STT-tensorflow/tensorflow/lite/delegates/gpu/common/quantization_util.cc

/* Copyright 2020 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.
==============================================================================*/

#include "tensorflow/lite/delegates/gpu/common/quantization_util.h"

#include <stdint.h>

#include <vector>

#include "absl/container/flat_hash_map.h"
#include "absl/status/status.h"
#include "tensorflow/lite/c/common.h"
#include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"
#include "tensorflow/lite/kernels/internal/tensor_ctypes.h"
#include "tensorflow/lite/kernels/internal/types.h"

namespace tflite {
namespace gpu {
namespace {
void DequantizeInput(
    TfLiteContext* context, int input_index,
    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  if (quant_conversion_map.find(input_index) == quant_conversion_map.end()) {
    return;
  }
  int original_tensor_idx = quant_conversion_map.at(input_index);
  const TfLiteTensor& dequantized_tflite_tensor = context->tensors[input_index];
  const TfLiteTensor& original_tflite_tensor =
      context->tensors[original_tensor_idx];
  DequantizationParams op_params;
  op_params.zero_point = original_tflite_tensor.params.zero_point;
  op_params.scale = original_tflite_tensor.params.scale;
  if (original_tflite_tensor.type == kTfLiteInt8) {
    optimized_ops::Dequantize(op_params,
                              GetTensorShape(&original_tflite_tensor),
                              original_tflite_tensor.data.int8,
                              GetTensorShape(&original_tflite_tensor),
                              dequantized_tflite_tensor.data.f);
  } else if (original_tflite_tensor.type == kTfLiteUInt8) {
    optimized_ops::Dequantize(op_params,
                              GetTensorShape(&original_tflite_tensor),
                              original_tflite_tensor.data.uint8,
                              GetTensorShape(&original_tflite_tensor),
                              dequantized_tflite_tensor.data.f);
  }
}

void QuantizeOutput(TfLiteContext* context, int output_index,
                    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  if (quant_conversion_map.find(output_index) == quant_conversion_map.end()) {
    return;
  }
  int original_tensor_idx = quant_conversion_map.at(output_index);
  const TfLiteTensor& dequantized_tflite_tensor =
      context->tensors[output_index];
  const TfLiteTensor& original_tflite_tensor =
      context->tensors[original_tensor_idx];
  tflite::QuantizationParams op_params;
  op_params.zero_point = original_tflite_tensor.params.zero_point;
  op_params.scale = original_tflite_tensor.params.scale;
  if (original_tflite_tensor.type == kTfLiteInt8) {
    optimized_ops::AffineQuantize(op_params,
                                  GetTensorShape(&original_tflite_tensor),
                                  dequantized_tflite_tensor.data.f,
                                  GetTensorShape(&original_tflite_tensor),
                                  original_tflite_tensor.data.int8);
  } else if (original_tflite_tensor.type == kTfLiteUInt8) {
    optimized_ops::AffineQuantize(op_params,
                                  GetTensorShape(&original_tflite_tensor),
                                  dequantized_tflite_tensor.data.f,
                                  GetTensorShape(&original_tflite_tensor),
                                  original_tflite_tensor.data.uint8);
  }
}
}  // namespace

absl::Status DequantizeInputs(
    TfLiteContext* context, const std::vector<uint32_t>& input_indices,
    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  for (auto index : input_indices) {
    DequantizeInput(context, static_cast<int>(index), quant_conversion_map);
  }
  return absl::OkStatus();
}

absl::Status DequantizeInputs(
    TfLiteContext* context, const std::vector<int64_t>& input_indices,
    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  for (auto index : input_indices) {
    DequantizeInput(context, static_cast<int>(index), quant_conversion_map);
  }
  return absl::OkStatus();
}

absl::Status QuantizeOutputs(
    TfLiteContext* context, const std::vector<uint32_t>& output_indices,
    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  for (auto index : output_indices) {
    QuantizeOutput(context, static_cast<int>(index), quant_conversion_map);
  }

  return absl::OkStatus();
}

absl::Status QuantizeOutputs(
    TfLiteContext* context, const std::vector<int64_t>& output_indices,
    const absl::flat_hash_map<int, int>& quant_conversion_map) {
  for (auto index : output_indices) {
    QuantizeOutput(context, static_cast<int>(index), quant_conversion_map);
  }

  return absl::OkStatus();
}

}  // namespace gpu
}  // namespace tflite