| /* Copyright 2018 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/kernels/dequantize.h" |
| |
| #include <stddef.h> |
| |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/optimized/neon_check.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| |
| namespace tflite { |
| namespace ops { |
| namespace builtin { |
| namespace dequantize { |
| |
| struct OpContext { |
| OpContext(TfLiteContext* context, TfLiteNode* node) { |
| input = GetInput(context, node, 0); |
| output = GetOutput(context, node, 0); |
| } |
| const TfLiteTensor* input; |
| TfLiteTensor* output; |
| }; |
| |
| struct OpData { |
| // This boolean value is only used when the input tensor is constant. |
| bool float_dequantized_weights_initialized; |
| }; |
| |
| void* Init(TfLiteContext* context, const char* buffer, size_t length) { |
| auto* op_data = new OpData(); |
| op_data->float_dequantized_weights_initialized = false; |
| return op_data; |
| } |
| |
| void Free(TfLiteContext* context, void* buffer) { |
| delete reinterpret_cast<OpData*>(buffer); |
| } |
| |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 1); |
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
| |
| OpContext op_context(context, node); |
| |
| TF_LITE_ENSURE(context, op_context.input->type == kTfLiteUInt8 || |
| op_context.input->type == kTfLiteInt8 || |
| op_context.input->type == kTfLiteInt16 || |
| op_context.input->type == kTfLiteFloat16); |
| |
| if (op_context.input->type == kTfLiteInt16) { |
| TF_LITE_ENSURE_EQ(context, op_context.input->params.zero_point, 0); |
| } |
| |
| op_context.output->type = kTfLiteFloat32; |
| // If the input tensor is constant, we can persist the dequantized value in |
| // the output tensor. Otherwise we run dequantize upon each eval. |
| if (IsConstantTensor(op_context.input)) { |
| op_context.output->allocation_type = kTfLiteArenaRwPersistent; |
| } |
| return context->ResizeTensor(context, op_context.output, |
| TfLiteIntArrayCopy(op_context.input->dims)); |
| } |
| |
| template <KernelType kernel_type> |
| TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
| OpData* op_data = reinterpret_cast<OpData*>(node->user_data); |
| OpContext op_context(context, node); |
| if (IsConstantTensor(op_context.input) && |
| op_data->float_dequantized_weights_initialized) { |
| return kTfLiteOk; |
| } |
| |
| auto status = DequantizeImpl<kernel_type>(context, node, op_context.input, |
| op_context.output); |
| if (status != kTfLiteOk) { |
| return status; |
| } |
| |
| if (IsConstantTensor(op_context.input)) { |
| op_data->float_dequantized_weights_initialized = true; |
| } |
| return kTfLiteOk; |
| } |
| |
| } // namespace dequantize |
| |
| TfLiteRegistration* Register_DEQUANTIZE_OPT() { |
| static TfLiteRegistration r = { |
| dequantize::Init, dequantize::Free, dequantize::Prepare, |
| dequantize::Eval<dequantize::kGenericOptimized>}; |
| return &r; |
| } |
| |
| TfLiteRegistration* Register_DEQUANTIZE_REF() { |
| static TfLiteRegistration r = {dequantize::Init, dequantize::Free, |
| dequantize::Prepare, |
| dequantize::Eval<dequantize::kReference>}; |
| return &r; |
| } |
| |
| TfLiteRegistration* Register_DEQUANTIZE() { |
| #ifdef USE_NEON |
| return Register_DEQUANTIZE_OPT(); |
| #else |
| return Register_DEQUANTIZE_REF(); |
| #endif |
| } |
| |
| } // namespace builtin |
| } // namespace ops |
| } // namespace tflite |