/TensorFlow 2.4


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]]

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).
A Tensor. Has the same type as t.

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Code samples licensed under the Apache 2.0 License.