wehub-resource-sync
140 lines
6.2 KiB
C++
140 lines
6.2 KiB
C++
/* Copyright 2018 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 TENSORFLOW_LITE_TOOLS_OPTIMIZE_QUANTIZE_MODEL_H_
|
|
#define TENSORFLOW_LITE_TOOLS_OPTIMIZE_QUANTIZE_MODEL_H_
|
|
|
|
#include <memory>
|
|
#include <unordered_set>
|
|
|
|
#include "tensorflow/lite/context.h"
|
|
#include "tensorflow/lite/core/api/error_reporter.h"
|
|
#include "tensorflow/lite/core/model.h"
|
|
#include "tensorflow/lite/schema/schema_generated.h"
|
|
#include "tensorflow/lite/util.h"
|
|
|
|
namespace tflite {
|
|
namespace optimize {
|
|
|
|
// Quantizes input_model and populates the provided builder with the new model.
|
|
// input_model is required to have min/max information populated in its
|
|
// quantization params.
|
|
//
|
|
// Inputs and output types default to float instead of a quantized type.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(flatbuffers::FlatBufferBuilder* builder,
|
|
ModelT* input_model, ErrorReporter* error_reporter);
|
|
|
|
// Same as above, but the types of quantized inputs and outputs are
|
|
// configurable.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(flatbuffers::FlatBufferBuilder* builder,
|
|
ModelT* input_model, const TensorType& input_type,
|
|
const TensorType& output_type,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Same as above, but can enable allowing float intermediate operations for ops
|
|
// that do not yet support quantizable.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(flatbuffers::FlatBufferBuilder* builder,
|
|
ModelT* input_model, const TensorType& input_type,
|
|
const TensorType& output_type, bool allow_float,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Same as above but with added option of disabling per channel quantization
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(
|
|
flatbuffers::FlatBufferBuilder* builder, ModelT* input_model,
|
|
const TensorType& input_type, const TensorType& output_type,
|
|
bool allow_float, bool disable_per_channel,
|
|
bool disable_per_channel_quantization_for_dense_layers,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Same as above but with added option of handling quantization of external
|
|
// state tensors. This assumes first input and output tensors are ouputs and
|
|
// rest are state tensors which are quantized later with type as
|
|
// activation type (hence no fake quant ops).
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(
|
|
flatbuffers::FlatBufferBuilder* builder, ModelT* input_model,
|
|
const TensorType& input_type, const TensorType& output_type,
|
|
bool allow_float, bool disable_per_channel,
|
|
bool disable_per_channel_quantization_for_dense_layers,
|
|
ErrorReporter* error_reporter, bool handle_external_state);
|
|
|
|
// Same as above, but enables only quantizing an allowlist of operations,
|
|
// specified by their operator output name.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(flatbuffers::FlatBufferBuilder* builder,
|
|
ModelT* input_model, const TensorType& input_type,
|
|
const TensorType& output_type, bool allow_float,
|
|
const std::unordered_set<string>& operator_names,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Same as above, but enables to provide activation type, which
|
|
// could be TensorType_INT16 or TensorType_INT8.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModel(flatbuffers::FlatBufferBuilder* builder,
|
|
ModelT* model, const TensorType& input_type,
|
|
const TensorType& output_type, bool allow_float,
|
|
const std::unordered_set<string>& operator_names,
|
|
const TensorType& activations_type,
|
|
const TensorType& bias_type,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Same as above, but all operators supporting quantization are quantized.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModelAllOperators(
|
|
flatbuffers::FlatBufferBuilder* builder, ModelT* model,
|
|
const TensorType& input_type, const TensorType& output_type,
|
|
bool allow_float, const TensorType& activations_type,
|
|
const TensorType& bias_type, ErrorReporter* error_reporter);
|
|
|
|
// Same as above, but allows disabling per channel quantization.
|
|
//
|
|
// Note: This is a private API, subject to change.
|
|
TfLiteStatus QuantizeModelAllOperators(
|
|
flatbuffers::FlatBufferBuilder* builder, ModelT* model,
|
|
const TensorType& input_type, const TensorType& output_type,
|
|
bool allow_float, const TensorType& activations_type,
|
|
const TensorType& bias_type, bool disable_per_channel,
|
|
bool disable_per_channel_quantization_for_dense_layers,
|
|
ErrorReporter* error_reporter);
|
|
|
|
// Quantizes input_model and populates the provided builder with the new model
|
|
// with all possible input parameters including disabling per_channel
|
|
// quantization.
|
|
//
|
|
// All functions above call this function underneath.
|
|
TfLiteStatus QuantizeModel(
|
|
flatbuffers::FlatBufferBuilder* builder, ModelT* model,
|
|
const TensorType& input_type, const TensorType& output_type,
|
|
bool allow_float, const std::unordered_set<string>& operator_names,
|
|
const TensorType& activations_type, const TensorType& bias_type,
|
|
bool disable_per_channel,
|
|
bool disable_per_channel_quantization_for_dense_layers,
|
|
ErrorReporter* error_reporter, bool handle_external_state);
|
|
|
|
} // namespace optimize
|
|
} // namespace tflite
|
|
|
|
#endif // TENSORFLOW_LITE_TOOLS_OPTIMIZE_QUANTIZE_MODEL_H_
|