mirror of
https://github.com/vee1e/tflite-micro.git
synced 2026-09-04 19:27:46 +00:00
6197a422df
* Force FLATBUFFERS_LOCALE_INDEPENDENT=0 With this change, we no longer need a #define in the sources that directly or indrectly include flatbuffers/base.h BUG=http://b/193264978 * Fix xtensa script.
56 lines
2.5 KiB
C++
56 lines
2.5 KiB
C++
/* Copyright 2021 The TensorFlow Authors. 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.
|
|
==============================================================================*/
|
|
|
|
#ifndef THIRD_PARTY_TFLITE_MICRO_TENSORFLOW_LITE_MICRO_FLATBUFFER_UTILS_H_
|
|
#define THIRD_PARTY_TFLITE_MICRO_TENSORFLOW_LITE_MICRO_FLATBUFFER_UTILS_H_
|
|
|
|
#include "flatbuffers/flatbuffers.h"
|
|
#include "flatbuffers/flexbuffers.h"
|
|
#include "tensorflow/lite/schema/schema_generated.h"
|
|
|
|
namespace tflite {
|
|
// Kernels use flexbuffers::Map to pack their init parameters in a tflite file,
|
|
// with the parameter names as map keys and the parameter values as the
|
|
// corresponding map values.
|
|
// Accessing the map values using the flexbuffers:Map class is inline heavy,
|
|
// which can cause the code size to bloat beyond what's reasonable for a micro
|
|
// application. Use this class instead, when possible.
|
|
// FlexbufferWrapper takes advantage of the following properties of
|
|
// flexbuffers::Map:
|
|
// 1. It can be viewed as a flexbuffers::Vector of the values.
|
|
// 2. The values in the vector are ordered alphabetically by their keys.
|
|
// 3. All integer and Boolean values are stored as 64-bit numbers.
|
|
// 4. All floating point values are stored as double precision numbers.
|
|
// The properties are mentioned in the flexbuffers docs, but we rely on
|
|
// a unit test to catch design changes.
|
|
class FlexbufferWrapper : public flexbuffers::Vector {
|
|
public:
|
|
// Construct with a serialized flexbuffer 'buffer' of 'size' bytes
|
|
explicit FlexbufferWrapper(const uint8_t* buffer, size_t size);
|
|
int64_t ElementAsInt64(size_t i) const;
|
|
uint64_t ElementAsUInt64(size_t i) const;
|
|
int32_t ElementAsInt32(size_t i) const;
|
|
bool ElementAsBool(size_t i) const;
|
|
double ElementAsDouble(size_t i) const;
|
|
float ElementAsFloat(size_t i) const;
|
|
};
|
|
|
|
// Return the number of operators in a subgraph tflite
|
|
uint32_t NumSubgraphOperators(const SubGraph* subgraph);
|
|
uint32_t NumSubgraphOperators(const Model* model, int subgraph_idx);
|
|
|
|
} // namespace tflite
|
|
|
|
#endif // THIRD_PARTY_TFLITE_MICRO_TENSORFLOW_LITE_MICRO_FLATBUFFER_UTILS_H_
|