| /* 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. |
| ==============================================================================*/ |
| |
| #include "tensorflow/lite/kernels/internal/reference/space_to_batch_nd.h" |
| |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
| #include "tensorflow/lite/kernels/internal/types.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| #include "tensorflow/lite/micro/kernels/kernel_util.h" |
| |
| namespace tflite { |
| |
| namespace { |
| |
| constexpr int kInputTensor = 0; |
| constexpr int kBlockShapeTensor = 1; |
| constexpr int kCropsTensor = 2; |
| constexpr int kOutputTensor = 0; |
| |
| constexpr int kInputDims = 4; |
| constexpr int kOutputDims = 4; |
| |
| } // namespace. |
| |
| void* Init(TfLiteContext* context, const char* buffer, size_t length) { |
| TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr); |
| return context->AllocatePersistentBuffer(context, sizeof(SpaceToBatchParams)); |
| } |
| |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 3); |
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
| |
| const TfLiteTensor* input = GetInput(context, node, kInputTensor); |
| TfLiteTensor* output = GetOutput(context, node, kOutputTensor); |
| TF_LITE_ENSURE(context, input != nullptr && output != nullptr); |
| |
| SpaceToBatchParams* params = |
| static_cast<SpaceToBatchParams*>(node->user_data); |
| params->output_offset = output->params.zero_point; |
| |
| // Only 4D input and output tensors are supported for this op on TFLM. |
| TF_LITE_ENSURE_EQ(context, NumDimensions(input), kInputDims); |
| TF_LITE_ENSURE_EQ(context, NumDimensions(output), kOutputDims); |
| TF_LITE_ENSURE_EQ(context, input->type, output->type); |
| |
| // Input and output must have the same flat size since TFLM does not support |
| // tensor resizing. |
| TF_LITE_ENSURE_EQ(context, GetTensorShape(input).FlatSize(), |
| GetTensorShape(output).FlatSize()); |
| return kTfLiteOk; |
| } |
| |
| TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
| TFLITE_DCHECK(node->user_data != nullptr); |
| const SpaceToBatchParams& params = |
| *(static_cast<const SpaceToBatchParams*>(node->user_data)); |
| |
| const TfLiteEvalTensor* input = |
| tflite::micro::GetEvalInput(context, node, kInputTensor); |
| const TfLiteEvalTensor* block_shape = |
| tflite::micro::GetEvalInput(context, node, kBlockShapeTensor); |
| const TfLiteEvalTensor* crops = |
| tflite::micro::GetEvalInput(context, node, kCropsTensor); |
| TfLiteEvalTensor* output = |
| tflite::micro::GetEvalOutput(context, node, kOutputTensor); |
| |
| switch (input->type) { // Already know in/out types are same. |
| case kTfLiteFloat32: |
| reference_ops::SpaceToBatchND( |
| params, tflite::micro::GetTensorShape(input), |
| tflite::micro::GetTensorData<float>(input), |
| tflite::micro::GetTensorShape(block_shape), |
| tflite::micro::GetTensorData<int32_t>(block_shape), |
| tflite::micro::GetTensorShape(crops), |
| tflite::micro::GetTensorData<int32_t>(crops), |
| tflite::micro::GetTensorShape(output), |
| tflite::micro::GetTensorData<float>(output)); |
| break; |
| case kTfLiteInt8: |
| reference_ops::SpaceToBatchND( |
| params, tflite::micro::GetTensorShape(input), |
| tflite::micro::GetTensorData<int8_t>(input), |
| tflite::micro::GetTensorShape(block_shape), |
| tflite::micro::GetTensorData<int32_t>(block_shape), |
| tflite::micro::GetTensorShape(crops), |
| tflite::micro::GetTensorData<int32_t>(crops), |
| tflite::micro::GetTensorShape(output), |
| tflite::micro::GetTensorData<int8_t>(output)); |
| break; |
| default: |
| TF_LITE_KERNEL_LOG(context, "Type %s (%d) not supported.", |
| TfLiteTypeGetName(input->type), input->type); |
| return kTfLiteError; |
| } |
| return kTfLiteOk; |
| } |
| |
| TfLiteRegistration Register_SPACE_TO_BATCH_ND() { |
| return {/*init=*/Init, |
| /*free=*/nullptr, |
| /*prepare=*/Prepare, |
| /*invoke=*/Eval, |
| /*profiling_string=*/nullptr, |
| /*builtin_code=*/0, |
| /*custom_name=*/nullptr, |
| /*version=*/0}; |
| } |
| |
| } // namespace tflite |