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tensorflow/tensorflow/lite/kernels/gather_nd.cc
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| /* Copyright 2019 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 <stdint.h> | |
| #include "tensorflow/lite/c/common.h" | |
| #include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h" | |
| #include "tensorflow/lite/kernels/internal/reference/reference_ops.h" | |
| #include "tensorflow/lite/kernels/internal/tensor.h" | |
| #include "tensorflow/lite/kernels/internal/tensor_ctypes.h" | |
| #include "tensorflow/lite/kernels/kernel_util.h" | |
| namespace tflite { | |
| namespace ops { | |
| namespace builtin { | |
| namespace gather_nd { | |
| constexpr int kParams = 0; | |
| constexpr int kIndices = 1; | |
| constexpr int kOutputTensor = 0; | |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { | |
| TF_LITE_ENSURE_EQ(context, NumInputs(node), 2); | |
| TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); | |
| const TfLiteTensor* params; | |
| TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kParams, ¶ms)); | |
| const TfLiteTensor* indices; | |
| TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kIndices, &indices)); | |
| TfLiteTensor* output; | |
| TF_LITE_ENSURE_OK(context, | |
| GetOutputSafe(context, node, kOutputTensor, &output)); | |
| switch (params->type) { | |
| case kTfLiteFloat32: | |
| case kTfLiteUInt8: | |
| case kTfLiteInt8: | |
| case kTfLiteInt16: | |
| case kTfLiteInt64: | |
| case kTfLiteInt32: | |
| case kTfLiteString: | |
| break; | |
| default: | |
| TF_LITE_KERNEL_LOG(context, | |
| "Params of type '%s' are not supported by gather_nd.", | |
| TfLiteTypeGetName(params->type)); | |
| return kTfLiteError; | |
| } | |
| switch (indices->type) { | |
| case kTfLiteInt64: | |
| case kTfLiteInt32: | |
| break; | |
| default: | |
| TF_LITE_KERNEL_LOG(context, | |
| "Indices of type '%s' are not supported by gather_nd.", | |
| TfLiteTypeGetName(indices->type)); | |
| return kTfLiteError; | |
| } | |
| const int params_rank = NumDimensions(params); | |
| const int indices_rank = NumDimensions(indices); | |
| const int indices_nd = SizeOfDimension(indices, indices_rank - 1); | |
| if (params_rank < 1) { | |
| TF_LITE_KERNEL_LOG(context, "Params must be at least a vector."); | |
| return kTfLiteError; | |
| } | |
| if (indices_rank < 1) { | |
| TF_LITE_KERNEL_LOG(context, "Indices must be at least a vector."); | |
| return kTfLiteError; | |
| } | |
| if (indices_nd > params_rank) { | |
| TF_LITE_KERNEL_LOG( | |
| context, "Index innermost dimension length must be <= params rank."); | |
| return kTfLiteError; | |
| } | |
| // Assign to output the input type. | |
| output->type = params->type; | |
| // The result shape is | |
| // indices.shape[:-1] + params.shape[indices.shape[-1]:] | |
| const int output_rank = indices_rank + params_rank - indices_nd - 1; | |
| TfLiteIntArray* output_shape = TfLiteIntArrayCreate(output_rank); | |
| int output_index = 0; | |
| for (int i = 0; i < indices_rank - 1; ++i) { | |
| output_shape->data[output_index++] = indices->dims->data[i]; | |
| } | |
| for (int i = indices_nd; i < params_rank; ++i) { | |
| output_shape->data[output_index++] = params->dims->data[i]; | |
| } | |
| return context->ResizeTensor(context, output, output_shape); | |
| } | |
| template <typename ParamsT, typename IndicesT> | |
| TfLiteStatus GatherNd(const TfLiteTensor* params, const TfLiteTensor* indices, | |
| TfLiteTensor* output) { | |
| reference_ops::GatherNd( | |
| GetTensorShape(params), GetTensorData<ParamsT>(params), | |
| GetTensorShape(indices), GetTensorData<IndicesT>(indices), | |
| GetTensorShape(output), GetTensorData<ParamsT>(output)); | |
| return kTfLiteOk; | |
| } | |
| template <typename IndicesT> | |
| TfLiteStatus GatherNdString(const TfLiteTensor* params, | |
| const TfLiteTensor* indices, TfLiteTensor* output) { | |
| reference_ops::GatherNdString( | |
| GetTensorShape(params), params, GetTensorShape(indices), | |
| GetTensorData<IndicesT>(indices), GetTensorShape(output), output); | |
| return kTfLiteOk; | |
| } | |
| template <typename IndicesT> | |
| TfLiteStatus EvalGatherNd(TfLiteContext* context, const TfLiteTensor* params, | |
| const TfLiteTensor* indices, TfLiteTensor* output) { | |
| bool indices_has_only_positive_elements = true; | |
| const auto* indices_values = GetTensorData<IndicesT>(indices); | |
| const size_t num_indices = indices->bytes / sizeof(IndicesT); | |
| for (size_t i = 0; i < num_indices; i++) { | |
| if (indices_values[i] < 0) { | |
| indices_has_only_positive_elements = false; | |
| break; | |
| } | |
| } | |
| TF_LITE_ENSURE(context, indices_has_only_positive_elements); | |
| switch (params->type) { | |
| case kTfLiteFloat32: | |
| return GatherNd<float, IndicesT>(params, indices, output); | |
| case kTfLiteUInt8: | |
| return GatherNd<uint8_t, IndicesT>(params, indices, output); | |
| case kTfLiteInt8: | |
| return GatherNd<int8_t, IndicesT>(params, indices, output); | |
| case kTfLiteInt16: | |
| return GatherNd<int16_t, IndicesT>(params, indices, output); | |
| case kTfLiteInt32: | |
| return GatherNd<int32_t, IndicesT>(params, indices, output); | |
| case kTfLiteInt64: | |
| return GatherNd<int64_t, IndicesT>(params, indices, output); | |
| case kTfLiteString: | |
| return GatherNdString<IndicesT>(params, indices, output); | |
| default: | |
| TF_LITE_KERNEL_LOG(context, | |
| "Params type '%s' are not supported by gather_nd.", | |
| TfLiteTypeGetName(params->type)); | |
| return kTfLiteError; | |
| } | |
| } | |
| TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { | |
| const TfLiteTensor* params; | |
| TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kParams, ¶ms)); | |
| const TfLiteTensor* indices; | |
| TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kIndices, &indices)); | |
| TfLiteTensor* output; | |
| TF_LITE_ENSURE_OK(context, | |
| GetOutputSafe(context, node, kOutputTensor, &output)); | |
| // Prevent division by 0 in the helper. | |
| // In TF, GatherND supports empty `params` only when `indices` is also empty. | |
| TF_LITE_ENSURE(context, | |
| (NumElements(params) == 0 && NumElements(indices) == 0) || | |
| NumElements(params) > 0); | |
| switch (indices->type) { | |
| case kTfLiteInt32: | |
| return EvalGatherNd<int32_t>(context, params, indices, output); | |
| case kTfLiteInt64: | |
| return EvalGatherNd<int64_t>(context, params, indices, output); | |
| default: | |
| TF_LITE_KERNEL_LOG(context, | |
| "Indices of type '%s' are not supported by gather_nd.", | |
| TfLiteTypeGetName(indices->type)); | |
| return kTfLiteError; | |
| } | |
| } | |
| } // namespace gather_nd | |
| TfLiteRegistration* Register_GATHER_ND() { | |
| static TfLiteRegistration r = {/*init*/ nullptr, /*free*/ nullptr, | |
| gather_nd::Prepare, gather_nd::Eval}; | |
| return &r; | |
| } | |
| } // namespace builtin | |
| } // namespace ops | |
| } // namespace tflite |