#include <math_ops.h>
Selects elements from x or y, depending on condition.
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]]
Arguments:
Tensor which may have the same shape as condition. If condition is rank 1, x may have higher rank, but its first dimension must match the size of condition.Tensor with the same type and shape as x.Returns:
| Constructors and Destructors | |
|---|---|
Where3(const ::tensorflow::Scope & scope, ::tensorflow::Input condition, ::tensorflow::Input x, ::tensorflow::Input y) |
| Public attributes | |
|---|---|
output | |
| Public functions | |
|---|---|
node() const | ::tensorflow::Node * |
operator::tensorflow::Input() const | |
operator::tensorflow::Output() const | |
::tensorflow::Output output
Where3( const ::tensorflow::Scope & scope, ::tensorflow::Input condition, ::tensorflow::Input x, ::tensorflow::Input y )
::tensorflow::Node * node() const
operator::tensorflow::Input() const
operator::tensorflow::Output() const
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/where3.html