Selects elements from x
or y
, depending on condition
.
tf.raw_ops.Select(
condition, x, y, name=None
)
The x
, and y
tensors must all have the same shape, and the
output will also have that shape.
The condition
tensor must be a scalar if x
and y
are scalars.
If x
and y
are vectors or higher rank, then condition
must be either a
scalar, a vector with size matching the first dimension of x
, or must have
the same shape as x
.
The condition
tensor acts as a mask that chooses, based on the value at each
element, whether the corresponding element / row in the output should be
taken from x
(if true) or y
(if false).
If condition
is a vector and x
and y
are higher rank matrices, then
it chooses which row (outer dimension) to copy from x
and y
.
If condition
has the same shape as x
and y
, then it chooses which
element to copy from x
and y
.
For example:
# 'condition' tensor is [[True, False]
# [False, True]]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) # => [[1, 6], [7, 4]]
# 'condition' tensor is [True, False]
# 't' is [[1, 2],
# [3, 4]]
# 'e' is [[5, 6],
# [7, 8]]
select(condition, t, e) ==> [[1, 2],
[7, 8]]
Returns | |
---|---|
A Tensor . Has the same type as t .
|