Add an N
-minibatch SparseTensor
to a SparseTensorsMap
, return N
handles.
tf.raw_ops.AddManySparseToTensorsMap(
sparse_indices,
sparse_values,
sparse_shape,
container='',
shared_name='',
name=None
)
A SparseTensor
of rank R
is represented by three tensors: sparse_indices
,
sparse_values
, and sparse_shape
, where
sparse_indices.shape[1] == sparse_shape.shape[0] == R
An N
-minibatch of SparseTensor
objects is represented as a SparseTensor
having a first sparse_indices
column taking values between [0, N)
, where
the minibatch size N == sparse_shape[0]
.
The input SparseTensor
must have rank R
greater than 1, and the first
dimension is treated as the minibatch dimension. Elements of the SparseTensor
must be sorted in increasing order of this first dimension. The stored
SparseTensor
objects pointed to by each row of the output sparse_handles
will have rank R-1
.
The SparseTensor
values can then be read out as part of a minibatch by passing
the given keys as vector elements to TakeManySparseFromTensorsMap
. To ensure
the correct SparseTensorsMap
is accessed, ensure that the same
container
and shared_name
are passed to that Op. If no shared_name
is provided here, instead use the name of the Operation created by calling
AddManySparseToTensorsMap
as the shared_name
passed to
TakeManySparseFromTensorsMap
. Ensure the Operations are colocated.
Returns | |
---|---|
A Tensor of type int64 .
|