mindspore.ops.OneHot
- class mindspore.ops.OneHot(axis=- 1)[source]
Computes a one-hot tensor.
The locations represented by indices in indices take value on_value, while all other locations take value off_value.
Note
If the input indices is rank N, the output will have rank N+1. The new axis is created at dimension axis. On Ascend, if on_value is Int64 dtype, indices must be Int64 dtype, and the value for on_value and off_value can only be 1 and 0.
- Parameters
axis (int) – Position to insert the value. e.g. If shape of indices is \((N, C)\), and axis is -1, the output shape will be \((N, C, D)\), If axis is 0, the output shape will be \((D, N, C)\). Default:
-1
.
- Inputs:
indices (Tensor) - A tensor of indices. Tensor of shape \((X_0, \ldots, X_n)\). Data type must be int32 or int64.
depth (Union[int, Tensor]) - A scalar defining the depth of the one-hot dimension.
on_value (Tensor) - A value to fill in output when indices[j] = i.
off_value (Tensor) - A value to fill in output when indices[j] != i. It has the same data type as on_value.
- Outputs:
Tensor, one-hot tensor. Tensor of shape \((X_0, \ldots, X_{axis}, \text{depth} ,X_{axis+1}, \ldots, X_n)\).
- Raises
TypeError – If axis or depth is not an int.
TypeError – If dtype of on_value is not int32, int64, float16 or float32.
TypeError – If dtype of indices is not int32 or int64.
TypeError – If indices, on_value or off_value is not a Tensor.
ValueError – If axis is not in range [-1, len(indices_shape)].
ValueError – If depth is less than 0.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> indices = Tensor(np.array([0, 1, 2]), mindspore.int32) >>> depth, on_value, off_value = 3, Tensor(1.0, mindspore.float32), Tensor(0.0, mindspore.float32) >>> onehot = ops.OneHot() >>> output = onehot(indices, depth, on_value, off_value) >>> print(output) [[1. 0. 0.] [0. 1. 0.] [0. 0. 1.]]