lzh
28 lines
1.1 KiB
Python
28 lines
1.1 KiB
Python
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class Config(object):
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num_layers = 3 # LSTM层数
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data_path = 'data/' # 诗歌的文本文件存放路径
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pickle_path = 'tang.npz' # 预处理好的二进制文件
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author = None # 只学习某位作者的诗歌
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constrain = None # 长度限制
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category = 'poet.tang' # 类别，唐诗还是宋诗歌(poet.song)
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lr = 1e-3
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weight_decay = 1e-4
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use_gpu = False
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epoch = 50
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batch_size = 16
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maxlen = 125 # 超过这个长度的之后字被丢弃，小于这个长度的在前面补空格
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plot_every = 200 # 每20个batch 可视化一次
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# use_env = True # 是否使用visodm
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env = 'poetry' # visdom env
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max_gen_len = 200 # 生成诗歌最长长度
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debug_file = '/tmp/debugp'
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model_path = "./checkpoints/tang_new.pth" # 预训练模型路径
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prefix_words = '仙路尽头谁为峰？一见无始道成空。' # 不是诗歌的组成部分，用来控制生成诗歌的意境
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start_words = '闲云潭影日悠悠' # 诗歌开始
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acrostic = False # 是否是藏头诗
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model_prefix = 'checkpoints/tang' # 模型保存路径
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embedding_dim = 256
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hidden_dim = 512
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