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Deduplicate StridedSlice Init and Prepare (tensorflow#2203)
The Init and Prepare functions were entirely common between the reference kernel and the Xtensa optimized kernel. This PR relocates the common functions to a strided_slice_common.cc file to be used on both platforms. This reduces the reference kernel and xtena kernel files to just the Eval function. BUG=cleanup
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| /* Copyright 2023 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. | ||
| ==============================================================================*/ | ||
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| #ifndef TENSORFLOW_LITE_MICRO_KERNELS_STRIDED_SLICE_H_ | ||
| #define TENSORFLOW_LITE_MICRO_KERNELS_STRIDED_SLICE_H_ | ||
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| #include <cstdint> | ||
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| #include "tensorflow/lite/c/builtin_op_data.h" | ||
| #include "tensorflow/lite/c/common.h" | ||
| #include "tensorflow/lite/micro/micro_common.h" | ||
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| namespace tflite { | ||
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| constexpr int kStridedSliceInputTensor = 0; | ||
| constexpr int kStridedSliceBeginTensor = 1; | ||
| constexpr int kStridedSliceEndTensor = 2; | ||
| constexpr int kStridedSliceStridesTensor = 3; | ||
| constexpr int kStridedSliceOutputTensor = 0; | ||
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| void* StridedSliceInit(TfLiteContext* context, const char* buffer, | ||
| size_t length); | ||
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| TfLiteStatus StridedSlicePrepare(TfLiteContext* context, TfLiteNode* node); | ||
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| } // namespace tflite | ||
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| #endif // TENSORFLOW_LITE_MICRO_KERNELS_STRIDED_SLICE_H_ |
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| /* Copyright 2023 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 <cmath> | ||
| #include <cstring> | ||
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| #include "tensorflow/lite/c/builtin_op_data.h" | ||
| #include "tensorflow/lite/c/common.h" | ||
| #include "tensorflow/lite/kernels/internal/reference/strided_slice.h" | ||
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" | ||
| #include "tensorflow/lite/kernels/kernel_util.h" | ||
| #include "tensorflow/lite/kernels/op_macros.h" | ||
| #include "tensorflow/lite/micro/kernels/kernel_util.h" | ||
| #include "tensorflow/lite/micro/kernels/strided_slice.h" | ||
| #include "tensorflow/lite/micro/micro_log.h" | ||
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| namespace tflite { | ||
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| namespace { | ||
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| struct StridedSliceContext { | ||
| StridedSliceContext(TfLiteContext* context, TfLiteNode* node) { | ||
| params = reinterpret_cast<TfLiteStridedSliceParams*>(node->builtin_data); | ||
| micro_context = GetMicroContext(context); | ||
| input = | ||
| micro_context->AllocateTempInputTensor(node, kStridedSliceInputTensor); | ||
| begin = | ||
| micro_context->AllocateTempInputTensor(node, kStridedSliceBeginTensor); | ||
| end = micro_context->AllocateTempInputTensor(node, kStridedSliceEndTensor); | ||
| strides = micro_context->AllocateTempInputTensor( | ||
| node, kStridedSliceStridesTensor); | ||
| output = micro_context->AllocateTempOutputTensor(node, | ||
| kStridedSliceOutputTensor); | ||
| dims = NumDimensions(input); | ||
| } | ||
| ~StridedSliceContext() { | ||
| micro_context->DeallocateTempTfLiteTensor(input); | ||
| micro_context->DeallocateTempTfLiteTensor(begin); | ||
| micro_context->DeallocateTempTfLiteTensor(end); | ||
| micro_context->DeallocateTempTfLiteTensor(strides); | ||
| micro_context->DeallocateTempTfLiteTensor(output); | ||
| } | ||
| const TfLiteStridedSliceParams* params; | ||
| MicroContext* micro_context; | ||
| TfLiteTensor* input; | ||
| TfLiteTensor* begin; | ||
| TfLiteTensor* end; | ||
| TfLiteTensor* strides; | ||
| TfLiteTensor* output; | ||
| int dims; | ||
| }; | ||
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| // This Op only supports 1-4D cases and since we use the reference 4D | ||
| // implementation, the 1-3D tensors are mapped to 4D. | ||
| const int kMaxDim = 4; | ||
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| tflite::StridedSliceParams BuildStridedSliceParams( | ||
| StridedSliceContext* op_context) { | ||
| tflite::StridedSliceParams op_params{}; | ||
| op_params.start_indices_count = op_context->dims; | ||
| op_params.stop_indices_count = op_context->dims; | ||
| op_params.strides_count = op_context->dims; | ||
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| for (int i = 0; i < op_context->dims; ++i) { | ||
| op_params.start_indices[i] = GetTensorData<int32_t>(op_context->begin)[i]; | ||
| op_params.stop_indices[i] = GetTensorData<int32_t>(op_context->end)[i]; | ||
| op_params.strides[i] = GetTensorData<int32_t>(op_context->strides)[i]; | ||
| } | ||
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| op_params.begin_mask = op_context->params->begin_mask; | ||
| op_params.ellipsis_mask = 0; | ||
| op_params.end_mask = op_context->params->end_mask; | ||
| op_params.new_axis_mask = 0; | ||
| op_params.shrink_axis_mask = op_context->params->shrink_axis_mask; | ||
| return op_params; | ||
| } | ||
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| // Processes the indexing tensors (begin, end and strides) to resize the | ||
| // output tensor. This function is callable from both Prepare() and Eval() as | ||
| // long as the caller ensures the indexing tensors are present. | ||
| TfLiteStatus CheckOutputSize(TfLiteContext* context, | ||
| StridedSliceContext* op_context) { | ||
| using ::tflite::strided_slice::StartForAxis; | ||
| using ::tflite::strided_slice::StopForAxis; | ||
| TfLiteIntArray* output_shape = op_context->output->dims; | ||
| int shape_size = 0; | ||
| auto op_params = BuildStridedSliceParams(op_context); | ||
| auto input_shape = GetTensorShape(op_context->input); | ||
| for (int idx = 0; idx < op_context->dims; ++idx) { | ||
| int32_t stride = GetTensorData<int32_t>(op_context->strides)[idx]; | ||
| TF_LITE_ENSURE_MSG(context, stride != 0, "stride value has to be non-zero"); | ||
| int32_t begin = StartForAxis(op_params, input_shape, idx); | ||
| int32_t end = StopForAxis(op_params, input_shape, idx, begin); | ||
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| // When shrinking an axis, the end position does not matter (and can be | ||
| // incorrect when negative indexing is used, see Issue #19260). Always use | ||
| // begin + 1 to generate a length 1 slice, since begin has | ||
| // already been adjusted for negative indices by StartForAxis. | ||
| const bool shrink_axis = op_context->params->shrink_axis_mask & (1 << idx); | ||
| if (shrink_axis) { | ||
| end = begin + 1; | ||
| } | ||
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| // This is valid for both positive and negative strides | ||
| int32_t dim_shape = std::ceil((end - begin) / static_cast<float>(stride)); | ||
| dim_shape = dim_shape < 0 ? 0 : dim_shape; | ||
| if (!shrink_axis) { | ||
| TF_LITE_ENSURE_EQ(context, output_shape->data[shape_size], dim_shape); | ||
| shape_size++; | ||
| } | ||
| } | ||
| TF_LITE_ENSURE_EQ(context, output_shape->size, shape_size); | ||
| return kTfLiteOk; | ||
| } | ||
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| } // namespace | ||
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| void* StridedSliceInit(TfLiteContext* context, const char* buffer, | ||
| size_t length) { | ||
| TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr); | ||
| return context->AllocatePersistentBuffer(context, sizeof(StridedSliceParams)); | ||
| } | ||
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| TfLiteStatus StridedSlicePrepare(TfLiteContext* context, TfLiteNode* node) { | ||
| TFLITE_DCHECK(node->user_data != nullptr); | ||
| StridedSliceParams* op_params = | ||
| static_cast<StridedSliceParams*>(node->user_data); | ||
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 4); | ||
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); | ||
| StridedSliceContext op_context(context, node); | ||
| TF_LITE_ENSURE_MSG(context, op_context.dims <= kMaxDim, | ||
| "input dim should not exceed 4"); | ||
| auto params = BuildStridedSliceParams(&op_context); | ||
| memcpy(op_params, ¶ms, sizeof(StridedSliceParams)); | ||
| return CheckOutputSize(context, &op_context); | ||
| } | ||
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| } // namespace tflite |
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