the names of multiple initializers.
463 //!
464 //! Calling this function with an initializer previously specified will overwrite the previous instance.
465 //!
466 //!
467 //! This function will return false if initializer validation fails. Possible validation errors are:
468 //! * This function was called prior to loadModelProto().
469 //! * The requested initializer was not found in the model.
470 //! * The size of the data provided is different from the corresponding initializer in the model.
471 //!
472 //! \param name Name of the initializer.
473 //! \param data Binary data containing the values of the initializer.
474 //! \param size Size of the initializer in bytes.
475 //! \return true if the initializer was loaded successfully
476 //! \see loadModelProto()
477 //!
478 virtual bool loadInitializer(char const* name, void const* data, size_t size) noexcept = 0;
479
480 //! \brief Begin the parsing and conversion process of the loaded ONNX model into a TensorRT INetworkDefinition.
481 //!
482 //! \return true if conversion was successful
483 //! \see getNbErrors() getError() loadModelProto() loadModelProtoFromFile()
484 //!
485 virtual bool parseModelProto() noexcept = 0;
486
487 //!
488 //! \brief Set the BuilderConfig for the parser.
489 //!
490 //! \return true if the IBuilderConfig was set successfully, false otherwise.
491 //!
492 virtual bool setBuilderConfig(const nvinfer1::IBuilderConfig* const builderConfig) noexcept = 0;
493};
494
495//!
496//! \class IParserRefitter
497//!
498//! \brief An interface designed to refit weights from an ONNX model.
499//!
500//! \warning Do not inherit from this class, as doing so will break forward-compatibility of the API and ABI.
501//!
502class IParserRefitter
503{
504public:
505 //!
506 //! \brief Load a serialized ONNX model from memory and perform weight refit.
507 //!
508 //! \param serializedOnnxModel Pointer to the serialized ONNX model
509 //! \param serializedOnnxModelSize Size of the serialized ONNX model
510 //! in bytes
511 //! \param modelPath Absolute path to the model file for loading external weights if required
512 //! \return true if all the weights in the engine were refit successfully.
513 //!
514 //! The serialized ONNX model must be identical to the one used to generate the engine
515 //! that will be refit.
516 //!
517 virtual bool refitFromBytes(
518 void const* serializedOnnxModel, size_t serializedOnnxModelSize, char const* modelPath = nullptr) noexcept
519 = 0;
520
521 //!
522 //! \brief Load and parse a ONNX model from disk and perform weight refit.
523 //!
524 //! \param onnxModelFile Path to the ONNX model to load from disk.
525 //!
526 //! \return true if the model was loaded successfully, and if all the weights in the engine were refit successfully.
527 //!
528 //! The provided ONNX model must be identical to the one used to generate the engine
529 //! that will be refit.
530 //!
531 virtual bool refitFromFile(char const* onnxModelFile) noexcept = 0;
532
533 //!
534 //!\brief Get the number of errors that occurred during prior calls to \p refitFromBytes or \p refitFromFile
535 //!
536 //! \see getError() IParserError
537 //!
538 virtual int32_t getNbErrors() const noexcept = 0;
539
540 //!
541 //!\brief Get an error that occurred during prior calls to \p refitFromBytes or \p refitFromFile
542 //!
543 //! \see getNbErrors() IParserError
544 //!
545 virtual IParserError const* getError(int32_t index) const noexcept = 0;
546
547 //!
548 //!\brief Clear errors from prior calls to \p refitFromBytes or \p refitFromFile
549 //!
550 //! \see getNbErrors() getError() IParserError
551 //!
552 virtual void clearErrors() = 0;
553
554 virtual ~IParserRefitter() noexcept = default;
555
556 //!
557 //! \brief Load a serialized ONNX model into the parser. Unlike the refit(), or refitFromFile()
558 //! functions, this function does not immediately begin the refit process. Using this function
559 //! allows users to provide their own initializers for the ONNX model through the loadInitializer() function.
560 //!
561 //! Only one model can be loaded at a time. Subsequent calls to loadModelProto() will result in an error.
562 //!
563 //! To begin the refit process, use refitModelProto().
564 //!
565 //! \param serializedOnnxModel Pointer to the serialized ONNX model. Can be freed after this function returns.
566 //! \param serializedOnnxModelSize Size of the serialized ONNX model in bytes.
567 //! \param modelPath Absolute path to the model file for loading external weights if required.
568 //! \return true if the model was loaded successfully
569 //! \see getNbErrors() getError()
570 //!
571 virtual bool loadModelProto(
572 void const* serializedOnnxModel, size_t serializedOnnxModelSize, char const* modelPath = nullptr) noexcept = 0;
573
574 //!
575 //! \brief Prompt the ONNX refitter to load an initializer with user-provided binary data.
576 //! The lifetime of the data must exceed the lifetime of the refitter.
577 //!
578 //! All user-provided initializers must be provided prior to calling refitModelProto().
579 //!
580 //! This function can be called multiple times to specify the names of multiple initializers.
581 //!
582 //! Calling this function with an initializer previously specified will overwrite the previous instance.
583 //!
584 //! This function will return false if initializer validation fails. Possible validation errors are:
585 //! * This function was called prior to loadModelProto()
586 //! * The requested initializer was not found in the model.
587 //! * The size of the data provided is different from the corresponding initializer in the model.
588 //!
589 //! \param name Name of the initializer.
590 //! \param data Binary data containing the values of the initializer.
591 //! \param size Size of the initializer in bytes.
592 //! \return true if the initializer was loaded successfully
593 //! \see loadModelProto()
594 //!
595 virtual bool loadInitializer(char const* name, void const* data, size_t size) noexcept = 0;
596
597 //! \brief Begin the refit process from the loaded ONNX model.
598 //!
599 //! \return true if refit was successful
600 //! \see getNbErrors() getError() loadModelProto()
601 //!
602 virtual bool refitModelProto() noexcept = 0;
603};
604
605} // namespace nvonnxparser
606
607extern "C" TENSORRTAPI void* createNvOnnxParser_INTERNAL(void* network, void* logger, int version) noexcept;
608extern "C" TENSORRTAPI void* createNvOnnxParserRefitter_INTERNAL(
609 void* refitter, void* logger, int32_t version) noexcept;
610extern "C" TENSORRTAPI int getNvOnnxParserVersion() noexcept;
611
612namespace nvonnxparser
613{
614
615namespace
616{
617
618//!
619//! \brief Create a new parser object
620//!
621//! \param network The network definition that the parser will write to
622//! \param logger The logger to use
623//! \return a new parser object or NULL if an error occurred
624//!
625//! Any input dimensions that are constant should not be changed after parsing,
626//! because correctness of the translation may rely on those constants.
627//! Changing a dynamic input dimension, i.e. one that translates to -1 in
628//! TensorRT, to a constant is okay if the constant is consistent with the model.
629//! Each instance of the parser is designed to only parse one ONNX model once.
630//!
631//! \see IParser
632//!
633inline IParser* createParser(nvinfer1::INetworkDefinition& network, nvinfer1::ILogger& logger) noexcept
634{
635 return static_cast<IParser*>(createNvOnnxParser_INTERNAL(&network, &logger, NV_ONNX_PARSER_VERSION));
636}
637
638//!
639//! \brief Create a new ONNX refitter object
640//!
641//! \param refitter The Refitter object used to refit the model
642//! \param logger The logger to use
643//! \return a new ParserRefitter object or NULL if an error occurred
644//!
645//! \see IParserRefitter
646//!
647inline IParserRefitter* createParserRefitter(nvinfer1::IRefitter& refitter, nvinfer1::ILogger& logger) noexcept
648{
649 return static_cast<IParserRefitter*>(
650 createNvOnnxParserRefitter_INTERNAL(&refitter, &logger, NV_ONNX_PARSER_VERSION));
651}
652
653} // namespace
654
655} // namespace nvonnxparser
656
657#endif // NV_ONNX_PARSER_H
658