Uses of Interface
org.episteme.core.mathematics.linearalgebra.Tensor

Packages that use Tensor

Package	Description
org.episteme.core.mathematics.linearalgebra
org.episteme.core.mathematics.linearalgebra.tensors
org.episteme.core.mathematics.linearalgebra.tensors.backends
org.episteme.core.mathematics.linearalgebra.tensors.providers
org.episteme.core.mathematics.linearalgebra.vectors
org.episteme.core.mathematics.ml.neural
org.episteme.core.mathematics.ml.neural.autograd
org.episteme.core.mathematics.ml.neural.backends
org.episteme.core.mathematics.ml.neural.optimizers
org.episteme.nativ.mathematics.linearalgebra.tensors
org.episteme.nativ.mathematics.linearalgebra.tensors.backends
org.episteme.nativ.mathematics.tensors.backends
org.episteme.nativ.physics.loaders.hdf5
org.episteme.natural.physics.classical.matter.fluids
org.episteme.natural.physics.classical.waves.electromagnetism.field
org.episteme.natural.physics.relativity

Uses of Tensor in org.episteme.core.mathematics.linearalgebra

Methods in org.episteme.core.mathematics.linearalgebra that return Tensor

Modifier and Type	Method	Description
Tensor<T>	Tensor.add(Tensor<T> other)	Element-wise addition.
Tensor<T>	Tensor.broadcast(int... newShape)	Broadcasts this tensor to a new shape.
Tensor<T>	Tensor.copy()	Returns a copy of this tensor.
default Tensor<T>	Tensor.einsum(String equation, Tensor<T>... operands)	Performs Einstein summation.
Tensor<T>	Tensor.map(Function<T,T> function)	Applies a function to each element of the tensor.
Tensor<T>	Tensor.multiply(Tensor<T> other)	Element-wise multiplication (Hadamard product).
static <T> Tensor<T>	Tensor.of(T[] data, int... shape)	Creates a tensor from data.
Tensor<T>	Tensor.reshape(int... newShape)	Reshapes this tensor to a new shape.
Tensor<T>	Tensor.scale(T scalar)	Scalar multiplication.
Tensor<T>	Tensor.slice(int[] starts, int[] sizes)	Returns a slice (sub-tensor) of this tensor.
Tensor<T>	Tensor.subtract(Tensor<T> other)	Element-wise subtraction.
Tensor<T>	Tensor.sum(int axis)	Sums along the specified axis.
default Tensor<E>	Matrix.toTensor()	Converts this matrix to a rank-2 tensor.
default Tensor<E>	Vector.toTensor()	Converts this vector to a rank-1 tensor.
default Tensor<T>	Tensor.transpose()	Transposes a rank-2 tensor (matrix).
Tensor<T>	Tensor.transpose(int... permutation)	Transposes dimensions according to the given permutation.
static <T> Tensor<T>	Tensor.zeros(Class<T> elementType, int... shape)	Creates a tensor of zeros with the specified shape.

Methods in org.episteme.core.mathematics.linearalgebra with parameters of type Tensor

Modifier and Type	Method	Description
Tensor<T>	Tensor.add(Tensor<T> other)	Element-wise addition.
default Tensor<T>	Tensor.einsum(String equation, Tensor<T>... operands)	Performs Einstein summation.
Tensor<T>	Tensor.multiply(Tensor<T> other)	Element-wise multiplication (Hadamard product).
Tensor<T>	Tensor.subtract(Tensor<T> other)	Element-wise subtraction.

Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors

Classes in org.episteme.core.mathematics.linearalgebra.tensors that implement Tensor

Modifier and Type	Class	Description
class	DenseTensor<T>	Dense tensor implementation backed by a flat array.
class	SparseTensor<T>	Sparse tensor implementation using a map for non-zero elements.

Methods in org.episteme.core.mathematics.linearalgebra.tensors that return Tensor

Modifier and Type	Method	Description
Tensor<T>	DenseTensor.add(Tensor<T> other)
Tensor<T>	SparseTensor.add(Tensor<T> other)
Tensor<T>	DenseTensor.broadcast(int... newShape)
Tensor<T>	SparseTensor.broadcast(int... newShape)
Tensor<T>	DenseTensor.copy()
Tensor<T>	SparseTensor.copy()
<T> Tensor<T>	TensorBackend.create(T[] data, int... shape)	Creates a tensor from a flat array and shape.
<T> Tensor<T>	TensorProvider.create(T[] data, int... shape)
static <T> Tensor<T>	EinsteinSummation.einsum(String equation, Tensor<T>... operands)	Performs Einstein summation.
Tensor<T>	DenseTensor.map(Function<T,T> function)
Tensor<T>	SparseTensor.map(Function<T,T> function)
Tensor<T>	DenseTensor.multiply(Tensor<T> other)
Tensor<T>	SparseTensor.multiply(Tensor<T> other)
<T> Tensor<T>	TensorBackend.ones(Class<T> elementType, int... shape)	Creates a tensor with the given shape, filled with ones.
<T> Tensor<T>	TensorProvider.ones(Class<T> elementType, int... shape)
Tensor<T>	DenseTensor.reshape(int... newShape)
Tensor<T>	SparseTensor.reshape(int... newShape)
Tensor<T>	DenseTensor.scale(T scalar)
Tensor<T>	SparseTensor.scale(T scalar)
Tensor<T>	DenseTensor.slice(int[] starts, int[] sizes)
Tensor<T>	SparseTensor.slice(int[] starts, int[] sizes)
Tensor<T>	DenseTensor.subtract(Tensor<T> other)
Tensor<T>	SparseTensor.subtract(Tensor<T> other)
Tensor<T>	DenseTensor.sum(int axis)
Tensor<T>	SparseTensor.sum(int axis)
Tensor<T>	DenseTensor.transpose(int... permutation)
Tensor<T>	SparseTensor.transpose(int... permutation)
<T> Tensor<T>	TensorBackend.zeros(Class<T> elementType, int... shape)	Creates a tensor with the given shape, filled with zeros.
<T> Tensor<T>	TensorProvider.zeros(Class<T> elementType, int... shape)

Methods in org.episteme.core.mathematics.linearalgebra.tensors with parameters of type Tensor

Modifier and Type	Method	Description
Tensor<T>	DenseTensor.add(Tensor<T> other)
Tensor<T>	SparseTensor.add(Tensor<T> other)
static <T> Tensor<T>	EinsteinSummation.einsum(String equation, Tensor<T>... operands)	Performs Einstein summation.
Tensor<T>	DenseTensor.multiply(Tensor<T> other)
Tensor<T>	SparseTensor.multiply(Tensor<T> other)
Tensor<T>	DenseTensor.subtract(Tensor<T> other)
Tensor<T>	SparseTensor.subtract(Tensor<T> other)

Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors.backends

Methods in org.episteme.core.mathematics.linearalgebra.tensors.backends that return Tensor

Modifier and Type	Method	Description
<T> Tensor<T>	CPUDenseTensorBackend.create(T[] data, int... shape)
<T> Tensor<T>	CPUSparseTensorBackend.create(T[] data, int... shape)
<T> Tensor<T>	CPUDenseTensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	CPUSparseTensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	CPUDenseTensorBackend.zeros(Class<T> elementType, int... shape)
<T> Tensor<T>	CPUSparseTensorBackend.zeros(Class<T> elementType, int... shape)

Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors.providers

Methods in org.episteme.core.mathematics.linearalgebra.tensors.providers that return Tensor

Modifier and Type	Method	Description
<T> Tensor<T>	DenseNeuralProvider.create(T[] data, int... shape)
<T> Tensor<T>	DenseNeuralProvider.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	DenseNeuralProvider.zeros(Class<T> elementType, int... shape)

Uses of Tensor in org.episteme.core.mathematics.linearalgebra.vectors

Methods in org.episteme.core.mathematics.linearalgebra.vectors that return Tensor

Modifier and Type	Method	Description
Tensor<E>	GenericVector.toTensor()

Uses of Tensor in org.episteme.core.mathematics.ml.neural

Methods in org.episteme.core.mathematics.ml.neural that return Tensor

Modifier and Type	Method	Description
default Tensor<T>	Layer.forward(Tensor<T> input)	Performs an optimized forward pass using raw tensors.
Tensor<T>	ComputationGraph.predict(Tensor<T> input)	Performs inference (forward pass) on the input.

Methods in org.episteme.core.mathematics.ml.neural that return types with arguments of type Tensor

Modifier and Type	Method	Description
default Map<String, Tensor<T>>	Layer.getGradients()	Returns the gradients of the learnable parameters.

Methods in org.episteme.core.mathematics.ml.neural with parameters of type Tensor

Modifier and Type	Method	Description
default Tensor<T>	Layer.forward(Tensor<T> input)	Performs an optimized forward pass using raw tensors.
Tensor<T>	ComputationGraph.predict(Tensor<T> input)	Performs inference (forward pass) on the input.
void	ComputationGraph.trainStep(Tensor<T> input, Tensor<T> target, Optimizer<T> optimizer)	Performs a training step (forward + backward + optimize).

Uses of Tensor in org.episteme.core.mathematics.ml.neural.autograd

Methods in org.episteme.core.mathematics.ml.neural.autograd that return Tensor

Modifier and Type	Method	Description
Tensor<T>	GraphNode.getData()
Tensor<T>	GraphNode.getGrad()

Methods in org.episteme.core.mathematics.ml.neural.autograd with parameters of type Tensor

Modifier and Type	Method	Description
void	GraphNode.BackwardFunc.backward(Tensor<T> outputGrad)
void	GraphNode.setData(Tensor<T> data)
void	GraphNode.setGrad(Tensor<T> grad)

Constructors in org.episteme.core.mathematics.ml.neural.autograd with parameters of type Tensor

Modifier	Constructor	Description
	GraphNode(Tensor<T> data)
	GraphNode(Tensor<T> data, boolean requiresGrad)
protected	GraphNode(Tensor<T> data, boolean requiresGrad, GraphNode.BackwardFunc<T> backwardFunc, List<GraphNode<T>> parents, String op)

Uses of Tensor in org.episteme.core.mathematics.ml.neural.backends

Methods in org.episteme.core.mathematics.ml.neural.backends that return types with arguments of type Tensor

Modifier and Type	Method	Description
Map<String, Tensor<?>>	ONNXRuntimeBackend.ONNXSession.run(Map<String, Tensor<?>> inputs)	Runs the model with input tensors.

Method parameters in org.episteme.core.mathematics.ml.neural.backends with type arguments of type Tensor

Modifier and Type	Method	Description
Map<String, Tensor<?>>	ONNXRuntimeBackend.ONNXSession.run(Map<String, Tensor<?>> inputs)	Runs the model with input tensors.

Uses of Tensor in org.episteme.core.mathematics.ml.neural.optimizers

Methods in org.episteme.core.mathematics.ml.neural.optimizers with parameters of type Tensor

Modifier and Type	Method	Description
void	Optimizer.update(Tensor<?> params, Tensor<?> grads)	Updates the improved parameters based on gradients.

Uses of Tensor in org.episteme.nativ.mathematics.linearalgebra.tensors

Classes in org.episteme.nativ.mathematics.linearalgebra.tensors that implement Tensor

Modifier and Type	Class	Description
class	CUDATensor<T>	CUDA implementation of Tensor backed by device (GPU) memory.
class	NativeTensor<T>	Tensor implementation backed by native memory (off-heap).

Methods in org.episteme.nativ.mathematics.linearalgebra.tensors that return Tensor

Modifier and Type	Method	Description
Tensor<T>	CUDATensor.add(Tensor<T> other)
Tensor<T>	NativeTensor.add(Tensor<T> other)
Tensor<T>	CUDATensor.broadcast(int... newShape)
Tensor<T>	NativeTensor.broadcast(int... newShape)
Tensor<T>	CUDATensor.copy()
Tensor<T>	NativeTensor.copy()
Tensor<T>	CUDATensor.map(Function<T,T> function)
Tensor<T>	NativeTensor.map(Function<T,T> function)
Tensor<T>	CUDATensor.multiply(Tensor<T> other)
Tensor<T>	NativeTensor.multiply(Tensor<T> other)
Tensor<T>	CUDATensor.reshape(int... newShape)
Tensor<T>	NativeTensor.reshape(int... newShape)
Tensor<T>	CUDATensor.scale(T scalar)
Tensor<T>	NativeTensor.scale(T scalar)
Tensor<T>	CUDATensor.slice(int[] starts, int[] sizes)
Tensor<T>	NativeTensor.slice(int[] starts, int[] sizes)
Tensor<T>	CUDATensor.subtract(Tensor<T> other)
Tensor<T>	NativeTensor.subtract(Tensor<T> other)
Tensor<T>	CUDATensor.sum(int axis)
Tensor<T>	NativeTensor.sum(int axis)
Tensor<T>	CUDATensor.transpose(int... permutation)
Tensor<T>	NativeTensor.transpose(int... permutation)

Methods in org.episteme.nativ.mathematics.linearalgebra.tensors with parameters of type Tensor

Modifier and Type	Method	Description
Tensor<T>	CUDATensor.add(Tensor<T> other)
Tensor<T>	NativeTensor.add(Tensor<T> other)
Tensor<T>	CUDATensor.multiply(Tensor<T> other)
Tensor<T>	NativeTensor.multiply(Tensor<T> other)
Tensor<T>	CUDATensor.subtract(Tensor<T> other)
Tensor<T>	NativeTensor.subtract(Tensor<T> other)

Uses of Tensor in org.episteme.nativ.mathematics.linearalgebra.tensors.backends

Methods in org.episteme.nativ.mathematics.linearalgebra.tensors.backends that return Tensor

Modifier and Type	Method	Description
<T> Tensor<T>	NativeND4JCUDASparseTensorBackend.create(T[] data, int... shape)
<T> Tensor<T>	ND4JBaseTensorBackend.create(T[] data, int... shape)
Tensor<Real>	ND4JBaseTensorBackend.fromINDArray(org.nd4j.linalg.api.ndarray.INDArray indArray)
<T> Tensor<T>	NativeND4JCUDASparseTensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	ND4JBaseTensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	NativeND4JCUDASparseTensorBackend.zeros(Class<T> elementType, int... shape)
<T> Tensor<T>	ND4JBaseTensorBackend.zeros(Class<T> elementType, int... shape)

Methods in org.episteme.nativ.mathematics.linearalgebra.tensors.backends with parameters of type Tensor

Modifier and Type	Method	Description
org.nd4j.linalg.api.ndarray.INDArray	ND4JBaseTensorBackend.toINDArray(Tensor<Real> tensor)

Uses of Tensor in org.episteme.nativ.mathematics.tensors.backends

Methods in org.episteme.nativ.mathematics.tensors.backends that return Tensor

Modifier and Type	Method	Description
<T> Tensor<T>	NativeCPUTensorBackend.create(T[] data, int... shape)
<T> Tensor<T>	NativeCUDATensorBackend.create(T[] data, int... shape)
<T> Tensor<T>	NativeCPUTensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	NativeCUDATensorBackend.ones(Class<T> elementType, int... shape)
<T> Tensor<T>	NativeCPUTensorBackend.zeros(Class<T> elementType, int... shape)
<T> Tensor<T>	NativeCUDATensorBackend.zeros(Class<T> elementType, int... shape)

Uses of Tensor in org.episteme.nativ.physics.loaders.hdf5

Subclasses with type arguments of type Tensor in org.episteme.nativ.physics.loaders.hdf5

Modifier and Type	Class	Description
class	NativeHDF5TensorWriter	Adapter to save Tensors to HDF5 files.

Methods in org.episteme.nativ.physics.loaders.hdf5 that return types with arguments of type Tensor

Modifier and Type	Method	Description
Class<Tensor<?>>	NativeHDF5TensorWriter.getResourceType()

Methods in org.episteme.nativ.physics.loaders.hdf5 with parameters of type Tensor

Modifier and Type	Method	Description
void	NativeHDF5TensorWriter.save(Tensor<?> resource, String destination)

Uses of Tensor in org.episteme.natural.physics.classical.matter.fluids

Methods in org.episteme.natural.physics.classical.matter.fluids that return Tensor

Modifier and Type	Method	Description
Tensor<Real>	FluidField.getDensity()
Tensor<Real>	FluidField.getPressure()
Tensor<Real>	FluidField.getVelocityX()
Tensor<Real>	FluidField.getVelocityY()
Tensor<Real>	FluidField.getVelocityZ()

Methods in org.episteme.natural.physics.classical.matter.fluids with parameters of type Tensor

Modifier and Type	Method	Description
void	FluidField.setDensity(Tensor<Real> density)
void	FluidField.setPressure(Tensor<Real> pressure)
void	FluidField.setVelocityX(Tensor<Real> velocityX)
void	FluidField.setVelocityY(Tensor<Real> velocityY)
void	FluidField.setVelocityZ(Tensor<Real> velocityZ)

Uses of Tensor in org.episteme.natural.physics.classical.waves.electromagnetism.field

Methods in org.episteme.natural.physics.classical.waves.electromagnetism.field that return Tensor

Modifier and Type	Method	Description
Tensor<Real>	ElectromagneticTensor.getTensor()	Returns the raw tensor object.

Methods in org.episteme.natural.physics.classical.waves.electromagnetism.field with parameters of type Tensor

Modifier and Type	Method	Description
DenseTensor<Real>	ElectromagneticTensor.extractElectricField(Tensor<Real> uObserver)	Extracts the electric field 4-vector seen by an observer with 4-velocity $u^\mu$.

Constructors in org.episteme.natural.physics.classical.waves.electromagnetism.field with parameters of type Tensor

Modifier	Constructor	Description
	ElectromagneticTensor(Tensor<Real> tensor)	Creates an EM tensor from explicit components.

Uses of Tensor in org.episteme.natural.physics.relativity

Methods in org.episteme.natural.physics.relativity that return Tensor

Modifier and Type	Method	Description
default Tensor<Real>	SpacetimeMetric.getChristoffelSymbols(Vector4D point)	Default implementation returns null.
Tensor<Real>	KerrMetric.getMetricTensor(Vector4D point)
Tensor<Real>	SchwarzschildMetric.getMetricTensor(Vector4D point)
Tensor<Real>	SpacetimeMetric.getMetricTensor(Vector4D point)	Calculates the covariant metric tensor $g_{\mu\nu}$ at the given event coordinates.