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TensorFlow 1 version
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View source on GitHub
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Fills empty rows in the input 2-D SparseTensor with a default value.
tf.sparse.fill_empty_rows(
sp_input, default_value, name=None
)
This op adds entries with the specified default_value at index
[row, 0] for any row in the input that does not already have a value.
For example, suppose sp_input has shape [5, 6] and non-empty values:
[0, 1]: a
[0, 3]: b
[2, 0]: c
[3, 1]: d
Rows 1 and 4 are empty, so the output will be of shape [5, 6] with values:
[0, 1]: a
[0, 3]: b
[1, 0]: default_value
[2, 0]: c
[3, 1]: d
[4, 0]: default_value
Note that the input may have empty columns at the end, with no effect on this op.
The output SparseTensor will be in row-major order and will have the
same shape as the input.
This op also returns an indicator vector such that
empty_row_indicator[i] = True iff row i was an empty row.
Args | |
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sp_input
|
A SparseTensor with shape [N, M].
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default_value
|
The value to fill for empty rows, with the same type as
sp_input.
|
name
|
A name prefix for the returned tensors (optional) |
Returns | |
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sp_ordered_output
|
A SparseTensor with shape [N, M], and with all empty
rows filled in with default_value.
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empty_row_indicator
|
A bool vector of length N indicating whether each
input row was empty.
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Raises | |
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TypeError
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If sp_input is not a SparseTensor.
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