wehub-resource-sync
113 lines
3.3 KiB
C++
113 lines
3.3 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/lite/experimental/resource/resource_variable.h"
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#include <cstdlib>
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#include <cstring>
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#include <memory>
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/core/c/c_api_types.h"
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#include "tensorflow/lite/experimental/resource/resource_base.h"
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namespace tflite {
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namespace resource {
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ResourceVariable::ResourceVariable() {
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memset(&tensor_, 0, sizeof(TfLiteTensor));
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}
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ResourceVariable::ResourceVariable(ResourceVariable&& other) {
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tensor_ = other.tensor_;
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is_initialized_ = other.is_initialized_;
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memset(&other.tensor_, 0, sizeof(TfLiteTensor));
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other.is_initialized_ = false;
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}
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ResourceVariable::~ResourceVariable() {
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if (is_initialized_) {
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free(tensor_.data.raw);
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if (tensor_.dims) {
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TfLiteIntArrayFree(tensor_.dims);
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}
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}
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}
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TfLiteStatus ResourceVariable::AssignFrom(const TfLiteTensor* tensor) {
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// Save the old allocated resources and attributes that we might use.
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char* old_raw = tensor_.data.raw;
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size_t old_bytes = tensor_.bytes;
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TfLiteIntArray* old_dims = tensor_.dims;
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// Copy primitive parameters.
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memset(&tensor_, 0, sizeof(tensor_));
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tensor_.name = "ResourceVariable";
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tensor_.allocation_type = kTfLiteDynamic;
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tensor_.type = tensor->type;
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tensor_.params = tensor->params;
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tensor_.quantization = tensor->quantization;
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// Copy old shape if possible otherwise create a new one.
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if (TfLiteIntArrayEqual(old_dims, tensor->dims)) {
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tensor_.dims = old_dims;
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} else {
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TfLiteIntArrayFree(old_dims);
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tensor_.dims = TfLiteIntArrayCopy(tensor->dims);
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}
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// Reuse the same buffer if possible otherwise allocate a new one.
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tensor_.data.raw = old_raw;
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if (old_bytes != tensor->bytes) {
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TfLiteTensorRealloc(tensor->bytes, &tensor_);
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} else {
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tensor_.bytes = old_bytes;
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}
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if (tensor->data.raw) {
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memcpy(tensor_.data.raw, tensor->data.raw, tensor_.bytes);
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}
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is_initialized_ = true;
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return kTfLiteOk;
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}
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void CreateResourceVariableIfNotAvailable(ResourceMap* resources,
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int resource_id) {
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if (resources->count(resource_id) != 0) {
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return;
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}
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resources->emplace(resource_id, std::make_unique<ResourceVariable>());
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}
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ResourceVariable* GetResourceVariable(ResourceMap* resources, int resource_id) {
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auto it = resources->find(resource_id);
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if (it != resources->end() &&
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it->second->GetResourceType() ==
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ResourceBase::ResourceType::kResourceVariable) {
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return static_cast<ResourceVariable*>(it->second.get());
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}
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return nullptr;
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}
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bool IsBuiltinResource(const TfLiteTensor* tensor) {
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return tensor && tensor->type == kTfLiteResource &&
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tensor->delegate == nullptr;
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}
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} // namespace resource
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} // namespace tflite
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