tf.sparse_split(keyword_required=KeywordRequired(), sp_input=None, num_split=None, axis=None, name=None, split_dim=None)

tf.sparse_split(keyword_required=KeywordRequired(), sp_input=None, num_split=None, axis=None, name=None, split_dim=None)

See the guide: Sparse Tensors > Manipulation

Split a SparseTensor into num_split tensors along axis.

If the sp_input.dense_shape[axis] is not an integer multiple of num_split each slice starting from 0:shape[axis] % num_split gets extra one dimension. For example, if axis = 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] =
[    a ]
[b c   ]

output_tensor[1] =
[ d e  ]
[      ]

Args:

• keyword_required: Python 2 standin for * (temporary for argument reorder)
• sp_input: The SparseTensor to split.
• num_split: A Python integer. The number of ways to split.
• axis: A 0-D int32 Tensor. The dimension along which to split.
• name: A name for the operation (optional).
• split_dim: Deprecated old name for axis.

Returns:

num_split SparseTensor objects resulting from splitting value.

Raises:

• TypeError: If sp_input is not a SparseTensor.
• ValueError: If the deprecated split_dim and axis are both non None.

Defined in tensorflow/python/ops/sparse_ops.py.