Uses of Interface
org.episteme.core.mathematics.linearalgebra.Tensor
Packages that use Tensor
Package
Description
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Uses of Tensor in org.episteme.core.mathematics.linearalgebra
Methods in org.episteme.core.mathematics.linearalgebra that return TensorModifier and TypeMethodDescriptionElement-wise addition.Tensor.broadcast(int... newShape) Broadcasts this tensor to a new shape.Tensor.copy()Returns a copy of this tensor.Performs Einstein summation.Applies a function to each element of the tensor.Element-wise multiplication (Hadamard product).static <T> Tensor<T> Tensor.of(T[] data, int... shape) Creates a tensor from data.Tensor.reshape(int... newShape) Reshapes this tensor to a new shape.Scalar multiplication.Tensor.slice(int[] starts, int[] sizes) Returns a slice (sub-tensor) of this tensor.Element-wise subtraction.Tensor.sum(int axis) Sums along the specified axis.Matrix.toTensor()Converts this matrix to a rank-2 tensor.Vector.toTensor()Converts this vector to a rank-1 tensor.Tensor.transpose()Transposes a rank-2 tensor (matrix).Tensor.transpose(int... permutation) Transposes dimensions according to the given permutation.static <T> Tensor<T> Creates a tensor of zeros with the specified shape.Methods in org.episteme.core.mathematics.linearalgebra with parameters of type TensorModifier and TypeMethodDescriptionElement-wise addition.Performs Einstein summation.Element-wise multiplication (Hadamard product).Element-wise subtraction. -
Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors
Classes in org.episteme.core.mathematics.linearalgebra.tensors that implement TensorModifier and TypeClassDescriptionclassDenseTensor<T>Dense tensor implementation backed by a flat array.classSparseTensor<T>Sparse tensor implementation using a map for non-zero elements.Methods in org.episteme.core.mathematics.linearalgebra.tensors that return TensorModifier and TypeMethodDescriptionDenseTensor.broadcast(int... newShape) SparseTensor.broadcast(int... newShape) DenseTensor.copy()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> Performs Einstein summation.<T> Tensor<T> Creates a tensor with the given shape, filled with ones.<T> Tensor<T> DenseTensor.reshape(int... newShape) SparseTensor.reshape(int... newShape) DenseTensor.slice(int[] starts, int[] sizes) SparseTensor.slice(int[] starts, int[] sizes) DenseTensor.sum(int axis) SparseTensor.sum(int axis) DenseTensor.transpose(int... permutation) SparseTensor.transpose(int... permutation) <T> Tensor<T> Creates a tensor with the given shape, filled with zeros.<T> Tensor<T> Methods in org.episteme.core.mathematics.linearalgebra.tensors with parameters of type Tensor -
Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors.backends
Methods in org.episteme.core.mathematics.linearalgebra.tensors.backends that return Tensor -
Uses of Tensor in org.episteme.core.mathematics.linearalgebra.tensors.providers
Methods in org.episteme.core.mathematics.linearalgebra.tensors.providers that return Tensor -
Uses of Tensor in org.episteme.core.mathematics.linearalgebra.vectors
Methods in org.episteme.core.mathematics.linearalgebra.vectors that return Tensor -
Uses of Tensor in org.episteme.core.mathematics.ml.neural
Methods in org.episteme.core.mathematics.ml.neural that return TensorModifier and TypeMethodDescriptionPerforms an optimized forward pass using raw tensors.Performs inference (forward pass) on the input.Methods in org.episteme.core.mathematics.ml.neural that return types with arguments of type TensorModifier and TypeMethodDescriptionLayer.getGradients()Returns the gradients of the learnable parameters.Methods in org.episteme.core.mathematics.ml.neural with parameters of type TensorModifier and TypeMethodDescriptionPerforms an optimized forward pass using raw tensors.Performs inference (forward pass) on the input.voidPerforms 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 TensorMethods in org.episteme.core.mathematics.ml.neural.autograd with parameters of type TensorModifier and TypeMethodDescriptionvoidvoidvoidConstructors in org.episteme.core.mathematics.ml.neural.autograd with parameters of type Tensor -
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 TensorModifier and TypeMethodDescriptionRuns the model with input tensors.Method parameters in org.episteme.core.mathematics.ml.neural.backends with type arguments of type Tensor -
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 -
Uses of Tensor in org.episteme.nativ.mathematics.linearalgebra.tensors
Classes in org.episteme.nativ.mathematics.linearalgebra.tensors that implement TensorModifier and TypeClassDescriptionclassCUDATensor<T>CUDA implementation of Tensor backed by device (GPU) memory.classNativeTensor<T>Tensor implementation backed by native memory (off-heap).Methods in org.episteme.nativ.mathematics.linearalgebra.tensors that return TensorModifier and TypeMethodDescriptionCUDATensor.broadcast(int... newShape) NativeTensor.broadcast(int... newShape) CUDATensor.copy()NativeTensor.copy()CUDATensor.reshape(int... newShape) NativeTensor.reshape(int... newShape) CUDATensor.slice(int[] starts, int[] sizes) NativeTensor.slice(int[] starts, int[] sizes) CUDATensor.sum(int axis) NativeTensor.sum(int axis) CUDATensor.transpose(int... permutation) NativeTensor.transpose(int... permutation) Methods in org.episteme.nativ.mathematics.linearalgebra.tensors with parameters of type TensorModifier and TypeMethodDescription -
Uses of Tensor in org.episteme.nativ.mathematics.linearalgebra.tensors.backends
Methods in org.episteme.nativ.mathematics.linearalgebra.tensors.backends that return TensorModifier and TypeMethodDescription<T> Tensor<T> NativeND4JCUDASparseTensorBackend.create(T[] data, int... shape) <T> Tensor<T> ND4JBaseTensorBackend.create(T[] data, int... shape) ND4JBaseTensorBackend.fromINDArray(org.nd4j.linalg.api.ndarray.INDArray indArray) <T> Tensor<T> <T> Tensor<T> <T> Tensor<T> <T> Tensor<T> Methods in org.episteme.nativ.mathematics.linearalgebra.tensors.backends with parameters of type TensorModifier and TypeMethodDescriptionorg.nd4j.linalg.api.ndarray.INDArrayND4JBaseTensorBackend.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 -
Uses of Tensor in org.episteme.nativ.physics.loaders.hdf5
Subclasses with type arguments of type Tensor in org.episteme.nativ.physics.loaders.hdf5Modifier and TypeClassDescriptionclassAdapter to save Tensors to HDF5 files.Methods in org.episteme.nativ.physics.loaders.hdf5 that return types with arguments of type TensorMethods in org.episteme.nativ.physics.loaders.hdf5 with parameters of type Tensor -
Uses of Tensor in org.episteme.natural.physics.classical.matter.fluids
Methods in org.episteme.natural.physics.classical.matter.fluids that return TensorModifier and TypeMethodDescriptionFluidField.getDensity()FluidField.getPressure()FluidField.getVelocityX()FluidField.getVelocityY()FluidField.getVelocityZ()Methods in org.episteme.natural.physics.classical.matter.fluids with parameters of type TensorModifier and TypeMethodDescriptionvoidFluidField.setDensity(Tensor<Real> density) voidFluidField.setPressure(Tensor<Real> pressure) voidFluidField.setVelocityX(Tensor<Real> velocityX) voidFluidField.setVelocityY(Tensor<Real> velocityY) voidFluidField.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 TensorModifier and TypeMethodDescriptionElectromagneticTensor.getTensor()Returns the raw tensor object.Methods in org.episteme.natural.physics.classical.waves.electromagnetism.field with parameters of type TensorModifier and TypeMethodDescriptionElectromagneticTensor.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 TensorModifierConstructorDescriptionElectromagneticTensor(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 TensorModifier and TypeMethodDescriptionSpacetimeMetric.getChristoffelSymbols(Vector4D point) Default implementation returns null.KerrMetric.getMetricTensor(Vector4D point) SchwarzschildMetric.getMetricTensor(Vector4D point) SpacetimeMetric.getMetricTensor(Vector4D point) Calculates the covariant metric tensor $g_{\mu\nu}$ at the given event coordinates.