81 lines
2.6 KiB
C++
81 lines
2.6 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/micro/micro_utils.h"
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#include <cmath>
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#include <cstdint>
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#include <limits>
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/op_macros.h"
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namespace tflite {
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int ElementCount(const TfLiteIntArray& dims) {
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int result = 1;
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for (int i = 0; i < dims.size; ++i) {
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result *= dims.data[i];
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}
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return result;
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}
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void SignedSymmetricPerChannelQuantize(const float* values,
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TfLiteIntArray* dims,
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int quantized_dimension,
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int8_t* quantized_values,
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float* scaling_factors) {
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int input_size = ElementCount(*dims);
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int channel_count = dims->data[quantized_dimension];
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int per_channel_size = input_size / channel_count;
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int stride;
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int channel_stride;
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if (quantized_dimension == 0) {
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stride = 1;
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channel_stride = per_channel_size;
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} else if (quantized_dimension == 3) {
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stride = channel_count;
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channel_stride = 1;
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} else {
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TF_LITE_FATAL("quantized dimension must be 0 or 3");
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}
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// Calculate scales for each channel.
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for (int channel = 0; channel < channel_count; channel++) {
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float min = 0;
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float max = 0;
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for (int i = 0; i < per_channel_size; i++) {
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int idx = channel * channel_stride + i * stride;
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min = fminf(min, values[idx]);
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max = fmaxf(max, values[idx]);
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}
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scaling_factors[channel] =
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fmaxf(fabs(min), fabs(max)) / std::numeric_limits<int8_t>::max();
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for (int i = 0; i < per_channel_size; i++) {
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int idx = channel * channel_stride + i * stride;
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const int32_t quantized_value =
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static_cast<int32_t>(roundf(values[idx] / scaling_factors[channel]));
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// Clamp: just in case some odd numeric offset.
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quantized_values[idx] =
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fminf(std::numeric_limits<int8_t>::max(),
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fmaxf(std::numeric_limits<int8_t>::min() + 1, quantized_value));
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}
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}
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}
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} // namespace tflite
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