4#include "nforge/core/tensor.h"
5#include "nforge/core/tensor_layout.h"
18 virtual ~Impl() =
default;
30 virtual void print(
const std::vector<size_t>& position)
const = 0;
39 virtual std::vector<float>
toVector()
const = 0;
45 virtual std::unique_ptr<Tensor::Impl>
clone()
const = 0;
134 size_t m,
size_t k,
size_t p)
const = 0;
166 float tolerance)
const = 0;
Definition tensor_impl.h:15
virtual std::unique_ptr< Tensor::Impl > clone() const =0
Deep copies this implementation.
virtual std::string toString() const =0
Returns a string representation of the data.
virtual std::unique_ptr< Tensor::Impl > sum(const TensorLayout &layout, const TensorLayout &blockLayout, const TensorLayout &outLayout) const =0
Reduces dimensions [dim, rank) by summation. Output with outLayout.
virtual std::unique_ptr< Tensor::Impl > min(const TensorLayout &layout, const TensorLayout &blockLayout, const TensorLayout &outLayout) const =0
Reduces dimensions [dim, rank) by taking the minimum. Output with outLayout.
virtual std::unique_ptr< Tensor::Impl > sub(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise subtraction. Returns a new Impl with the result with outLayout.
virtual std::unique_ptr< Tensor::Impl > less(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise less than. Returns a tensor of 0.0 / 1.0 with outLayout.
virtual void imul(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout)=0
In-place elementwise multiplication. Modifies lhsLayout in place.
virtual void fillAll(float value)=0
Fills all elements with value.
virtual size_t getNumElements() const =0
Returns the total number of elements.
virtual std::unique_ptr< Tensor::Impl > lessEqual(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise less or equal. Returns a tensor of 0.0 / 1.0 with outLayout.
virtual std::unique_ptr< Tensor::Impl > prod(const TensorLayout &layout, const TensorLayout &blockLayout, const TensorLayout &outLayout) const =0
Reduces dimensions [dim, rank) by taking the product. Output with outLayout.
virtual std::unique_ptr< Tensor::Impl > greater(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise greater than. Returns a tensor of 0.0 / 1.0 with outLayout.
virtual std::vector< float > toVector() const =0
Copies all elements into a flat vector (row-major order).
virtual std::unique_ptr< Tensor::Impl > norm(const TensorLayout &layout) const =0
L2 norm of the tensor described by layout.
virtual void idiv(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout)=0
In-place elementwise division. Modifies lhsLayout in place.
virtual bool compare(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout) const =0
Returns true if the data with lhsLayout matches rhsImpl with rhsLayout.
virtual void iadd(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout)=0
In-place elementwise addition. Modifies lhsLayout in place.
virtual std::unique_ptr< Tensor::Impl > div(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise division. Returns a new Impl with the result with outLayout.
virtual void copyFromHost(const float *data, size_t count)=0
virtual std::unique_ptr< Tensor::Impl > mul(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise multiplication. Returns a new Impl with the result with outLayout.
virtual std::unique_ptr< Tensor::Impl > greaterEqual(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise greater or equal. Returns a tensor of 0.0 / 1.0 with outLayout.
virtual void print() const =0
Prints the entire tensor to stdout.
virtual std::unique_ptr< Tensor::Impl > add(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout) const =0
Elementwise addition. Returns a new Impl with the result with outLayout.
virtual void isub(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout)=0
In-place elementwise subtraction. Modifies lhsLayout in place.
virtual std::unique_ptr< Tensor::Impl > isClose(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout, float tolerance) const =0
Elementwise closeness within tolerance. Returns a tensor of 0.0 / 1.0 with outLayout.
virtual void set(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout)=0
Copies data from rhsImpl with rhsLayout into this with lhsLayout.
virtual std::unique_ptr< Tensor::Impl > max(const TensorLayout &layout, const TensorLayout &blockLayout, const TensorLayout &outLayout) const =0
Reduces dimensions [dim, rank) by taking the maximum. Output with outLayout.
virtual Tensor::Shape getShape() const =0
Returns the tensor shape.
virtual std::unique_ptr< Tensor::Impl > matmul(const TensorLayout &lhsLayout, const Tensor::Impl *rhsImpl, const TensorLayout &rhsLayout, const TensorLayout &outLayout, size_t batch, size_t m, size_t k, size_t p) const =0
virtual void print(const std::vector< size_t > &position) const =0
Prints the block starting at position to stdout.
virtual void fillRand()=0
Fills all elements with random values in [-1, 1].
Definition tensor_shape.h:15
Definition tensor_layout.h:15