95 lines
3.1 KiB
C++
95 lines
3.1 KiB
C++
/*
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* Copyright (c) 2017-2019 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#ifndef ARM_COMPUTE_TEST_GC_HELPER_H
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#define ARM_COMPUTE_TEST_GC_HELPER_H
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#include "tests/Globals.h"
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#include "arm_compute/core/ITensor.h"
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#include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
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#include <iostream>
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namespace arm_compute
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{
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namespace test
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{
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/** Helper to create an empty tensor.
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*
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* @param[in] shape Desired shape.
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* @param[in] data_type Desired data type.
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* @param[in] num_channels (Optional) It indicates the number of channels for each tensor element
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*
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* @return Empty @ref GCTensor with the specified shape and data type.
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*/
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inline GCTensor create_tensor(const TensorShape &shape, DataType data_type, int num_channels = 1)
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{
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GCTensor tensor;
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tensor.allocator()->init(TensorInfo(shape, num_channels, data_type));
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return tensor;
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}
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/** Helper to create an empty tensor.
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*
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* @param[in] name File name from which to get the dimensions.
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* @param[in] data_type Desired data type.
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*
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* @return Empty @ref GCTensor with the specified shape and data type.
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*/
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inline GCTensor create_tensor(const std::string &name, DataType data_type)
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{
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constexpr unsigned int num_channels = 1;
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const RawTensor &raw = library->get(name);
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GCTensor tensor;
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tensor.allocator()->init(TensorInfo(raw.shape(), num_channels, data_type));
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return tensor;
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}
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/** Helper to print tensor.
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*
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* @param[in] tensor Tensor to print.
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* @param[in] name Tensor name.
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* @param[in] info Format information.
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*
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* @return Empty @ref GCTensor with the specified shape and data type.
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*/
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inline void print_tensor(ITensor &tensor, const std::string &name, IOFormatInfo info = IOFormatInfo(IOFormatInfo::PrintRegion::Full))
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{
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std::ostringstream s;
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IGCTensor &t = dynamic_cast<IGCTensor &>(tensor);
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t.map();
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t.print(s, info);
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std::cout << name << ":" << std::endl;
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std::cout << s.str().c_str();
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t.unmap();
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}
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} // namespace test
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} // namespace arm_compute
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#endif /* ARM_COMPUTE_TEST_GC_HELPER_H */
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