List of articles

• Preface
• label turn one-hot
• one-hot turn label

Preface

Sometimes you need to label, For example, the discrete action space of reinforcement learning , Output action index ; Sometimes you need to one-hot, For example, training data or the action of inputting the previous state , Simple mutual transformation is still important .

label turn one-hot

adopt np.eye(action_dims)[actions] Quickly generate ：

>>> import numpy as np
>>> label = [1,2,2,3]
>>> np.eye(4)[label]
array([[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])

one-hot turn label

numpy Can pass np.argmax(onehot, 1) Realization ,pytorch Can pass torch.topk(one_hot, 1)[1].squeeze(1) Realization ：

>>> import torch
>>> onehot
array([[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
>>> np.argmax(onehot,1)
array([1, 2, 2, 3], dtype=int64)
>>> torch.topk(torch.tensor(onehot), 1)[1].squeeze(1)
tensor([1, 2, 2, 3])