tensorflow:: ops:: SparseSplit

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.

Public attributes

Operation operation

::tensorflow::OutputList output_indices

::tensorflow::OutputList output_shape

::tensorflow::OutputList output_values

Public functions

 SparseSplit(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input split_dim,
  ::tensorflow::Input indices,
  ::tensorflow::Input values,
  ::tensorflow::Input shape,
  int64 num_split
)