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.
|