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A sparse representation of a set of tensor slices at given indices.
tf.IndexedSlices(
values, indices, dense_shape=None
)
This class is a simple wrapper for a pair of Tensor
objects:
values
: ATensor
of any dtype with shape[D0, D1, ..., Dn]
.indices
: A 1D integerTensor
with shape[D0]
.
An IndexedSlices
is typically used to represent a subset of a larger
tensor dense
of shape [LARGE0, D1, .. , DN]
where LARGE0 >> D0
.
The values in indices
are the indices in the first dimension of
the slices that have been extracted from the larger tensor.
The dense tensor dense
represented by an IndexedSlices
slices
has
dense[slices.indices[i], :, :, :, ...] = slices.values[i, :, :, :, ...]
The IndexedSlices
class is used principally in the definition of
gradients for operations that have sparse gradients
(e.g. tf.gather
).
v = tf.Variable([[0.,1, 2], [2, 3, 4], [4, 5, 6], [6, 7, 8]])
with tf.GradientTape() as tape:
r = tf.gather(v, [1,3])
index_slices = tape.gradient(r,v)
index_slices
<...IndexedSlices object ...>
index_slices.indices.numpy()
array([1, 3], dtype=int32)
index_slices.values.numpy()
array([[1., 1., 1.],
[1., 1., 1.]], dtype=float32)
Contrast this representation with
tf.sparse.SparseTensor
,
which uses multidimensional indices and scalar values.
Attributes  

dense_shape

A 1D Tensor containing the shape of the corresponding dense tensor.

device

The name of the device on which values will be produced, or None .

dtype

The DType of elements in this tensor.

graph

The Graph that contains the values, indices, and shape tensors.

indices

A 1D Tensor containing the indices of the slices.

name

The name of this IndexedSlices .

op

The Operation that produces values as an output.

shape

Gets the tf.TensorShape representing the shape of the dense tensor.

values

A Tensor containing the values of the slices.

Methods
consumers
consumers()
__neg__
__neg__()