description: Returns a one-hot tensor.

robots: noindex

tf.raw_ops.OneHot

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) ]