Package smile.deep.tensor

Class Tensor

java.lang.Object

smile.deep.tensor.Tensor

All Implemented Interfaces:

AutoCloseable

public class Tensor
extends Object
implements AutoCloseable

A Tensor is a multidimensional array containing elements of a single data type.

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Tensor.Options	A class that encapsulates the construction axes of a tensor.

Constructor Summary

Constructors

Constructor	Description
Tensor(org.bytedeco.pytorch.Tensor tensor)	Constructor.

Method Summary

Modifier and Type	Method	Description
Tensor	acos()	Returns a new tensor with the arccosine of the elements of input.
Tensor	acos_()	Computes the arccosine of the elements of input in place.
Tensor	add(double other)	Returns A + b.
Tensor	add(float other)	Returns A + b.
Tensor	add(Tensor other)	Returns A + B.
Tensor	add(Tensor other, double alpha)	Returns A + alpha * B.
Tensor	add_(double other)	Returns A += b.
Tensor	add_(float other)	Returns A += b.
Tensor	add_(Tensor other)	Returns A += B.
Tensor	add_(Tensor other, double alpha)	Returns A += alpha * B.
boolean	all()	Tests if all elements in the tensor are true.
Tensor	and(Tensor other)	Returns logical AND of two boolean tensors.
Tensor	and_(Tensor other)	Returns logical AND of two boolean tensors.
static Tensor	arange(long start, long end, long step)	Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.
Tensor	argmax(int dim, boolean keepDim)	Returns the indices of the maximum value of a tensor across a dimension.
Tensor	asin()	Returns a new tensor with the arcsine of the elements of input.
Tensor	asin_()	Computes the arcsine of the elements of input in place.
org.bytedeco.pytorch.Tensor	asTorch()	Returns the PyTorch tensor object.
void	backward()	Computes the gradients.
Tensor	bernoulli_(double p)	Draws binary random numbers (0 or 1) from a Bernoulli distribution.
boolean	boolValue()	Returns the boolean value when the tensor holds a single value.
byte[]	byteArray()	Returns the byte array of tensor elements
byte	byteValue()	Returns the byte value when the tensor holds a single value.
void	close()
Tensor	contiguous()	Returns a contiguous in memory tensor containing the same data as this tensor.
Tensor	cos()	Returns a new tensor with the cosine of the elements of input.
Tensor	cos_()	Computes the cosine of the elements of input in place.
static Tensor	crossEntropy(Tensor input, Tensor target, String reduction, long ignoreIndex)	Computes the cross entropy loss between input logits and target.
Tensor	detach()	Returns a new tensor, detached from the current graph.
Device	device()	Returns the device on which the tensor is.
int	dim()	Returns the number of dimensions of tensor.
Tensor	div(double other)	Returns A / b.
Tensor	div(float other)	Returns A / b.
Tensor	div(Tensor other)	Returns A / B element wisely.
Tensor	div_(double other)	Returns A /= b.
Tensor	div_(float other)	Returns A /= b.
Tensor	div_(Tensor other)	Returns A /= B element wisely.
double[]	doubleArray()	Returns the double array of tensor elements
double	doubleValue()	Returns the double value when the tensor holds a single value.
Tensor	dropout(double p)	Randomly zeroes some elements of the input tensor with probability p.
Tensor	dropout_(double p)	Randomly zeroes some elements in place with probability p.
ScalarType	dtype()	Returns the element data type.
static Tensor	empty(long... shape)	Returns a tensor with uninitialized data.
static Tensor	empty(Tensor.Options options, long... shape)	Returns a tensor with uninitialized data.
Tensor	eq(double other)	Computes element-wise equality.
Tensor	eq(int other)	Computes element-wise equality.
Tensor	eq(Tensor other)	Computes element-wise equality.
boolean	equals(Object other)
Tensor	exp()	Returns the exponential of elements in the tensor.
Tensor	exp_()	Returns the exponential of elements in the tensor in place.
Tensor	expand(long... size)	Returns a new view of this tensor with singleton dimensions expanded to a larger size.
static Tensor	eye(long shape)	Returns an identity matrix.
static Tensor	eye(Tensor.Options options, long shape)	Returns an identity matrix.
Tensor	fill_(double x)	Fills this tensor with the specified value.
Tensor	fill_(int x)	Fills this tensor with the specified value.
Tensor	flatten()	Flattens the tensor by reshaping it into a one-dimensional tensor.
Tensor	flatten(int startDim)	Flattens the tensor by reshaping it into a one-dimensional tensor.
Tensor	flatten(int startDim, int endDim)	Flattens the tensor by reshaping it into a one-dimensional tensor.
float[]	floatArray()	Returns the float array of tensor elements
float	floatValue()	Returns the float value when the tensor holds a single value.
static Tensor	full(double value, long... shape)	Returns a tensor filled with the given value.
static Tensor	full(long value, long... shape)	Returns a tensor filled with the given value.
Tensor	gather(int dim, Tensor index)	Gathers values along an axis specified by dim.
Tensor	ge(double other)	Computes element-wise greater-than-or-equal-to comparison.
Tensor	ge(int other)	Computes element-wise greater-than-or-equal-to comparison.
Tensor	ge(Tensor other)	Computes element-wise greater-than-or-equal-to comparison.
Tensor	get(int... indices)	Returns a portion of tensor given the indices.
Tensor	get(long... indices)	Returns a portion of tensor given the indices.
Tensor	get(Index... indices)	Returns a portion of tensor given the indices.
Tensor	get(Tensor index)	Returns a portion of tensor given the indices.
byte	getByte(int... indices)	Returns the byte value of element at given index.
byte	getByte(long... indices)	Returns the byte value of element at given index.
double	getDouble(int... indices)	Returns the double value of element at given index.
double	getDouble(long... indices)	Returns the double value of element at given index.
float	getFloat(int... indices)	Returns the float value of element at given index.
float	getFloat(long... indices)	Returns the float value of element at given index.
int	getInt(int... indices)	Returns the int value of element at given index.
int	getInt(long... indices)	Returns the int value of element at given index.
long	getLong(int... indices)	Returns the long value of element at given index.
long	getLong(long... indices)	Returns the long value of element at given index.
boolean	getRequireGrad()	Returns true if autograd should record operations on this tensor.
short	getShort(int... indices)	Returns the short value of element at given index.
short	getShort(long... indices)	Returns the short value of element at given index.
Tensor	gt(double other)	Computes element-wise greater-than comparison.
Tensor	gt(int other)	Computes element-wise greater-than comparison.
Tensor	gt(Tensor other)	Computes element-wise greater-than comparison.
static Tensor	hstack(Tensor... tensors)	Stacks tensors in sequence horizontally (column wise).
int[]	intArray()	Returns the integer array of tensor elements
int	intValue()	Returns the int value when the tensor holds a single value.
static boolean	isBF16Supported()	Checks if the CUDA device supports bf16.
Tensor	isin(Tensor other)	Tests if each element of this tensor is in other tensor.
Tensor	le(double other)	Computes element-wise less-than-or-equal-to comparison.
Tensor	le(int other)	Computes element-wise less-than-or-equal-to comparison.
Tensor	le(Tensor other)	Computes element-wise less-than-or-equal-to comparison.
long	length()	Returns the number of tensor elements.
long[]	longArray()	Returns the long integer array of tensor elements
long	longValue()	Returns the long value when the tensor holds a single value.
Tensor	lt(double other)	Computes element-wise less-than comparison.
Tensor	lt(int other)	Computes element-wise less-than comparison.
Tensor	lt(Tensor other)	Computes element-wise less-than comparison.
Tensor	matmul(Tensor other)	Returns the matrix product of two tensors.
Tensor	mean()	Returns the mean of all elements in the tensor.
Tensor	mean(int dim, boolean keepDim)	Returns the mean along a dimension in the tensor.
Tensor	mul(double other)	Returns A * b.
Tensor	mul(float other)	Returns A * b.
Tensor	mul(Tensor other)	Returns A * B element wisely.
Tensor	mul_(double other)	Returns A *= b.
Tensor	mul_(float other)	Returns A *= b.
Tensor	mul_(Tensor other)	Returns A *= B element wisely.
Tensor	ne(double other)	Computes element-wise inequality.
Tensor	ne(int other)	Computes element-wise inequality.
Tensor	ne(Tensor other)	Computes element-wise inequality.
Tensor	neg()	Returns a new tensor with the negative of the elements of input.
Tensor	neg_()	Returns the tensor with the negative of the elements of input.
Tensor	newOnes(long... shape)	Returns a tensor filled with all ones.
Tensor	newZeros(long... shape)	Returns a tensor filled with all zeros.
static org.bytedeco.pytorch.NoGradGuard	noGradGuard()	Disables gradient calculation.
Tensor	not()	Returns logical NOT of this tensor.
Tensor	not_()	Returns logical NOT of this tensor.
static Tensor	of(boolean[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(byte[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(double[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(float[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(int[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(long[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	of(short[] data, long... shape)	Returns a tensor with given data and shape.
static Tensor	ones(long... shape)	Returns a tensor filled with all ones.
static Tensor	ones(Tensor.Options options, long... shape)	Returns a tensor filled with all ones.
Tensor	or(Tensor other)	Returns logical OR of two boolean tensors.
Tensor	or_(Tensor other)	Returns logical OR of two boolean tensors.
Tensor	outer(Tensor other)	Returns the outer product of two tensors.
Tensor	permute(long... dims)	Returns a view of the original tensor input with its dimensions permuted.
static Tensor	polar(Tensor abs, Tensor angle)	Returns a complex tensor whose elements are Cartesian coordinates corresponding to the polar coordinates with abs and angle.
static AutoScope	pop()	Removes the scope at the top of the tensor stack.
Tensor	pow(double exponent)	Returns a new tensor with the power of the elements of input.
Tensor	pow_(double exponent)	Computes the power of the elements of input in place.
void	print()	Prints the tensor on the standard output.
static void	push(AutoScope scope)	Pushes a scope onto the top of the tensor scope stack.
Tensor	put(Tensor source, Index... indices)	Updates a portion of tensor.
Tensor	put(Tensor source, Tensor index)	Updates a portion of tensor.
Tensor	put_(byte x, int... indices)	Updates an element in place.
Tensor	put_(byte x, long... indices)	Updates an element in place.
Tensor	put_(double x, int... indices)	Updates an element in place.
Tensor	put_(double x, long... indices)	Updates an element in place.
Tensor	put_(float x, int... indices)	Updates an element in place.
Tensor	put_(float x, long... indices)	Updates an element in place.
Tensor	put_(int x, int... indices)	Updates an element in place.
Tensor	put_(int x, long... indices)	Updates an element in place.
Tensor	put_(long x, int... indices)	Updates an element in place.
Tensor	put_(long x, long... indices)	Updates an element in place.
Tensor	put_(short x, int... indices)	Updates an element in place.
Tensor	put_(short x, long... indices)	Updates an element in place.
Tensor	put_(Tensor source, Index... indices)	Updates a portion of tensor in place.
Tensor	put_(Tensor source, Tensor index)	Updates a portion of tensor in place.
static Tensor	rand(long... shape)	Returns a tensor filled with values drawn from a uniform distribution on [0, 1).
static Tensor	rand(Tensor.Options options, long... shape)	Returns a tensor filled with values drawn from a uniform distribution on [0, 1).
static Tensor	randn(long... shape)	Returns a tensor filled with values drawn from a unit normal distribution.
static Tensor	randn(Tensor.Options options, long... shape)	Returns a tensor filled with values drawn from a unit normal distribution.
Tensor	reshape(long... shape)	Returns a tensor with the same data and number of elements but with the specified shape.
Tensor	rsqrt()	Returns the reciprocal of the square-root of each of the elements in the tensor.
Tensor	rsqrt_()	Returns the reciprocal of the square-root of each of the elements in the tensor.
Tensor	scatterReduce(int dim, Tensor index, Tensor source, String reduce)	Writes all values from the tensor src into this tensor at the indices specified in the index tensor.
Tensor	scatterReduce_(int dim, Tensor index, Tensor source, String reduce)	Writes all values from the tensor src into this tensor at the indices specified in the index tensor.
static void	setDefaultOptions(Tensor.Options options)	Sets the default options to create tensors.
Tensor	setRequireGrad(boolean required)	Sets if autograd should record operations on this tensor.
long[]	shape()	Returns the shape of the tensor.
short[]	shortArray()	Returns the short integer array of tensor elements
short	shortValue()	Returns the short value when the tensor holds a single value.
Tensor	sin()	Returns a new tensor with the sine of the elements of input.
Tensor	sin_()	Computes the sine of the elements of input in place.
long	size(int dim)	Returns the size of given dimension.
Tensor	softmax(int dim)	Rescales a tensor so that the elements lie in the range [0,1] and sum to 1.
Tensor	sub(double other)	Returns A -= b.
Tensor	sub(float other)	Returns A - b.
Tensor	sub(Tensor other)	Returns A - B.
Tensor	sub(Tensor other, double alpha)	Returns A - alpha * B.
Tensor	sub_(double other)	Returns A -= b.
Tensor	sub_(float other)	Returns A - b.
Tensor	sub_(Tensor other)	Returns A -= B.
Tensor	sub_(Tensor other, double alpha)	Returns A -= alpha * B.
Tensor	sum()	Returns the sum of all elements in the tensor.
Tensor	to(Device device)	Clone the tensor to a device.
Tensor	to(Device device, ScalarType dtype)	Clone the tensor to a device with a different data type.
Tensor	to(ScalarType dtype)	Clone the tensor with a different data type.
Tuple2<Tensor,Tensor>	topk(int k)	Returns the k largest elements.
Tuple2<Tensor,Tensor>	topk(int k, int dim, boolean largest, boolean sorted)	Returns the k largest elements along a given dimension.
Tensor	topp(double p)	Performs top-p (nucleus) sampling on a probability distribution.
String	toString()
Tensor	transpose(long dim0, long dim1)	Returns a tensor that is a transposed version of input.
Tensor	triu(long diagonal)	Returns the upper triangular part of a matrix (2-D tensor) or batch of matrices input, the other elements of the result tensor out are set to 0.
Tensor	triu_(long diagonal)	Returns the upper triangular part of a matrix (2-D tensor) or batch of matrices input, the other elements of the result tensor out are set to 0.
Tensor	unsqueeze(long dim)	Returns a new tensor with a dimension of size one inserted at the specified position.
Tensor	view(long... shape)	Returns a view tensor that shares the same underlying data with this base tensor.
Tensor	viewAsComplex()	Returns a view of tensor as a complex tensor.
Tensor	viewAsReal()	Returns a view of tensor as a real tensor.
static Tensor	vstack(Tensor... tensors)	Stacks tensors in sequence vertically (row wise).
static Tensor	where(Tensor condition, double input, double other)	Returns a tensor of elements selected from either input or other, depending on condition.
static Tensor	where(Tensor condition, int input, int other)	Returns a tensor of elements selected from either input or other, depending on condition.
static Tensor	where(Tensor condition, Tensor input, Tensor other)	Returns a tensor of elements selected from either input or other, depending on condition.
static Tensor	zeros(long... shape)	Returns a tensor filled with all zeros.
static Tensor	zeros(Tensor.Options options, long... shape)	Returns a tensor filled with all zeros.

Methods inherited from class java.lang.Object

clone, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Details

Tensor

public Tensor(org.bytedeco.pytorch.Tensor tensor)

Constructor.

Parameters:

tensor - PyTorch Tensor object.

Method Details

setDefaultOptions

public static void setDefaultOptions(Tensor.Options options)

Sets the default options to create tensors. This does not affect factory function calls which are called with an explicit options argument.

Parameters:

options - the construction options of a tensor.

isBF16Supported

public static boolean isBF16Supported()

Checks if the CUDA device supports bf16. On pre-ampere hardware bf16 works, but doesn't provide speed-ups compared to fp32 matmul operations, and some matmul operations are failing outright, so this check is more like "guaranteed to work and be performant" than "works somehow".

Returns:

true if bf16 works and is performant.

noGradGuard

public static org.bytedeco.pytorch.NoGradGuard noGradGuard()

Disables gradient calculation. Disabling gradient calculation is useful for inference, when you are sure that you will not call backward. It will reduce memory consumption for computations that would otherwise have requireGrad(true).

In this mode, the result of every computation will have requireGrad(false), even when the inputs have requireGrad(true).

This context manager is thread-local; it will not affect computation in other threads.

Returns:

no grad guard to be used with try-with scope.

push

public static void push(AutoScope scope)

Pushes a scope onto the top of the tensor scope stack. Newly created tensors will be automatically added to this scope.

Parameters:

scope - a scope to automatically release tensors.

pop

public static AutoScope pop()

Removes the scope at the top of the tensor stack. All tensors added to this scope will be released.

Returns:

the top level scope.

print

public void print()

Prints the tensor on the standard output.

equals

public boolean equals(Object other)

Overrides:

equals in class Object

close

public void close()

Specified by:

close in interface AutoCloseable

toString

public String toString()

Overrides:

toString in class Object

asTorch

public org.bytedeco.pytorch.Tensor asTorch()

Returns the PyTorch tensor object.

Returns:

the PyTorch tensor object.

setRequireGrad

public Tensor setRequireGrad(boolean required)

Sets if autograd should record operations on this tensor.

Parameters:

required - the flag indicating if autograd should record operations on this tensor.

Returns:

this tensor.

getRequireGrad

public boolean getRequireGrad()

Returns true if autograd should record operations on this tensor.

Returns:

true if autograd should record operations on this tensor.

detach

public Tensor detach()

Returns a new tensor, detached from the current graph. The result will never require gradient.

Returns:

a new tensor that doesn't require gradient.

to

public Tensor to(ScalarType dtype)

Clone the tensor with a different data type.

Parameters:

dtype - the element data type of new tensor.

Returns:

The cloned tensor.

to

public Tensor to(Device device)

Clone the tensor to a device.

Parameters:

device - the compute device of new tensor.

Returns:

The cloned tensor.

to

public Tensor to(Device device,
 ScalarType dtype)

Clone the tensor to a device with a different data type.

Parameters:

device - the compute device of new tensor.

dtype - the element data type of new tensor.

Returns:

The cloned tensor.

dtype

public ScalarType dtype()

Returns the element data type.

Returns:

the element data type.

device

public Device device()

Returns the device on which the tensor is.

Returns:

the device.

dim

public int dim()

Returns the number of dimensions of tensor.

Returns:

the number of dimensions of tensor

shape

public long[] shape()

Returns the shape of the tensor.

Returns:

the shape of the tensor.

size

public long size(int dim)

Returns the size of given dimension.

Parameters:

dim - dimension index.

Returns:

the size of given dimension.

length

public long length()

Returns the number of tensor elements.

Returns:

the number of tensor elements.

neg

public Tensor neg()

Returns a new tensor with the negative of the elements of input.

Returns:

the output tensor.

neg_

public Tensor neg_()

Returns the tensor with the negative of the elements of input.

Returns:

this tensor.

contiguous

public Tensor contiguous()

Returns a contiguous in memory tensor containing the same data as this tensor.

Returns:

a contiguous in memory tensor containing the same data as this tensor.

expand

public Tensor expand(long... size)

Returns a new view of this tensor with singleton dimensions expanded to a larger size.

Parameters:

size - the desired expanded size.

Returns:

the tensor view with the expanded size.

reshape

public Tensor reshape(long... shape)

Returns a tensor with the same data and number of elements but with the specified shape. This method returns a view if shape is compatible with the current shape.

Parameters:

shape - the new shape of tensor.

Returns:

the tensor with the specified shape.

flatten

public Tensor flatten()

Flattens the tensor by reshaping it into a one-dimensional tensor. This function may return the original object, a view, or copy.

Returns:

the tensor with the specified shape.

flatten

public Tensor flatten(int startDim)

Flattens the tensor by reshaping it into a one-dimensional tensor. Only dimensions starting with startDim and ending with endDim are flattened. The order of elements in input is unchanged. This function may return the original object, a view, or copy.

Parameters:

startDim - the first dim to flatten.

Returns:

the tensor with the specified shape.

flatten

public Tensor flatten(int startDim,
 int endDim)

Flattens the tensor by reshaping it into a one-dimensional tensor. Only dimensions starting with startDim and ending with endDim are flattened. The order of elements in input is unchanged. This function may return the original object, a view, or copy.

Parameters:

startDim - the first dim to flatten.

endDim - the last dim to flatten

Returns:

the tensor with the specified shape.

backward

public void backward()

Computes the gradients.

fill_

public Tensor fill_(int x)

Fills this tensor with the specified value.

Parameters:

x - the value.

Returns:

this tensor.

fill_

public Tensor fill_(double x)

Fills this tensor with the specified value.

Parameters:

x - the value.

Returns:

this tensor.

bernoulli_

public Tensor bernoulli_(double p)

Draws binary random numbers (0 or 1) from a Bernoulli distribution.

Parameters:

p - Bernoulli probability.

Returns:

this tensor.

permute

public Tensor permute(long... dims)

Returns a view of the original tensor input with its dimensions permuted.

Parameters:

dims - The desired ordering of dimensions.

Returns:

the permuted tensor.

put

public Tensor put(Tensor source,
 Index... indices)

Updates a portion of tensor.

Parameters:

source - the new sub-tensor values.

indices - the indices along the dimensions.

Returns:

the output tensor.

put

public Tensor put(Tensor source,
 Tensor index)

Updates a portion of tensor.

Parameters:

source - the new sub-tensor value.

index - the sub-tensor index.

Returns:

the output tensor.

put_

public Tensor put_(Tensor source,
 Index... indices)

Updates a portion of tensor in place.

Parameters:

source - the new sub-tensor values.

indices - the indices along the dimensions.

Returns:

this tensor.

put_

public Tensor put_(Tensor source,
 Tensor index)

Updates a portion of tensor in place.

Parameters:

source - the new sub-tensor value.

index - the sub-tensor index.

Returns:

this tensor.

put_

public Tensor put_(byte x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(byte x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(short x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(short x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(int x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(int x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(long x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(long x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(float x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(float x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(double x,
 int... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

put_

public Tensor put_(double x,
 long... indices)

Updates an element in place.

Parameters:

x - the new element value.

indices - the element indices.

Returns:

this tensor.

get

public Tensor get(int... indices)

Returns a portion of tensor given the indices.

Parameters:

indices - the indices along the dimensions.

Returns:

the sub-tensor.

get

public Tensor get(long... indices)

Returns a portion of tensor given the indices.

Parameters:

indices - the indices along the dimensions.

Returns:

the sub-tensor.

get

public Tensor get(Index... indices)

Returns a portion of tensor given the indices.

Parameters:

indices - the indices along the dimensions.

Returns:

the sub-tensor.

get

public Tensor get(Tensor index)

Returns a portion of tensor given the indices.

Parameters:

index - the tensor index.

Returns:

the sub-tensor.

getByte

public byte getByte(int... indices)

Returns the byte value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getByte

public byte getByte(long... indices)

Returns the byte value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getShort

public short getShort(int... indices)

Returns the short value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getShort

public short getShort(long... indices)

Returns the short value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getInt

public int getInt(int... indices)

Returns the int value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getInt

public int getInt(long... indices)

Returns the int value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getLong

public long getLong(int... indices)

Returns the long value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getLong

public long getLong(long... indices)

Returns the long value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getFloat

public float getFloat(int... indices)

Returns the float value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getFloat

public float getFloat(long... indices)

Returns the float value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getDouble

public double getDouble(int... indices)

Returns the double value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

getDouble

public double getDouble(long... indices)

Returns the double value of element at given index.

Parameters:

indices - the indices along the dimensions.

Returns:

the element value.

boolValue

public boolean boolValue()

Returns the boolean value when the tensor holds a single value.

Returns:

the boolean value when the tensor holds a single value.

byteValue

public byte byteValue()

Returns the byte value when the tensor holds a single value.

Returns:

the byte value when the tensor holds a single value.

shortValue

public short shortValue()

Returns the short value when the tensor holds a single value.

Returns:

the short value when the tensor holds a single value.

intValue

public int intValue()

Returns the int value when the tensor holds a single value.

Returns:

the int value when the tensor holds a single value.

longValue

public long longValue()

Returns the long value when the tensor holds a single value.

Returns:

the long value when the tensor holds a single value.

floatValue

public float floatValue()

Returns the float value when the tensor holds a single value.

Returns:

the float value when the tensor holds a single value.

doubleValue

public double doubleValue()

Returns the double value when the tensor holds a single value.

Returns:

the double value when the tensor holds a single value.

byteArray

public byte[] byteArray()

Returns the byte array of tensor elements

Returns:

the byte array of tensor elements.

shortArray

public short[] shortArray()

Returns the short integer array of tensor elements

Returns:

the short integer array of tensor elements.

intArray

public int[] intArray()

Returns the integer array of tensor elements

Returns:

the integer array of tensor elements.

longArray

public long[] longArray()

Returns the long integer array of tensor elements

Returns:

the long integer array of tensor elements.

floatArray

public float[] floatArray()

Returns the float array of tensor elements

Returns:

the float array of tensor elements.

doubleArray

public double[] doubleArray()

Returns the double array of tensor elements

Returns:

the double array of tensor elements.

unsqueeze

public Tensor unsqueeze(long dim)

Returns a new tensor with a dimension of size one inserted at the specified position.

The returned tensor shares the same underlying data with this tensor.

A dim value within the range [-input.dim() - 1, input.dim() + 1) can be used. Negative dim will correspond to unsqueeze() applied at dim = dim + input.dim() + 1.

Parameters:

dim - the index at which to insert the singleton dimension.

Returns:

the output tensor.

transpose

public Tensor transpose(long dim0,
 long dim1)

Returns a tensor that is a transposed version of input. The given dimensions dim0 and dim1 are swapped.

If input is a strided tensor then the resulting out tensor shares its underlying storage with the input tensor, so changing the content of one would change the content of the other.

If input is a sparse tensor then the resulting out tensor does not share the underlying storage with the input tensor.

If input is a sparse tensor with compressed layout (SparseCSR, SparseBSR, SparseCSC or SparseBSC) the arguments dim0 and dim1 must be both batch dimensions, or must both be sparse dimensions. The batch dimensions of a sparse tensor are the dimensions preceding the sparse dimensions.

Parameters:

dim0 - the first dimension to be transposed.

dim1 - the second dimension to be transposed.

Returns:

the output tensor.

triu

public Tensor triu(long diagonal)

Returns the upper triangular part of a matrix (2-D tensor) or batch of matrices input, the other elements of the result tensor out are set to 0.

Parameters:

diagonal - The parameter diagonal controls which diagonal to consider. If diagonal = 0, all elements on and above the main diagonal are retained. A positive value excludes just as many diagonals above the main diagonal, and similarly a negative value includes just as many diagonals below the main diagonal.

Returns:

the output tensor.

triu_

public Tensor triu_(long diagonal)

Returns the upper triangular part of a matrix (2-D tensor) or batch of matrices input, the other elements of the result tensor out are set to 0.

Parameters:

diagonal - The parameter diagonal controls which diagonal to consider. If diagonal = 0, all elements on and above the main diagonal are retained. A positive value excludes just as many diagonals above the main diagonal, and similarly a negative value includes just as many diagonals below the main diagonal.

Returns:

this tensor.

view

public Tensor view(long... shape)

Returns a view tensor that shares the same underlying data with this base tensor. Supporting View avoids explicit data copy, thus allows us to do fast and memory efficient reshaping, slicing and element-wise operations.

Parameters:

shape - the shape of view tensor.

Returns:

the view tensor.

viewAsComplex

public Tensor viewAsComplex()

Returns a view of tensor as a complex tensor.

Returns:

the complex tensor view.

viewAsReal

public Tensor viewAsReal()

Returns a view of tensor as a real tensor.

Returns:

the real tensor view.

argmax

public Tensor argmax(int dim,
 boolean keepDim)

Returns the indices of the maximum value of a tensor across a dimension.

Parameters:

dim - the dimension to reduce.

keepDim - whether the output tensor has dim retained or not.

Returns:

the indices of the maximum value of a tensor across a dimension.

topk

public Tuple2<Tensor,Tensor> topk(int k)

Returns the k largest elements.

Parameters:

k - the number of largest elements.

Returns:

the values and indices of the largest k elements.

topk

public Tuple2<Tensor,Tensor> topk(int k,
 int dim,
 boolean largest,
 boolean sorted)

Returns the k largest elements along a given dimension.

Parameters:

k - the number of largest elements.

dim - the dimension to sort along.

largest - controls whether to return largest or smallest elements.

sorted - controls whether to return the elements in sorted order.

Returns:

the values and indices of the largest k elements.

topp

public Tensor topp(double p)

Performs top-p (nucleus) sampling on a probability distribution. Top-p sampling selects the smallest set of tokens whose cumulative probability mass exceeds the threshold p. The distribution is renormalized based on the selected tokens.

Parameters:

p - Probability threshold for top-p sampling.

Returns:

Sampled token indices.

hstack

public static Tensor hstack(Tensor... tensors)

Stacks tensors in sequence horizontally (column wise).

Parameters:

tensors - the tensors to concatenate.

Returns:

the output tensor.

vstack

public static Tensor vstack(Tensor... tensors)

Stacks tensors in sequence vertically (row wise).

Parameters:

tensors - the tensors to concatenate.

Returns:

the output tensor.

polar

public static Tensor polar(Tensor abs,
 Tensor angle)

Returns a complex tensor whose elements are Cartesian coordinates corresponding to the polar coordinates with abs and angle.

Parameters:

abs - The absolute value the complex tensor. Must be float or double.

angle - The angle of the complex tensor. Must be same dtype as abs.

Returns:

the complex tensor.

crossEntropy

public static Tensor crossEntropy(Tensor input,
 Tensor target,
 String reduction,
 long ignoreIndex)

Computes the cross entropy loss between input logits and target.

Parameters:

input - Predicted unnormalized logits.

target - Ground truth class indices or class probabilities.

reduction - Specifies the reduction to apply to the output: "none" | "mean" | "sum". "none": no reduction will be applied, "mean": the sum of the output will be divided by the number of elements in the output, "sum": the output will be summed.

ignoreIndex - Specifies a target value that is ignored and does not contribute to the input gradient. Note that ignoreIndex is only applicable when the target contains class indices.

Returns:

the cross entropy loss between input logits and target.

where

public static Tensor where(Tensor condition,
 Tensor input,
 Tensor other)

Returns a tensor of elements selected from either input or other, depending on condition.

Parameters:

condition - a boolean tensor. When true (nonzero), yield input, otherwise yield other.

input - value selected at indices where condition is true.

other - value selected at indices where condition is false.

Returns:

the output tensor.

where

public static Tensor where(Tensor condition,
 int input,
 int other)

Returns a tensor of elements selected from either input or other, depending on condition.

Parameters:

condition - a boolean tensor. When true (nonzero), yield input, otherwise yield other.

input - value selected at indices where condition is true.

other - value selected at indices where condition is false.

Returns:

the output tensor.

where

public static Tensor where(Tensor condition,
 double input,
 double other)

Returns a tensor of elements selected from either input or other, depending on condition.

Parameters:

condition - a boolean tensor. When true (nonzero), yield input, otherwise yield other.

input - value selected at indices where condition is true.

other - value selected at indices where condition is false.

Returns:

the output tensor.

matmul

public Tensor matmul(Tensor other)

Returns the matrix product of two tensors.

Parameters:

other - another tensor.

Returns:

the matrix product of two tensors.

outer

public Tensor outer(Tensor other)

Returns the outer product of two tensors.

Parameters:

other - another tensor.

Returns:

the outer product of two tensors.

eq

public Tensor eq(int other)

Computes element-wise equality.

Parameters:

other - the sclar to compare.

Returns:

the output tensor.

eq

public Tensor eq(double other)

Computes element-wise equality.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

eq

public Tensor eq(Tensor other)

Computes element-wise equality.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

ne

public Tensor ne(int other)

Computes element-wise inequality.

Parameters:

other - the sclar to compare.

Returns:

the output tensor.

ne

public Tensor ne(double other)

Computes element-wise inequality.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

ne

public Tensor ne(Tensor other)

Computes element-wise inequality.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

lt

public Tensor lt(double other)

Computes element-wise less-than comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

lt

public Tensor lt(int other)

Computes element-wise less-than comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

lt

public Tensor lt(Tensor other)

Computes element-wise less-than comparison.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

le

public Tensor le(int other)

Computes element-wise less-than-or-equal-to comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

le

public Tensor le(double other)

Computes element-wise less-than-or-equal-to comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

le

public Tensor le(Tensor other)

Computes element-wise less-than-or-equal-to comparison.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

gt

public Tensor gt(int other)

Computes element-wise greater-than comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

gt

public Tensor gt(double other)

Computes element-wise greater-than comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

gt

public Tensor gt(Tensor other)

Computes element-wise greater-than comparison.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

ge

public Tensor ge(int other)

Computes element-wise greater-than-or-equal-to comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

ge

public Tensor ge(double other)

Computes element-wise greater-than-or-equal-to comparison.

Parameters:

other - the scalar to compare.

Returns:

the output tensor.

ge

public Tensor ge(Tensor other)

Computes element-wise greater-than-or-equal-to comparison.

Parameters:

other - the tensor to compare.

Returns:

the output tensor.

sum

public Tensor sum()

Returns the sum of all elements in the tensor.

Returns:

the sum of all elements.

mean

public Tensor mean()

Returns the mean of all elements in the tensor.

Returns:

the mean of all elements.

mean

public Tensor mean(int dim,
 boolean keepDim)

Returns the mean along a dimension in the tensor.

Parameters:

dim - the dimension to reduce.

keepDim - whether the output tensor has dim retained or not.

Returns:

the output tensor.

rsqrt

public Tensor rsqrt()

Returns the reciprocal of the square-root of each of the elements in the tensor.

Returns:

the output tensor.

rsqrt_

public Tensor rsqrt_()

Returns the reciprocal of the square-root of each of the elements in the tensor.

Returns:

this tensor.

exp

public Tensor exp()

Returns the exponential of elements in the tensor.

Returns:

the output tensor.

exp_

public Tensor exp_()

Returns the exponential of elements in the tensor in place.

Returns:

this tensor.

scatterReduce

public Tensor scatterReduce(int dim,
 Tensor index,
 Tensor source,
 String reduce)

Writes all values from the tensor src into this tensor at the indices specified in the index tensor. For each value in src, its output index is specified by its index in src for dimension != dim and by the corresponding value in index for dimension = dim.

This is the reverse operation of the manner described in gather().

Parameters:

dim - the axis along which to index.

index - the indices of elements to scatter, can be either empty or of the same dimensionality as src. When empty, the operation returns self unchanged.

source - the source elements to scatter and reduce.

reduce - the reduction operation to apply for non-unique indices ("sum", "prod", "mean", "amax", or "amin").

Returns:

the output tensor.

scatterReduce_

public Tensor scatterReduce_(int dim,
 Tensor index,
 Tensor source,
 String reduce)

Writes all values from the tensor src into this tensor at the indices specified in the index tensor. For each value in src, its output index is specified by its index in src for dimension != dim and by the corresponding value in index for dimension = dim.

This is the reverse operation of the manner described in gather().

Parameters:

dim - the axis along which to index.

index - the indices of elements to scatter, can be either empty or of the same dimensionality as src. When empty, the operation returns self unchanged.

source - the source elements to scatter and reduce.

reduce - the reduction operation to apply for non-unique indices ("sum", "prod", "mean", "amax", or "amin").

Returns:

this tensor.

gather

public Tensor gather(int dim,
 Tensor index)

Gathers values along an axis specified by dim.

Parameters:

dim - the axis along which to index.

index - the indices of elements to gather.

Returns:

the output tensor.

add

public Tensor add(float other)

Returns A + b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

add_

public Tensor add_(float other)

Returns A += b.

Parameters:

other - a scalar value.

Returns:

this tensor.

add

public Tensor add(double other)

Returns A + b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

add_

public Tensor add_(double other)

Returns A += b.

Parameters:

other - a scalar value.

Returns:

this tensor.

add

public Tensor add(Tensor other)

Returns A + B.

Parameters:

other - another tensor.

Returns:

the output tensor.

add_

public Tensor add_(Tensor other)

Returns A += B.

Parameters:

other - another tensor.

Returns:

this tensor.

add

public Tensor add(Tensor other,
 double alpha)

Returns A + alpha * B.

Parameters:

other - another tensor.

alpha - the scaling factor.

Returns:

the output tensor.

add_

public Tensor add_(Tensor other,
 double alpha)

Returns A += alpha * B.

Parameters:

other - another tensor.

alpha - the scaling factor.

Returns:

this tensor.

sub

public Tensor sub(float other)

Returns A - b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

sub_

public Tensor sub_(float other)

Returns A - b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

sub

public Tensor sub(double other)

Returns A -= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

sub_

public Tensor sub_(double other)

Returns A -= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

sub

public Tensor sub(Tensor other)

Returns A - B.

Parameters:

other - another tensor.

Returns:

the output tensor.

sub_

public Tensor sub_(Tensor other)

Returns A -= B.

Parameters:

other - another tensor.

Returns:

this tensor.

sub

public Tensor sub(Tensor other,
 double alpha)

Returns A - alpha * B.

Parameters:

other - another tensor.

alpha - the scaling factor.

Returns:

the output tensor.

sub_

public Tensor sub_(Tensor other,
 double alpha)

Returns A -= alpha * B.

Parameters:

other - another tensor.

alpha - the scaling factor.

Returns:

this tensor.

mul

public Tensor mul(float other)

Returns A * b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

mul_

public Tensor mul_(float other)

Returns A *= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

mul

public Tensor mul(double other)

Returns A * b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

mul_

public Tensor mul_(double other)

Returns A *= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

mul

public Tensor mul(Tensor other)

Returns A * B element wisely.

Parameters:

other - another tensor.

Returns:

the output tensor.

mul_

public Tensor mul_(Tensor other)

Returns A *= B element wisely.

Parameters:

other - another tensor.

Returns:

this tensor.

div

public Tensor div(float other)

Returns A / b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

div_

public Tensor div_(float other)

Returns A /= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

div

public Tensor div(double other)

Returns A / b.

Parameters:

other - a scalar value.

Returns:

the output tensor.

div_

public Tensor div_(double other)

Returns A /= b.

Parameters:

other - a scalar value.

Returns:

this tensor.

div

public Tensor div(Tensor other)

Returns A / B element wisely.

Parameters:

other - another tensor.

Returns:

the output tensor.

div_

public Tensor div_(Tensor other)

Returns A /= B element wisely.

Parameters:

other - another tensor.

Returns:

this tensor.

pow

public Tensor pow(double exponent)

Returns a new tensor with the power of the elements of input.

Parameters:

exponent - the exponent value.

Returns:

a new tensor with the power of the elements of input.

pow_

public Tensor pow_(double exponent)

Computes the power of the elements of input in place.

Parameters:

exponent - the exponent value.

Returns:

this tensor.

cos

public Tensor cos()

Returns a new tensor with the cosine of the elements of input.

Returns:

a new tensor with the cosine of the elements of input.

cos_

public Tensor cos_()

Computes the cosine of the elements of input in place.

Returns:

this tensor.

sin

public Tensor sin()

Returns a new tensor with the sine of the elements of input.

Returns:

a new tensor with the sine of the elements of input.

sin_

public Tensor sin_()

Computes the sine of the elements of input in place.

Returns:

this tensor.

acos

public Tensor acos()

Returns a new tensor with the arccosine of the elements of input.

Returns:

a new tensor with the arccosine of the elements of input.

acos_

public Tensor acos_()

Computes the arccosine of the elements of input in place.

Returns:

this tensor.

asin

public Tensor asin()

Returns a new tensor with the arcsine of the elements of input.

Returns:

a new tensor with the arcsine of the elements of input.

asin_

public Tensor asin_()

Computes the arcsine of the elements of input in place.

Returns:

this tensor.

isin

public Tensor isin(Tensor other)

Tests if each element of this tensor is in other tensor. Returns a boolean tensor of the same shape.

Parameters:

other - another tensor.

Returns:

a boolean tensor.

all

public boolean all()

Tests if all elements in the tensor are true.

Returns:

the output tensor.

not

public Tensor not()

Returns logical NOT of this tensor.

Returns:

a new tensor of logical not results.

not_

public Tensor not_()

Returns logical NOT of this tensor.

Returns:

a new tensor of logical not results.

and

public Tensor and(Tensor other)

Returns logical AND of two boolean tensors.

Parameters:

other - another tensor.

Returns:

a new tensor of logical and results.

and_

public Tensor and_(Tensor other)

Returns logical AND of two boolean tensors.

Parameters:

other - another tensor.

Returns:

this tensor.

or

public Tensor or(Tensor other)

Returns logical OR of two boolean tensors.

Parameters:

other - another tensor.

Returns:

a new tensor of logical and results.

or_

public Tensor or_(Tensor other)

Returns logical OR of two boolean tensors.

Parameters:

other - another tensor.

Returns:

this tensor.

softmax

public Tensor softmax(int dim)

Rescales a tensor so that the elements lie in the range [0,1] and sum to 1.

Parameters:

dim - the dimension along which softmax will be computed.

Returns:

this tensor.

dropout

public Tensor dropout(double p)

Randomly zeroes some elements of the input tensor with probability p.

Parameters:

p - the probability of an element to be zeroed.

Returns:

a new tensor after random dropouts.

dropout_

public Tensor dropout_(double p)

Randomly zeroes some elements in place with probability p.

Parameters:

p - the probability of an element to be zeroed.

Returns:

this tensor.

newZeros

public Tensor newZeros(long... shape)

Returns a tensor filled with all zeros. The returned Tensor has the data type and device as this tensor.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

newOnes

public Tensor newOnes(long... shape)

Returns a tensor filled with all ones. The returned Tensor has the data type and device as this tensor.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

eye

public static Tensor eye(long shape)

Returns an identity matrix.

Parameters:

shape - the dimension of the resulting matrix.

Returns:

the created tensor.

eye

public static Tensor eye(Tensor.Options options,
 long shape)

Returns an identity matrix.

Parameters:

options - Tensor creation options.

shape - the dimension of the resulting matrix.

Returns:

the created tensor.

full

public static Tensor full(long value,
 long... shape)

Returns a tensor filled with the given value.

Parameters:

value - the value to fill the output tensor with.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

full

public static Tensor full(double value,
 long... shape)

Returns a tensor filled with the given value.

Parameters:

value - the value to fill the output tensor with.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

empty

public static Tensor empty(long... shape)

Returns a tensor with uninitialized data.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

empty

public static Tensor empty(Tensor.Options options,
 long... shape)

Returns a tensor with uninitialized data.

Parameters:

options - Tensor creation options.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

zeros

public static Tensor zeros(long... shape)

Returns a tensor filled with all zeros.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

zeros

public static Tensor zeros(Tensor.Options options,
 long... shape)

Returns a tensor filled with all zeros.

Parameters:

options - Tensor creation options.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

ones

public static Tensor ones(long... shape)

Returns a tensor filled with all ones.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

ones

public static Tensor ones(Tensor.Options options,
 long... shape)

Returns a tensor filled with all ones.

Parameters:

options - Tensor creation options.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

rand

public static Tensor rand(long... shape)

Returns a tensor filled with values drawn from a uniform distribution on [0, 1).

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

rand

public static Tensor rand(Tensor.Options options,
 long... shape)

Returns a tensor filled with values drawn from a uniform distribution on [0, 1).

Parameters:

options - Tensor creation options.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

randn

public static Tensor randn(long... shape)

Returns a tensor filled with values drawn from a unit normal distribution.

Parameters:

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

randn

public static Tensor randn(Tensor.Options options,
 long... shape)

Returns a tensor filled with values drawn from a unit normal distribution.

Parameters:

options - Tensor creation options.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

arange

public static Tensor arange(long start,
 long end,
 long step)

Returns a 1-D tensor of size (end - start) / step with values from the interval [start, end) taken with common difference step beginning from start.

Parameters:

start - the starting value for the set of points.

end - the ending value for the set of points.

step - the gap between each pair of adjacent points.

Returns:

a 1-D tensor.

of

public static Tensor of(boolean[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(byte[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(short[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(int[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(long[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(float[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.

of

public static Tensor of(double[] data,
 long... shape)

Returns a tensor with given data and shape.

Parameters:

data - the initialization data.

shape - the dimensional shape of the resulting tensor.

Returns:

the created tensor.