org.tensorflow.types

Interface TInt32

All Superinterfaces:

AutoCloseable, org.tensorflow.ndarray.IntNdArray, org.tensorflow.ndarray.NdArray<Integer>, org.tensorflow.ndarray.Shaped, Tensor, TIntegral, TNumber, TType

@TensorType(dataType=DT_INT32,
            byteSize=4,
            mapperClass=TInt32Mapper.class)
public interface TInt32
extends org.tensorflow.ndarray.IntNdArray, TIntegral

32-bit signed integer tensor type.

Method Summary

Modifier and Type	Method and Description
static TInt32	scalarOf(int value) Allocates a new tensor for storing a single int value.
static TInt32	tensorOf(org.tensorflow.ndarray.NdArray<Integer> src) Allocates a new tensor which is a copy of a given array of ints.
static TInt32	tensorOf(org.tensorflow.ndarray.Shape shape) Allocates a new tensor of the given shape.
static TInt32	tensorOf(org.tensorflow.ndarray.Shape shape, Consumer<TInt32> dataInit) Allocates a new tensor of the given shape and initialize its data.
static TInt32	tensorOf(org.tensorflow.ndarray.Shape shape, org.tensorflow.ndarray.buffer.IntDataBuffer data) Allocates a new tensor of the given shape, initialized with the provided data.
static TInt32	vectorOf(int... values) Allocates a new tensor for storing a vector of ints.

Methods inherited from interface org.tensorflow.ndarray.IntNdArray

copyTo, elements, get, getInt, getObject, read, read, scalars, set, setInt, setObject, slice, write, write

Methods inherited from interface org.tensorflow.ndarray.NdArray

equals

Methods inherited from interface org.tensorflow.types.family.TType

close, dataType, numBytes, type

Methods inherited from interface org.tensorflow.Tensor

asRawTensor, of, of, of, of, of

Methods inherited from interface org.tensorflow.ndarray.Shaped

rank, size

Method Detail

scalarOf

static TInt32 scalarOf(int value)

Allocates a new tensor for storing a single int value.

Parameters:

value - int to store in the new tensor

Returns:

the new tensor

vectorOf

static TInt32 vectorOf(int... values)

Allocates a new tensor for storing a vector of ints.

Parameters:

values - ints to store in the new tensor

Returns:

the new tensor

Throws:

IllegalArgumentException - if no values are provided

tensorOf

static TInt32 tensorOf(org.tensorflow.ndarray.NdArray<Integer> src)

Allocates a new tensor which is a copy of a given array of ints.

The tensor will have the same shape as the source array and its data will be copied.

Parameters:

src - the source array giving the shape and data to the new tensor

Returns:

the new tensor

tensorOf

static TInt32 tensorOf(org.tensorflow.ndarray.Shape shape)

Allocates a new tensor of the given shape.

Parameters:

shape - shape of the tensor to allocate

Returns:

the new tensor

tensorOf

static TInt32 tensorOf(org.tensorflow.ndarray.Shape shape,
                       org.tensorflow.ndarray.buffer.IntDataBuffer data)

Allocates a new tensor of the given shape, initialized with the provided data.

Parameters:

shape - shape of the tensor to allocate

data - buffer of ints to initialize the tensor with

Returns:

the new tensor

tensorOf

static TInt32 tensorOf(org.tensorflow.ndarray.Shape shape,
                       Consumer<TInt32> dataInit)

Allocates a new tensor of the given shape and initialize its data.

Parameters:

shape - shape of the tensor to allocate

dataInit - tensor data initializer

Returns:

the new tensor