| /* 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 <string.h> |
| |
| #include <memory> |
| |
| #include "tensorflow/lite/c/builtin_op_data.h" |
| #include "tensorflow/lite/c/c_api_internal.h" |
| #include "tensorflow/lite/core/subgraph.h" |
| #include "tensorflow/lite/kernels/internal/tensor.h" |
| #include "tensorflow/lite/kernels/kernel_util.h" |
| #include "tensorflow/lite/kernels/op_macros.h" |
| |
| namespace tflite { |
| namespace ops { |
| namespace custom { |
| namespace read_variable { |
| |
| constexpr int kInputVariableId = 0; |
| constexpr int kOutputValue = 0; |
| |
| TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| TF_LITE_ENSURE_EQ(context, node->inputs->size, 1); |
| TF_LITE_ENSURE_EQ(context, node->outputs->size, 1); |
| |
| const TfLiteTensor* input_variable_id_tensor = |
| GetInput(context, node, kInputVariableId); |
| TF_LITE_ENSURE_EQ(context, input_variable_id_tensor->type, kTfLiteInt32); |
| TF_LITE_ENSURE_EQ(context, NumElements(input_variable_id_tensor), 1); |
| |
| TfLiteTensor* output = GetOutput(context, node, kOutputValue); |
| SetTensorToDynamic(output); |
| |
| return kTfLiteOk; |
| } |
| |
| TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
| Subgraph* subgraph = reinterpret_cast<Subgraph*>(context->impl_); |
| |
| const TfLiteTensor* input_variable_id_tensor = |
| GetInput(context, node, kInputVariableId); |
| int variable_id = input_variable_id_tensor->data.i32[0]; |
| auto& resource_variables = subgraph->resource_variables(); |
| |
| const auto& variable_iterator = resource_variables.find(variable_id); |
| if (variable_iterator == resource_variables.end()) { |
| context->ReportError(context, "Variable ID %d is read before initialized.", |
| variable_id); |
| return kTfLiteError; |
| } |
| auto& variable = variable_iterator->second; |
| |
| TfLiteTensor* variable_tensor = variable.GetTensor(); |
| TfLiteTensor* output = GetOutput(context, node, kOutputValue); |
| |
| TF_LITE_ENSURE_EQ(context, variable_tensor->type, output->type); |
| TF_LITE_ENSURE_OK( |
| context, context->ResizeTensor( |
| context, output, TfLiteIntArrayCopy(variable_tensor->dims))); |
| memcpy(output->data.raw, variable_tensor->data.raw, output->bytes); |
| |
| return kTfLiteOk; |
| } |
| |
| } // namespace read_variable |
| |
| TfLiteRegistration* Register_READ_VARIABLE() { |
| static TfLiteRegistration r = {nullptr, nullptr, read_variable::Prepare, |
| read_variable::Eval}; |
| return &r; |
| } |
| |
| } // namespace custom |
| } // namespace ops |
| } // namespace tflite |