Split a SparseTensor
into num_split
tensors along one dimension.
tf.raw_ops.SparseSplit(
split_dim, indices, values, shape, num_split, name=None
)
If the shape[split_dim]
is not an integer multiple of num_split
. Slices
[0 : shape[split_dim] % num_split]
gets one extra dimension.
For example, if split_dim = 1
and num_split = 2
and the input is
input_tensor = shape = [2, 7]
[ a d e ]
[b c ]
Graphically the output tensors are:
output_tensor[0] = shape = [2, 4]
[ a ]
[b c ]
output_tensor[1] = shape = [2, 3]
[ d e ]
[ ]
Args |
split_dim
|
A Tensor of type int64 .
0-D. The dimension along which to split. Must be in the range
[0, rank(shape)) .
|
indices
|
A Tensor of type int64 .
2-D tensor represents the indices of the sparse tensor.
|
values
|
A Tensor . 1-D tensor represents the values of the sparse tensor.
|
shape
|
A Tensor of type int64 .
1-D. tensor represents the shape of the sparse tensor.
output indices: A list of 1-D tensors represents the indices of the output
sparse tensors.
|
num_split
|
An int that is >= 1 . The number of ways to split.
|
name
|
A name for the operation (optional).
|
Returns |
A tuple of Tensor objects (output_indices, output_values, output_shape).
|
output_indices
|
A list of num_split Tensor objects with type int64 .
|
output_values
|
A list of num_split Tensor objects with the same type as values .
|
output_shape
|
A list of num_split Tensor objects with type int64 .
|