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.
 |