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.
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]]
Returns | |
|---|---|
A Tensor. Has the same type as t.
|