| /* Copyright 2019 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 SIGNAL_SRC_FILTER_BANK_LOG_H_ |
| #define SIGNAL_SRC_FILTER_BANK_LOG_H_ |
| |
| #include <stdint.h> |
| |
| namespace tflite { |
| namespace tflm_signal { |
| // TODO(b/286250473): remove namespace once de-duped libraries above |
| |
| // Apply natural log to each element in array `input` of size `num_channels` |
| // with pre-shift and post scaling. |
| // The operation is roughly equivalent to: |
| // `output` = min(Log(`input` << `correction_bits`) * `output_scale`, INT16_MAX) |
| // Where: |
| // If (input << `correction_bits`) is 1 or 0, the function returns 0 |
| void FilterbankLog(const uint32_t* input, int num_channels, |
| int32_t output_scale, uint32_t correction_bits, |
| int16_t* output); |
| |
| } // namespace tflm_signal |
| } // namespace tflite |
| |
| #endif // SIGNAL_SRC_FILTER_BANK_LOG_H_ |