tf.sparse.SparseTensor

Represents a sparse tensor.

Used in the notebooks

Used in the guide Used in the tutorials

TensorFlow represents a sparse tensor as three separate dense tensors: indices, values, and dense_shape. In Python, the three tensors are collected into a SparseTensor class for ease of use. If you have separate indices, values, and dense_shape tensors, wrap them in a SparseTensor object before passing to the ops below.

Concretely, the sparse tensor SparseTensor(indices, values, dense_shape) comprises the following components, where N and ndims are the number of values and number of dimensions in the SparseTensor, respectively:

  • indices: A 2-D int64 tensor of shape [N, ndims], which specifies the indices of the elements in the sparse tensor that contain nonzero values (elements are zero-indexed). For example, indices=[[1,3], [2,4]] specifies that the elements with indexes of [1,3] and [2,4] have nonzero values.

  • values: A 1-D tensor of any type and shape [N], which supplies the values for each element in indices. For example, given indices=[[1,3], [2,4]], the parameter values=[18, 3.6] specifies that element [1,3] of the sparse tensor has a value of 18, and element [2,4] of the tensor has a value of 3.6.

  • dense_shape: A 1-D int64 tensor of shape [ndims], which specifies the dense_shape of the sparse tensor. Takes a list indicating the number of elements in each dimension. For example, dense_shape=[3,6] specifies a two-dimensional 3x6 tensor, dense_shape=[2,3,4] specifies a three-dimensional 2x3x4 tensor, and dense_shape=[9] specifies a one-dimensional tensor with 9 elements.

The corresponding dense tensor satisfies:

dense.shape = dense_shape
dense[tuple(indices[i])] = values[i]

By convention, indices should be sorted in row-major order (or equivalently lexicographic order on the tuples indices[i]). This is not enforced when SparseTensor objects are constructed, but most ops assume correct ordering. If the ordering of sparse tensor st is wrong, a fixed version can be obtained by calling tf.sparse.reorder(st).

Example: The sparse tensor

SparseTensor(indices=[[0, 0], [1, 2]], values=[1, 2], dense_shape=[3, 4])

represents the dense tensor

[[1, 0, 0, 0]
 [0, 0, 2, 0]
 [0, 0, 0, 0]]

indices A 2-D int64 tensor of shape [N, ndims].
values A 1-D tensor of any type and shape [N].
dense_shape A 1-D int64 tensor of shape [ndims].

ValueError When building an eager SparseTensor if dense_shape is unknown or contains unknown elements (None or -1).

dense_shape A 1-D Tensor of int64 representing the shape of the dense tensor.
dtype The DType of elements in this tensor.
graph The Graph that contains the index, value, and dense_shape tensors.
indices The indices of non-zero values in the represented dense tensor.
op The Operation that produces values as an output.
shape Get the TensorShape representing the shape of the dense tensor.
values The non-zero values in the represented dense tensor.

Methods

consumers

View source

eval

View source

Evaluates this sparse tensor in a Session.

Calling this method will execute all preceding operations that produce the inputs needed for the operation that produces this tensor.

Args
feed_dict A dictionary that maps Tensor objects to feed values. See tf.Session.run for a description of the valid feed values.
session (Optional.) The Session to be used to evaluate this sparse tensor. If none, the default session will be used.

Returns
A SparseTensorValue object.

from_value

View source

get_shape

View source

Get the TensorShape representing the shape of the dense tensor.

Returns
A TensorShape object.

__div__

View source

Component-wise divides a SparseTensor by a dense Tensor.

Limitation: this Op only broadcasts the dense side to the sparse side, but not the other direction.

Args
sp_indices A Tensor of type int64. 2-D. N x R matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.
sp_values A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, complex64, int64, qint8, quint8, qint32, bfloat16, uint16, complex128, half, uint32, uint64. 1-D. N non-empty values corresponding to sp_indices.
sp_shape A Tensor of type int64. 1-D. Shape of the input SparseTensor.
dense A Tensor. Must have the same type as sp_values. R-D. The dense Tensor operand.
name A name for the operation (optional).

Returns
A Tensor. Has the same type as sp_values.