tensorflow::
ops::
Where3
#include <math_ops.h>
Selects elements from
x
or
y
, depending on
condition
.
Summary
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]]
Args:
- scope: A Scope object
-
x: = A
Tensor
which may have the same shape ascondition
. Ifcondition
is rank 1,x
may have higher rank, but its first dimension must match the size ofcondition
. -
y: = A
Tensor
with the same type and shape asx
.
Returns:
Constructors and Destructors |
|
---|---|
Where3
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
condition, ::
tensorflow::Input
x, ::
tensorflow::Input
y)
|
Public attributes |
|
---|---|
operation
|
|
output
|
Public functions |
|
---|---|
node
() const
|
::tensorflow::Node *
|
operator::tensorflow::Input
() const
|
|
operator::tensorflow::Output
() const
|
|
Public attributes
Public functions
Where3
Where3( const ::tensorflow::Scope & scope, ::tensorflow::Input condition, ::tensorflow::Input x, ::tensorflow::Input y )
node
::tensorflow::Node * node() const
operator::tensorflow::Input
operator::tensorflow::Input() const
operator::tensorflow::Output
operator::tensorflow::Output() const