Tensor

public interface Tensor

Known Indirect Subclasses RawTensor, TBfloat16, TBool, TFloat16, TFloat32, TFloat64, TFloating, TInt32, TInt64, TIntegral, TNumber, TString, TType, TUint8 RawTensor A tensor which memory has not been mapped to a data space directly accessible from the JVM.  TBfloat16 Brain 16-bit float tensor type.  TBool Boolean tensor type.  TFloat16 IEEE-754 half-precision 16-bit float tensor type.  TFloat32 IEEE-754 single-precision 32-bit float tensor type.  TFloat64 IEEE-754 double-precision 64-bit float tensor type.  TFloating Common interface for all floating point tensors.  TInt32 32-bit signed integer tensor type.  TInt64 64-bit signed integer tensor type.  TIntegral Common interface for all integral numeric tensors.  TNumber Common interface for all numeric tensors.  TString String type.  TType Common interface for all typed tensors.  TUint8 8-bit unsigned integer tensor type.

A statically typed multi-dimensional array.

There are two categories of tensors in TensorFlow Java: typed tensors and raw tensors. The former maps the tensor native memory to an n-dimensional typed data space, allowing direct I/O operations from the JVM, while the latter is only a reference to a native tensor allowing basic operations and flat data access.

WARNING: Resources consumed by the Tensor object must be explicitly freed by invoking the close() method when the object is no longer needed. For example, using a try-with-resources block:

try (Tensor t = Tensor.of(...)) {
   doSomethingWith(t);
 
 }

Instances of a Tensor are not thread-safe.

Public Methods

abstract RawTensor	asRawTensor() Returns a raw (untyped) representation of this tensor
abstract void	close() Release resources associated with the Tensor.
abstract DataType	dataType() Returns the DataType of elements stored in the tensor.
abstract long	numBytes() Returns the size, in bytes, of the tensor data.
abstract static <T extends TType> T	of(Class<T> type, Shape shape, long size, Consumer<T> dataInitializer) Allocates a tensor of a given datatype, shape and size.
abstract static <T extends TType> T	of(Class<T> type, Shape shape) Allocates a tensor of a given datatype and shape.
abstract static <T extends TType> T	of(Class<T> type, Shape shape, long size) Allocates a tensor of a given datatype, shape and size.
abstract static <T extends TType> T	of(Class<T> type, Shape shape, Consumer<T> dataInitializer) Allocates and initialize a tensor of a given datatype and shape.
abstract static <T extends TType> T	of(Class<T> type, Shape shape, ByteDataBuffer rawData) Creates a Tensor of any type from the raw data provided by the given buffer.
abstract Shape	shape() Returns the shape of the tensor.

Inherited Methods

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

From interface java.lang.AutoCloseable

abstract void

close()

Public Methods

public abstract RawTensor asRawTensor ()

Returns a raw (untyped) representation of this tensor

public abstract void close ()

Release resources associated with the Tensor.

WARNING:This must be invoked for all tensors that were not been produced by an eager operation or memory will be leaked.

The Tensor object is no longer usable after close returns.

public abstract DataType dataType ()

Returns the DataType of elements stored in the tensor.

public abstract long numBytes ()

Returns the size, in bytes, of the tensor data.

public static abstract T of (Class<T> type, Shape shape, long size, Consumer<T> dataInitializer)

Allocates a tensor of a given datatype, shape and size.

This method is identical to of(Class, Shape, Consumer), except that the final size for the tensor can be explicitly set instead of being computed from the datatype and shape.

This could be useful for tensor types that stores data but also metadata in the tensor memory, such as the lookup table in a tensor of strings.

Parameters

type	the tensor type class
shape	shape of the tensor
size	size in bytes of the tensor or -1 to compute the size from the shape
dataInitializer	method receiving accessor to the allocated tensor data for initialization

Returns

• an allocated and initialized tensor

Throws

IllegalArgumentException	if size is smaller than the minimum space required to store the tensor data
IllegalArgumentException	if size is set to -1 but elements of the given type are of variable length (e.g. strings)
IllegalArgumentException	if shape is totally or partially unknown
IllegalStateException	if tensor failed to be allocated

See Also

• of(Class, Shape, long, Consumer)

public static abstract T of (Class<T> type, Shape shape)

Allocates a tensor of a given datatype and shape.

The amount of memory to allocate is derived from the datatype and the shape of the tensor, and is left uninitialized.

Parameters

type	the tensor type class
shape	shape of the tensor

Returns

• an allocated but uninitialized tensor

Throws

IllegalArgumentException	if elements of the given type are of variable length (e.g. strings)
IllegalArgumentException	if shape is totally or partially unknown
IllegalStateException	if tensor failed to be allocated

public static abstract T of (Class<T> type, Shape shape, long size)

Allocates a tensor of a given datatype, shape and size.

This method is identical to of(Class, Shape), except that the final size of the tensor can be explicitly set instead of computing it from the datatype and shape, which could be larger than the actual space required to store the data but not smaller.

Parameters

type	the tensor type class
shape	shape of the tensor
size	size in bytes of the tensor or -1 to compute the size from the shape

Returns

• an allocated but uninitialized tensor

Throws

IllegalArgumentException	if size is smaller than the minimum space required to store the tensor data
IllegalArgumentException	if size is set to -1 but elements of the given type are of variable length (e.g. strings)
IllegalArgumentException	if shape is totally or partially unknown
IllegalStateException	if tensor failed to be allocated

See Also

• of(Class, Shape)

public static abstract T of (Class<T> type, Shape shape, Consumer<T> dataInitializer)

Allocates and initialize a tensor of a given datatype and shape.

The amount of memory to allocate is derived from the datatype and the shape of the tensor. Tensor data is initialized by calling the dataInitializer, which receives in argument the value returned by ERROR(/#data()) on the allocated tensor. For example:

FloatNdArray data = ...
 try (TFloat32 t = Tensor.of(TFloat32.class, Shape.of(2, 2), data::copyTo)) {
   ...
 
 }

If dataInitializer fails and throws an exception, the allocated tensor will be automatically released before rethrowing the same exception.

Parameters

type	the tensor type class
shape	shape of the tensor
dataInitializer	method receiving accessor to the allocated tensor data for initialization

Returns

• an allocated and initialized tensor

Throws

IllegalArgumentException	if elements of the given type are of variable length (e.g. strings)
IllegalArgumentException	if shape is totally or partially unknown
IllegalStateException	if tensor failed to be allocated

public static abstract T of (Class<T> type, Shape shape, ByteDataBuffer rawData)

Creates a Tensor of any type from the raw data provided by the given buffer.

Data must have been encoded into data as per the specification of the TensorFlow C API.

Parameters

type	the tensor type class
shape	the tensor shape.
rawData	a buffer containing the tensor raw data.

Throws

IllegalArgumentException	if rawData is not large enough to contain the tensor data
IllegalArgumentException	if shape is totally or partially unknown
IllegalStateException	if tensor failed to be allocated with the given parameters

public abstract Shape shape ()

Returns the shape of the tensor.