Applies lower_bound(sorted_search_values, values) along each row.
tf.raw_ops.LowerBound(
sorted_inputs,
values,
out_type=tf.dtypes.int32
,
name=None
)
Each set of rows with the same index in (sorted_inputs, values) is treated
independently. The resulting row is the equivalent of calling
np.searchsorted(sorted_inputs, values, side='left')
.
The result is not a global index to the entire
Tensor
, but rather just the index in the last dimension.
A 2-D example: sorted_sequence = [[0, 3, 9, 9, 10], [1, 2, 3, 4, 5]] values = [[2, 4, 9], [0, 2, 6]]
result = LowerBound(sorted_sequence, values)
result == [[1, 2, 2], [0, 1, 5]]
Args | |
---|---|
sorted_inputs
|
A Tensor . 2-D Tensor where each row is ordered.
|
values
|
A Tensor . Must have the same type as sorted_inputs .
2-D Tensor with the same numbers of rows as sorted_search_values . Contains
the values that will be searched for in sorted_search_values .
|
out_type
|
An optional tf.DType from: tf.int32, tf.int64 . Defaults to tf.int32 .
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor of type out_type .
|