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
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.
Args | |
|---|---|
sparse_indices
|
A Tensor of type int64.
2-D. The indices of the minibatch SparseTensor.
sparse_indices[:, 0] must be ordered values in [0, N).
|
sparse_values
|
A Tensor.
1-D. The values of the minibatch SparseTensor.
|
sparse_shape
|
A Tensor of type int64.
1-D. The shape of the minibatch SparseTensor.
The minibatch size N == sparse_shape[0].
|
container
|
An optional string. Defaults to "".
The container name for the SparseTensorsMap created by this op.
|
shared_name
|
An optional string. Defaults to "".
The shared name for the SparseTensorsMap created by this op.
If blank, the new Operation's unique name is used.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A Tensor of type int64.
|