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TheRock/rocm-libraries/projects/hipblaslt/tensilelite/client/include/TensorDataManipulation.hpp
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/*******************************************************************************
*
* MIT License
*
* Copyright (C) 2024 Advanced Micro Devices, Inc.
*
* 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.
*
*******************************************************************************/
#pragma once
#include <cassert>
#include <functional>
#include <iosfwd>
#include <memory>
#include <vector>
namespace Tensor
{
namespace Manipulation
{
using Shape = std::vector<size_t>;
using Strides = std::vector<size_t>;
using Indices = std::vector<size_t>;
using Permutation = std::vector<size_t>;
//shape: [M, N, K]
//strides: [N * K, K, 1]
class TensorDesc
{
public:
explicit TensorDesc(std::initializer_list<size_t> shape)
: shape(shape)
{
strides.assign(shape.size(), 1);
for(ssize_t i = strides.size() - 2; i >= 0; --i)
{
strides[i] = strides[i + 1] * this->shape[i + 1];
}
}
explicit TensorDesc(const Shape& shape)
: shape(shape)
{
strides.assign(shape.size(), 1);
for(int i = strides.size() - 2; i >= 0; --i)
{
strides[i] = strides[i + 1] * this->shape[i + 1];
}
}
TensorDesc(std::initializer_list<size_t> shape, std::initializer_list<size_t> strides)
: shape(shape)
, strides(strides)
{
}
TensorDesc(const Shape& shape, const Strides& strides)
: shape(shape)
, strides(strides)
{
}
size_t stride(size_t i) const
{
return strides.at(i);
}
size_t numDims() const
{
return shape.size();
}
size_t dim(size_t i) const
{
return shape.at(i);
}
const Shape& getShape() const
{
return shape;
}
void setShape(const Shape& shape)
{
this->shape = shape;
strides.assign(shape.size(), 1);
for(int i = strides.size() - 2; i >= 0; --i)
{
strides[i] = strides[i + 1] * this->shape[i + 1];
}
}
friend std::ostream& operator<<(std::ostream& os, const TensorDesc& desc)
{
os << "Shape: [";
for(auto i : desc.shape)
{
os << i << ", ";
}
os << "]\n";
os << "Strides: [";
for(auto i : desc.strides)
{
os << i << ", ";
}
os << "]\n";
return os;
}
std::size_t flattenSize() const
{
size_t s{1};
for(auto i : shape)
{
s *= i;
}
return s;
}
bool isShapeCompatible(const Shape& shape) const
{
TensorDesc newDesc(shape);
return flattenSize() == newDesc.flattenSize();
}
bool canShapePadTo(const Shape& shape) const
{
if(this->shape.size() != shape.size())
{
return false;
}
for(size_t i = 0; i < this->shape.size(); ++i)
{
if(this->shape.at(i) > shape.at(i))
{
return false;
}
}
return true;
}
private:
Shape shape;
Strides strides;
};
class Tensor
{
public:
template <typename T>
static Tensor create(const Shape shape)
{
return Tensor(shape, sizeof(T));
}
Tensor(const Shape shape, float elementSize)
: desc(shape)
, elementSize(elementSize)
, data(new char[TensileLite::multiplyElementSize(desc.flattenSize(), elementSize)])
{
}
template <typename T>
const T* as() const
{
return reinterpret_cast<const T*>(data.get());
}
template <typename T>
T* as()
{
return reinterpret_cast<T*>(data.get());
}
template <typename T>
const T& getValue(const Indices& indices) const
{
size_t offset{};
for(size_t i = 0; i < indices.size(); ++i)
{
const auto idx = indices[i];
offset += desc.stride(i) * idx;
}
return as<T>()[offset];
}
template <typename T>
const T& setValue(const Indices& indices, const T& value)
{
size_t offset{};
for(size_t i = 0; i < indices.size(); ++i)
{
const auto idx = indices[i];
offset += desc.stride(i) * idx;
}
as<T>()[offset] = value;
return value;
}
friend std::ostream& operator<<(std::ostream& os, const Tensor& t)
{
os << t.desc;
return os;
}
const TensorDesc& getDesc() const
{
return desc;
}
float getElementSize() const
{
return elementSize;
}
size_t getNumBytes() const
{
return TensileLite::multiplyElementSize(getDesc().flattenSize(), getElementSize());
}
void reshape(const Shape& shape)
{
if(desc.isShapeCompatible(shape))
{
desc.setShape(shape);
return;
}
assert(false && "Incompatible shape");
}
private:
float elementSize{};
TensorDesc desc;
std::unique_ptr<char[]> data;
};
Indices permute(const Indices& indices, const Permutation& perm)
{
assert(indices.size() == perm.size());
Indices newIndices = indices;
for(size_t i = 0; i < perm.size(); ++i)
{
newIndices[i] = indices.at(perm.at(i));
}
return newIndices;
}
using IterateCallback = std::function<void(const Indices& indices)>;
using IterateDimCallback = std::function<void(size_t dim)>;
void iterate(
const Shape& shape,
size_t dim,
Indices& indices,
IterateCallback callback,
IterateDimCallback dimEnterCallback = [](size_t) {},
IterateDimCallback dimLeaveCallback = [](size_t) {})
{
if(dim == shape.size())
{
callback(indices);
return;
}
dimEnterCallback(dim);
for(size_t i = 0; i < shape.at(dim); ++i)
{
indices[dim] = i;
iterate(shape, dim + 1, indices, callback, dimEnterCallback, dimLeaveCallback);
}
dimLeaveCallback(dim);
}
template <typename T>
void permute(Tensor& dst, const Tensor& src, const Permutation& perm)
{
Indices indices(src.getDesc().numDims(), 0);
iterate(
src.getDesc().getShape(), 0, indices, [&dst, &src, &perm](const Indices& indices) {
Indices dstIndices = permute(indices, perm);
auto&& value = src.getValue<T>(indices);
dst.setValue<T>(dstIndices, value);
});
}
template <typename T>
Tensor permute(const Tensor& tensor, const Permutation& perm)
{
assert(tensor.getDesc().numDims() == perm.size());
assert(sizeof(T) == size_t(tensor.getElementSize()));
Shape newShape = permute(tensor.getDesc().getShape(), perm);
Tensor permuted(newShape, size_t(tensor.getElementSize()));
permute<T>(permuted, tensor, perm);
return permuted;
}
template <typename T>
Tensor pad(const Tensor& src, const Shape& newShape, T padVal)
{
assert(src.getDesc().canShapePadTo(newShape) && "Invalid shape for padding");
Tensor dst(newShape, sizeof(T));
Indices indices(src.getDesc().numDims(), 0);
iterate(dst.getDesc().getShape(), 0, indices, [&dst, &padVal](const Indices& indices) {
dst.setValue<T>(indices, padVal);
});
iterate(src.getDesc().getShape(), 0, indices, [&dst, &src](const Indices& indices) {
auto&& value = src.getValue<T>(indices);
dst.setValue<T>(indices, value);
});
return dst;
}
Tensor pad(const Tensor& tensor,
const Shape& newShape,
const void* padValPtr,
size_t padValSize)
{
switch(padValSize)
{
case 1:
return pad<uint8_t>(tensor, newShape, *static_cast<const uint8_t*>(padValPtr));
case 2:
return pad<uint16_t>(tensor, newShape, *static_cast<const uint16_t*>(padValPtr));
case 4:
return pad<uint32_t>(tensor, newShape, *static_cast<const uint32_t*>(padValPtr));
case 8:
return pad<uint64_t>(tensor, newShape, *static_cast<const uint64_t*>(padValPtr));
default:
assert(false && "Unsupported element size");
}
return Tensor({0}, tensor.getElementSize());
}
Tensor permute(const Tensor& tensor, const Permutation& perm)
{
Shape newShape = permute(tensor.getDesc().getShape(), perm);
Tensor permuted(newShape, size_t(tensor.getElementSize()));
switch(size_t(tensor.getElementSize()))
{
case 1:
permute<uint8_t>(permuted, tensor, perm);
break;
case 2:
permute<uint16_t>(permuted, tensor, perm);
break;
case 4:
permute<uint32_t>(permuted, tensor, perm);
break;
case 8:
permute<uint64_t>(permuted, tensor, perm);
break;
default:
assert(false && "Unsupported element size");
}
return permuted;
}
template <typename T>
void printTensorData(std::ostream& os, const Tensor& tensor)
{
const auto* data = tensor.as<T>();
const auto numElements = tensor.getDesc().flattenSize();
os << "[";
for(size_t i = 0; i < numElements; ++i)
{
os << float(data[i]) << ", ";
}
os << "]\n";
}
template <typename T>
void printTensorDataMultiDims(std::ostream& os, const Tensor& tensor)
{
os << "[";
Indices indices(tensor.getDesc().numDims(), 0);
iterate(
tensor.getDesc().getShape(),
0,
indices,
[&os, &tensor](const Indices& idx) {
os << float(tensor.getValue<T>(idx)) << ", ";
},
[&os](size_t dim) { os << "["; },
[&os, &tensor](size_t dim) {
os << "], ";
if(dim + 1 == tensor.getDesc().numDims())
{
os << '\n';
}
});
os << "]\n";
}
}
}