original_docstring: Embedding labels to one-hot form.
  
      Args:
        labels: (LongTensor) class labels, sized [N,].
        num_classes: (int) number of classes.
  
      Returns:
        (tensor) encoded labels, sized [N,#classes].
      
docstring: Embedding labels to one-hot form.
docstring_tokens: Embedding labels to one - hot form .
code: def one_hot_embedding(labels, num_classes):
      '''Embedding labels to one-hot form.
  
      Args:
        labels: (LongTensor) class labels, sized [N,].
        num_classes: (int) number of classes.
  
      Returns:
        (tensor) encoded labels, sized [N,#classes].
      '''
      # import pdb; pdb.set_trace()
      y = torch.eye(num_classes)  # [D,D]
      return y[labels.long()]     # [N,D]
code_tokens: def one_hot_embedding ( labels , num_classes ) : y = torch . eye ( num_classes ) return y [ labels . long ( ) ]
short_docstring: Embedding labels to one-hot form.
short_docstring_tokens: Embedding labels to one - hot form .
comment: '''Embedding labels to one-hot form.
  
      Args:
        labels: (LongTensor) class labels, sized [N,].
        num_classes: (int) number of classes.
  
      Returns:
        (tensor) encoded labels, sized [N,#classes].
      '''$SEP$# import pdb; pdb.set_trace()$SEP$# [D,D]$SEP$# [N,D]