| /* |
| * Copyright 2024 Google LLC |
| * |
| * 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 TFLM_OPT_OPT_H_ |
| #define TFLM_OPT_OPT_H_ |
| |
| /* clang-format off */ |
| #include <cstring> |
| #include "tensorflow/lite/kernels/internal/runtime_shape.h" |
| #include "tensorflow/lite/kernels/internal/types.h" |
| /* clang-format on */ |
| |
| namespace kelvin::opt { |
| void* Memcpy(void* dst, const void* src, size_t n); |
| void ElementwiseAddS8(const int8_t* input1, const int8_t* input2, |
| const int32_t input1_offset, const int32_t input1_mult, |
| const int32_t input1_shift, const int32_t input2_offset, |
| const int32_t input2_mult, const int32_t input2_shift, |
| const int32_t left_shift, int8_t* output, |
| const int32_t output_offset, const int32_t output_mult, |
| const int32_t output_shift, |
| const int32_t output_activation_min, |
| const int32_t output_activation_max, |
| const int32_t block_size); |
| void ElementwiseAddS16(const int16_t* input1, const int16_t* input2, |
| const int32_t input1_offset, const int32_t input1_mult, |
| const int32_t input1_shift, const int32_t input2_offset, |
| const int32_t input2_mult, const int32_t input2_shift, |
| const int32_t left_shift, int16_t* output, |
| const int32_t output_offset, const int32_t output_mult, |
| const int32_t output_shift, |
| const int32_t output_activation_min, |
| const int32_t output_activation_max, |
| const int32_t block_size); |
| void ElementwiseAddS32(const int32_t* input1, const int32_t* input2, |
| int32_t* output, const int32_t output_activation_min, |
| const int32_t output_activation_max, |
| const int32_t block_size); |
| void LeakyReluS8(const int8_t* input, int8_t* output, const int32_t block_size, |
| const int32_t input_zero_point, |
| const int32_t output_zero_point, |
| const int32_t output_multiplier_alpha, |
| const int32_t output_shift_alpha, |
| const int32_t output_multiplier_identity, |
| const int32_t output_shift_identity); |
| void LeakyReluS16(const int16_t* input, int16_t* output, |
| const int32_t block_size, const int32_t input_zero_point, |
| const int32_t output_zero_point, |
| const int32_t output_multiplier_alpha, |
| const int32_t output_shift_alpha, |
| const int32_t output_multiplier_identity, |
| const int32_t output_shift_identity); |
| void ConvS16B32(const tflite::ConvParams& params, |
| const int32_t* output_multiplier, const int32_t* output_shift, |
| const tflite::RuntimeShape& input_shape, |
| const int16_t* input_data, |
| const tflite::RuntimeShape& filter_shape, |
| const int8_t* filter_data, |
| const tflite::RuntimeShape& bias_shape, |
| const int32_t* bias_data, |
| const tflite::RuntimeShape& output_shape, int16_t* output_data); |
| void ConvS16B64(const tflite::ConvParams& params, |
| const int32_t* output_multiplier, const int32_t* output_shift, |
| const tflite::RuntimeShape& input_shape, |
| const int16_t* input_data, |
| const tflite::RuntimeShape& filter_shape, |
| const int8_t* filter_data, |
| const tflite::RuntimeShape& bias_shape, |
| const int64_t* bias_data, |
| const tflite::RuntimeShape& output_shape, int16_t* output_data); |
| void ConvS8(const tflite::ConvParams& params, const int32_t* output_multiplier, |
| const int32_t* output_shift, |
| const tflite::RuntimeShape& input_shape, const int8_t* input_data, |
| const tflite::RuntimeShape& filter_shape, const int8_t* filter_data, |
| const tflite::RuntimeShape& bias_shape, const int32_t* bias_data, |
| const tflite::RuntimeShape& output_shape, int8_t* output_data); |
| void DepthwiseConvS8( |
| const tflite::DepthwiseParams& params, const int32_t* output_multiplier, |
| const int32_t* output_shift, const tflite::RuntimeShape& input_shape, |
| const int8_t* input_data, const tflite::RuntimeShape& filter_shape, |
| const int8_t* filter_data, const tflite::RuntimeShape& bias_shape, |
| const int32_t* bias_data, const tflite::RuntimeShape& output_shape, |
| int8_t* output_data); |
| void DepthwiseConvS16( |
| const tflite::DepthwiseParams& params, const int32_t* output_multiplier, |
| const int32_t* output_shift, const tflite::RuntimeShape& input_shape, |
| const int16_t* input_data, const tflite::RuntimeShape& filter_shape, |
| const int8_t* filter_data, const tflite::RuntimeShape& bias_shape, |
| const int64_t* bias_data, const tflite::RuntimeShape& output_shape, |
| int16_t* output_data); |
| void MaxPoolS8(const tflite::PoolParams& params, |
| const tflite::RuntimeShape& input_shape, |
| const int8_t* input_data, |
| const tflite::RuntimeShape& output_shape, int8_t* output_data); |
| |
| } // namespace kelvin::opt |
| |
| #endif // TFLM_OPT_OPT_H_ |