yhq e1ed85f677
Doc/update mae benchmark (#50)
* update mae benchmark, we fintune the model four times, and chose the highest one as the result. we pretrain and fintune the model only by 8 V100 which is a little different from official one.
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maintain docs

  1. install requirements needed to build docs

    # in easycv root dir
    pip install requirements/docs.txt
    
  2. build docs

    # in easycv/docs dir
    bash build_docs.sh
    
  3. doc string format

    We adopt the google style docstring format as the standard, please refer to the following documents.

    1. Google Python style guide docstring link
    2. Google docstring example link
    3. sampletorch.nn.modules.conv link
    4. Transformer as an example
    class Transformer(base.Layer):
        """
            Transformer model from ``Attention Is All You Need``,
            Original paper: https://arxiv.org/abs/1706.03762
    
            Args:
                num_token (int): vocab size.
                num_layer (int): num of layer.
                num_head (int): num of attention heads.
                embedding_dim (int): embedding dimension.
                attention_head_dim (int): attention head dimension.
                feed_forward_dim (int): feed forward dimension.
                initializer: initializer type.
                activation: activation function.
                dropout (float): dropout rate (0.0 to 1.0).
                attention_dropout (float): dropout rate for attention layer.
    
            Returns: None
        """