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/*
* Copyright (c) 2018 Samsung Electronics Co., Ltd. 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 "nnkit/support/tflite/TensorContext.h"
#include "nnkit/support/tflite/TensorUtils.h"
#include <nncc/core/ADT/tensor/LexicalLayout.h>
#include <nncc/core/ADT/tensor/Overlay.h>
namespace nnkit
{
namespace support
{
namespace tflite
{
nncc::core::ADT::tensor::Shape TensorContext::shape(uint32_t n) const
{
return tensor_shape(_tensors.at(n));
}
void TensorContext::getMutableFloatTensor(uint32_t n,
const nnkit::TensorContext::TypedAccessor<float> &f)
{
using nncc::core::ADT::tensor::LexicalLayout;
using nncc::core::ADT::tensor::make_overlay;
auto t = _tensors.at(n);
float *data = reinterpret_cast<float *>(t->data.f);
auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
f(*this, n, overlay);
}
void TensorContext::getConstFloatTensor(uint32_t n,
const nnkit::TensorContext::TypedReader<float> &f) const
{
using nncc::core::ADT::tensor::LexicalLayout;
using nncc::core::ADT::tensor::make_overlay;
auto t = _tensors.at(n);
float *data = reinterpret_cast<float *>(t->data.f);
auto overlay = make_overlay<float, LexicalLayout>(shape(n), data);
f(*this, n, overlay);
}
} // namespace tflite
} // namespace support
} // namespace nnkit
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