Warning: This API is deprecated and will be removed in a future version of TensorFlow after the replacement is stable.

Shape

public final class Shape

The possibly partially known shape of a tensor produced by an operation.

Public Methods

 boolean equals(Object obj) int hashCode() static Shape make(long firstDimensionSize, long... otherDimensionSizes) Create a Shape representing an N-dimensional value. int numDimensions() Number of dimensions represented by this shape. static Shape scalar() Create a Shape representing a scalar value. long size(int i) The size of the i-th dimension. String toString() Succinct description of the shape meant for debugging. static Shape unknown() Create a Shape representing an unknown number of dimensions.

Public Methods

public static Shape make(long firstDimensionSize, long... otherDimensionSizes)

Create a Shape representing an N-dimensional value.

Creates a Shape representing an N-dimensional value (N being at least 1), with the provided size for each dimension. A -1 indicates that the size of the corresponding dimension is unknown. For example:

``````// A 2-element vector.
Shape vector = Shape.create(2);

// A 2x3 matrix.
Shape matrix = Shape.create(2, 3);

// A matrix with 4 columns but an unknown number of rows.
// This is typically used to indicate the shape of tensors that represent
// a variable-sized batch of values. The Shape below might represent a
// variable-sized batch of 4-element vectors.
Shape batch = Shape.create(-1, 4);
``````

public int numDimensions()

Number of dimensions represented by this shape.

Returns
• -1 if the number of dimensions is unknown, 0 if the shape represents a scalar, 1 for a vector, 2 for a matrix etc.

public static Shape scalar()

Create a Shape representing a scalar value.

public long size(int i)

The size of the i-th dimension.

Returns
• The size of the requested dimension or -1 if it is unknown.

public String toString()

Succinct description of the shape meant for debugging.

public static Shape unknown()

Create a Shape representing an unknown number of dimensions.

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