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`

.

# '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 | |
---|---|

`condition` | A `Tensor` of type `bool` . |

`x` | A `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` . |

`y` | A `Tensor` with the same type and shape as `x` . |

`name` | A name for the operation (optional). |

Returns | |
---|---|

A `Tensor` . Has the same type as `t` . |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/Select