| /* Copyright 2021 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. |
| ==============================================================================*/ |
| |
| #if defined(VISION_P6) |
| |
| #include <cstdint> |
| |
| #include "tensorflow/lite/c/builtin_op_data.h" |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/common.h" |
| #include "tensorflow/lite/kernels/internal/reference/reduce.h" |
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/xtensa/xtensa.h" |
| #include "tensorflow/lite/micro/kernels/xtensa/xtensa_pad.h" |
| |
| namespace tflite { |
| |
| inline void OperandDims4D(uint32_t* dims, TfLiteTensor* opnd) { |
| for (int i = NumDimensions(opnd) - 1, j = 0; i >= 0; i--, j++) { |
| dims[j] = SizeOfDimension(opnd, i); |
| } |
| return; |
| } |
| |
| TfLiteStatus PadPrepareVision(TfLiteContext* context, TfLiteNode* node) { |
| TFLITE_DCHECK(node->user_data != nullptr); |
| XtensaPadData* data = reinterpret_cast<XtensaPadData*>(node->user_data); |
| |
| MicroContext* micro_context = GetMicroContext(context); |
| TfLiteTensor* input = |
| micro_context->AllocateTempInputTensor(node, /*index=*/0); |
| TfLiteTensor* paddings = |
| micro_context->AllocateTempInputTensor(node, /*index=*/1); |
| TfLiteTensor* constant_values = |
| NumInputs(node) == 3 |
| ? micro_context->AllocateTempInputTensor(node, /*index=*/2) |
| : nullptr; |
| TfLiteTensor* output = |
| micro_context->AllocateTempOutputTensor(node, /*index=*/0); |
| |
| uint32_t inputDims[4] = {1, 1, 1, 1}; |
| OperandDims4D(inputDims, input); |
| |
| const int32_t* paddings_data = GetTensorData<int32_t>(paddings); |
| uint32_t inputRank = NumDimensions(input); |
| |
| uint32_t context_size = 0; |
| uint32_t status = xiPadGetMemReqd_Context(&context_size); |
| TFLITE_DCHECK(status == 0); |
| if (context_size) { |
| void* context_data = |
| context->AllocatePersistentBuffer(context, context_size); |
| if (context_data == nullptr) { |
| return kTfLiteError; |
| } |
| data->p_context = reinterpret_cast<uint8_t*>(context_data); |
| data->context_size = context_size; |
| } |
| int8_t pad_value; |
| if (constant_values == nullptr) { |
| pad_value = static_cast<uint8_t>(data->reference_op_data.output_zero_point); |
| } else { |
| pad_value = *constant_values->data.int8; |
| } |
| |
| status = xiPadSetContext(data->p_context, data->context_size, inputDims, |
| paddings_data, pad_value, inputRank); |
| |
| if (status) { |
| return kTfLiteError; |
| } |
| |
| micro_context->DeallocateTempTfLiteTensor(input); |
| micro_context->DeallocateTempTfLiteTensor(paddings); |
| if (constant_values != nullptr) { |
| micro_context->DeallocateTempTfLiteTensor(constant_values); |
| } |
| micro_context->DeallocateTempTfLiteTensor(output); |
| return kTfLiteOk; |
| } |
| TfLiteStatus PadEvalVision(const XtensaPadData& data, |
| const TfLiteEvalTensor* input, |
| TfLiteEvalTensor* output) { |
| const uint32_t input_size = NumElements(input->dims); |
| const uint32_t output_size = NumElements(output->dims); |
| |
| xiPad(data.p_context, data.context_size, |
| const_cast<int8_t*>(tflite::micro::GetTensorData<int8_t>(input)), |
| input_size, tflite::micro::GetTensorData<int8_t>(output), output_size); |
| return kTfLiteOk; |
| } |
| } // namespace tflite |
| #endif // defined(VISION_P6) |