168 lines
6.7 KiB
C++
168 lines
6.7 KiB
C++
/*
|
|
* Copyright (c) 2019 Arm Limited.
|
|
*
|
|
* SPDX-License-Identifier: MIT
|
|
*
|
|
* Permission is hereby granted, free of charge, to any person obtaining a copy
|
|
* of this software and associated documentation files (the "Software"), to
|
|
* deal in the Software without restriction, including without limitation the
|
|
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
|
|
* sell copies of the Software, and to permit persons to whom the Software is
|
|
* furnished to do so, subject to the following conditions:
|
|
*
|
|
* The above copyright notice and this permission notice shall be included in all
|
|
* copies or substantial portions of the Software.
|
|
*
|
|
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
|
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
|
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
|
* SOFTWARE.
|
|
*/
|
|
#include "ConcatenateLayer.h"
|
|
|
|
#include "tests/validation/Helpers.h"
|
|
#include "tests/validation/reference/Permute.h"
|
|
|
|
namespace arm_compute
|
|
{
|
|
namespace test
|
|
{
|
|
namespace validation
|
|
{
|
|
namespace reference
|
|
{
|
|
namespace
|
|
{
|
|
template <typename T>
|
|
SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst)
|
|
{
|
|
// Create reference
|
|
std::vector<TensorShape> shapes;
|
|
shapes.reserve(srcs.size());
|
|
for(const auto &src : srcs)
|
|
{
|
|
shapes.emplace_back(src.shape());
|
|
}
|
|
// Compute reference
|
|
int width_offset = 0;
|
|
const int width_out = dst.shape().x();
|
|
// Set output tensor to 0
|
|
std::fill_n(dst.data(), dst.num_elements(), 0);
|
|
for(const auto &src : srcs)
|
|
{
|
|
ARM_COMPUTE_ERROR_ON(width_offset >= width_out);
|
|
|
|
const int width = src.shape().x();
|
|
const int height = src.shape().y();
|
|
const int depth = src.shape().z();
|
|
const int upper_dims = src.shape().total_size() / (width * height * depth);
|
|
|
|
const T *src_ptr = src.data();
|
|
T *dst_ptr = dst.data();
|
|
|
|
for(int u = 0; u < upper_dims; ++u)
|
|
{
|
|
for(int d = 0; d < depth; ++d)
|
|
{
|
|
for(int r = 0; r < height; ++r)
|
|
{
|
|
const int offset = u * height * depth + d * height + r;
|
|
if(is_data_type_quantized(src.data_type()) && src.quantization_info() != dst.quantization_info())
|
|
{
|
|
const UniformQuantizationInfo iq_info = src.quantization_info().uniform();
|
|
const UniformQuantizationInfo oq_info = dst.quantization_info().uniform();
|
|
|
|
if(src.data_type() == DataType::QASYMM8)
|
|
{
|
|
std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t)
|
|
{
|
|
const float dequantized_input = dequantize_qasymm8(t, iq_info);
|
|
return quantize_qasymm8(dequantized_input, oq_info);
|
|
});
|
|
}
|
|
else
|
|
{
|
|
std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [&](T t)
|
|
{
|
|
const float dequantized_input = dequantize_qasymm8_signed(t, iq_info);
|
|
return quantize_qasymm8_signed(dequantized_input, oq_info);
|
|
});
|
|
}
|
|
src_ptr += width;
|
|
}
|
|
else
|
|
{
|
|
std::copy(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out);
|
|
src_ptr += width;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
width_offset += width;
|
|
}
|
|
return dst;
|
|
}
|
|
|
|
template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst);
|
|
template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst);
|
|
template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst);
|
|
template SimpleTensor<int8_t> widthconcatenate_layer(const std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst);
|
|
} // namespace
|
|
|
|
template <typename T>
|
|
SimpleTensor<T> concatenate_layer(std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst, unsigned int axis)
|
|
{
|
|
switch(axis)
|
|
{
|
|
case Window::DimX:
|
|
{
|
|
return widthconcatenate_layer(srcs, dst);
|
|
}
|
|
case Window::DimY:
|
|
{
|
|
for(auto &t : srcs)
|
|
{
|
|
t = reference::permute<T>(t, PermutationVector(1U, 0U));
|
|
}
|
|
dst = reference::permute<T>(dst, PermutationVector(1U, 0U));
|
|
return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(1U, 0U));
|
|
}
|
|
case Window::DimZ:
|
|
{
|
|
for(auto &t : srcs)
|
|
{
|
|
t = reference::permute<T>(t, PermutationVector(2U, 1U, 0U));
|
|
}
|
|
dst = reference::permute<T>(dst, PermutationVector(2U, 1U, 0U));
|
|
return reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(2U, 1U, 0U));
|
|
}
|
|
case 3:
|
|
{
|
|
for(auto &t : srcs)
|
|
{
|
|
t = reference::permute<T>(t, PermutationVector(3U, 2U, 1U, 0U));
|
|
}
|
|
dst = reference::permute<T>(dst, PermutationVector(3U, 2U, 1U, 0U));
|
|
auto ret = reference::permute<T>(widthconcatenate_layer(srcs, dst), PermutationVector(3U, 2U, 1U, 0U));
|
|
return ret;
|
|
}
|
|
default:
|
|
{
|
|
ARM_COMPUTE_ERROR("Not supported");
|
|
return dst;
|
|
}
|
|
}
|
|
}
|
|
|
|
template SimpleTensor<float> concatenate_layer(std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst, unsigned int axis);
|
|
template SimpleTensor<half> concatenate_layer(std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst, unsigned int axis);
|
|
template SimpleTensor<uint8_t> concatenate_layer(std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst, unsigned int axis);
|
|
template SimpleTensor<int8_t> concatenate_layer(std::vector<SimpleTensor<int8_t>> &srcs, SimpleTensor<int8_t> &dst, unsigned int axis);
|
|
} // namespace reference
|
|
} // namespace validation
|
|
} // namespace test
|
|
} // namespace arm_compute
|