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- /* Copyright 2022 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_MICRO_KERNELS_SOFTMAX_H_
- #define TENSORFLOW_LITE_MICRO_KERNELS_SOFTMAX_H_
- #include "tensorflow/lite/c/builtin_op_data.h"
- #include "tensorflow/lite/c/common.h"
- #include "tensorflow/lite/kernels/internal/types.h"
- namespace tflite {
- void* SoftmaxInit(TfLiteContext* context, const char* buffer, size_t length);
- // Common helper function to SoftmaxPrepare.
- TfLiteStatus CalculateSoftmaxParams(TfLiteContext* context,
- const TfLiteTensor* input,
- TfLiteTensor* output,
- const TfLiteSoftmaxParams* params,
- SoftmaxParams* op_data);
- TfLiteStatus SoftmaxPrepare(TfLiteContext* context, TfLiteNode* node);
- // This is the most generic TfLiteRegistration. The actual supported types may
- // still be target dependent. The only requirement is that every implementation
- // (reference or optimized) must define this function.
- TfLiteRegistration Register_SOFTMAX();
- #if defined(XTENSA) || defined(CMSIS_NN)
- // Returns a TfLiteRegistration struct for kernel variant that only supports
- // int8 input and int16 output.
- TfLiteRegistration Register_SOFTMAX_INT8_INT16();
- #else
- inline TfLiteRegistration Register_SOFTMAX_INT8_INT16() {
- return Register_SOFTMAX();
- }
- #endif
- #if defined(CMSIS_NN)
- // Returns a TfLiteRegistration struct for kernel variant that only supports
- // int8 input/output and uses the latency optimized implementations.
- TfLiteRegistration Register_SOFTMAX_INT8();
- // Returns a TfLiteRegistration struct for kernel variant that only supports
- // int16 input/output and uses the latency optimized implementations.
- TfLiteRegistration Register_SOFTMAX_INT16();
- #else
- inline TfLiteRegistration Register_SOFTMAX_INT8() { return Register_SOFTMAX(); }
- inline TfLiteRegistration Register_SOFTMAX_INT16() {
- return Register_SOFTMAX();
- }
- #endif
- } // namespace tflite
- #endif // TENSORFLOW_LITE_MICRO_KERNELS_SOFTMAX_H_
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