Returns a one-hot tensor.
tf.raw_ops.OneHot(
indices, depth, on_value, off_value, axis=-1, name=None
)
The locations represented by indices in indices
take value on_value
,
while all other locations take value off_value
.
If the input indices
is rank N
, the output will have rank N+1
,
The new axis is created at dimension axis
(default: the new axis is
appended at the end).
If indices
is a scalar the output shape will be a vector of length depth
.
If indices
is a vector of length features
, the output shape will be:
features x depth if axis == -1
depth x features if axis == 0
If indices
is a matrix (batch) with shape [batch, features]
,
the output shape will be:
batch x features x depth if axis == -1
batch x depth x features if axis == 1
depth x batch x features if axis == 0
Examples
Suppose that
indices = [0, 2, -1, 1]
depth = 3
on_value = 5.0
off_value = 0.0
axis = -1
Then output is [4 x 3]
:
output =
[5.0 0.0 0.0] // one_hot(0)
[0.0 0.0 5.0] // one_hot(2)
[0.0 0.0 0.0] // one_hot(-1)
[0.0 5.0 0.0] // one_hot(1)
Suppose that
indices = [0, 2, -1, 1]
depth = 3
on_value = 0.0
off_value = 3.0
axis = 0
Then output is [3 x 4]
:
output =
[0.0 3.0 3.0 3.0]
[3.0 3.0 3.0 0.0]
[3.0 3.0 3.0 3.0]
[3.0 0.0 3.0 3.0]
// ^ one_hot(0)
// ^ one_hot(2)
// ^ one_hot(-1)
// ^ one_hot(1)
Suppose that
indices = [[0, 2], [1, -1]]
depth = 3
on_value = 1.0
off_value = 0.0
axis = -1
Then output is [2 x 2 x 3]
:
output =
[
[1.0, 0.0, 0.0] // one_hot(0)
[0.0, 0.0, 1.0] // one_hot(2)
][
[0.0, 1.0, 0.0] // one_hot(1)
[0.0, 0.0, 0.0] // one_hot(-1)
]
Returns | |
---|---|
A Tensor . Has the same type as on_value .
|