tensorflow::
ops::
SparseSplit
#include <sparse_ops.h>
Split a
SparseTensor
into
num_split
tensors along one dimension.
Summary
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:
- scope: A Scope object
-
split_dim: 0-D. The dimension along which to split. Must be in the range
[0, rank(shape))
. - indices: 2-D tensor represents the indices of the sparse tensor.
- values: 1-D tensor represents the values of the sparse tensor.
- shape: 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: The number of ways to split.
Returns:
-
OutputList
output_indices -
OutputList
output_values: A list of 1-D tensors represents the values of the output sparse tensors. -
OutputList
output_shape: A list of 1-D tensors represents the shape of the output sparse tensors.
Constructors and Destructors |
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SparseSplit
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
split_dim, ::
tensorflow::Input
indices, ::
tensorflow::Input
values, ::
tensorflow::Input
shape, int64 num_split)
|
Public attributes |
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operation
|
|
output_indices
|
|
output_shape
|
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output_values
|
Public attributes
Public functions
SparseSplit
SparseSplit( const ::tensorflow::Scope & scope, ::tensorflow::Input split_dim, ::tensorflow::Input indices, ::tensorflow::Input values, ::tensorflow::Input shape, int64 num_split )