tensorflow::
#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 Tensorwhich may have the same shape ascondition. Ifconditionis rank 1,xmay have higher rank, but its first dimension must match the size ofcondition.
- y: = A Tensorwith 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
operation
Operation operation
output
::tensorflow::Output output
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