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/*******************************************************************************
*
* MIT License
*
* Copyright (C) 2019-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* 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 <algorithm>
#include <cstddef>
#include <numeric>
#include <sstream>
#include <string>
#include <Tensile/Comparison.hpp>
#include <Tensile/Debug.hpp>
#include <Tensile/TensorDescriptor.hpp>
#include <Tensile/Utils.hpp>
namespace Tensile
{
const size_t TensorDescriptor::UseDefaultStride = static_cast<size_t>(-1);
bool TensorDescriptor::operator==(const TensorDescriptor& rhs) const
{
return m_dataType == rhs.m_dataType && m_sizes == rhs.m_sizes && m_strides == rhs.m_strides
&& m_offset == rhs.m_offset;
}
bool TensorDescriptor::operator!=(const TensorDescriptor& rhs) const
{
return !(*this == rhs);
}
void TensorDescriptor::appendDim(size_t size)
{
appendDim(size, m_totalAllocatedElements);
}
void TensorDescriptor::appendDim(size_t size, size_t stride)
{
m_sizes.push_back(size);
m_strides.push_back(stride);
calculate();
}
int64_t TensorDescriptor::dimensionPadding(size_t dim) const
{
TENSILE_ASSERT_EXC(dim < dimensions());
if(dim == 0)
return m_strides[0] - 1;
return m_strides[dim] - (m_strides[dim - 1] * m_sizes[dim - 1]);
}
void TensorDescriptor::collapseDims(size_t begin, size_t end)
{
TENSILE_ASSERT_EXC(end >= begin);
TENSILE_ASSERT_EXC(begin < dimensions());
TENSILE_ASSERT_EXC(end <= dimensions());
if(end <= (begin + 1))
return;
for(size_t i = begin + 1; i < end; i++)
TENSILE_ASSERT_EXC(dimensionPadding(i) == 0);
size_t newDimensionSize = 1;
for(size_t i = begin; i < end; i++)
newDimensionSize *= m_sizes[i];
m_sizes.erase(m_sizes.begin() + (begin + 1), m_sizes.begin() + end);
m_sizes[begin] = newDimensionSize;
m_strides.erase(m_strides.begin() + (begin + 1), m_strides.begin() + end);
calculate();
}
std::string TensorDescriptor::ToString() const
{
std::ostringstream result;
result << dimensions() << "-tensor<" << dataType() << ">"
<< "( sizes(";
streamJoin(result, m_sizes, ", ");
result << "), strides(";
streamJoin(result, m_strides, ", ");
result << "), offset(" << m_offset << "))";
return result.str();
}
std::ostream& operator<<(std::ostream& stream, const TensorDescriptor& t)
{
return stream << t.ToString();
}
} // namespace Tensile
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