output_size = self.config.label_sizewithtf.variable_scope('Composition'):### YOUR CODE HEREembedding = tf.get_variable("embedding", shape=(vocab_size, embed_size)) W1 = tf.get_variable("W1", shape=(2* embed_size, embed_size)) b1 = tf.get_variable("b1", shape=(1, embed_size))...
# 需要导入模块: import vocab [as 别名]# 或者: from vocab importVocab[as 别名]defload_data(small=True, char_based=False, batch_size=20, vocab_size=10000, history_len=5, max_tokens=50, null_mark=False):vocab_path = os.path.join(resource_dir,"ptb.train.txt") valid_path = os.path....
0.693433 val loss 0.69323194 steps: 490, losses: 0.693890 val loss 0.69317454 训练模型: def lstm(): input = keras.Input(shape=(128,)) embeding = keras.layers.Embedding(vocab_size, 128)(input) lstm1 = keras.layers.LSTM(128, return_sequences=True)(embeding) 分享8赞 stablediffusion吧 爪袭...
IB Unit 1-Festival Part 1 Chinese Characters HSK 1 body parts, size ( no pinyin) Food and Drink related words Body parts, size ( with pinyin) Fruits in Chinese IB Unit 1-Festival Chinese Leisure Family (with pinyin) AP Chinese Vocab...
dec_hidden_size = enc_total_size self.enc_dec_adapter =Noneself.embedding = nn.Embedding(self.vocab_size, self.embed_size, padding_idx=vocab.PAD, _weight=embedding_weights) self.encoder = EncoderRNN(self.embed_size, params.hidden_size, params.enc_bidi, ...
opt.vocab_size = len(TEXT.vocab) opt.embedding_dim= TEXT.vocab.vectors.size()[1] opt.embeddings = TEXT.vocab.vectorsreturntrain_iter, test_iter 开发者ID:wabyking,项目名称:TextClassificationBenchmark,代码行数:34,代码来源:utils.py 示例15: embed_sent ...
在下文中一共展示了Vocabulary.get_vocab_size方法的14个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: __init__ ▲点赞 9▼ # 需要导入模块: from allennlp.data import Vocabulary [as 别名]# 或者: from allennl...
embedding: tensor(vocab_size, embed_size) W1: tensor(2* embed_size, embed_size) b1: tensor(1, embed_size) U: tensor(embed_size, output_size) bs: tensor(1, output_size) Hint: Add the tensorflow variables to the graph here and *reuse* them while building ...
embedding: tensor(vocab_size, embed_size) W1: tensor(2* embed_size, embed_size) b1: tensor(1, embed_size) U: tensor(embed_size, output_size) bs: tensor(1, output_size) Hint: Add the tensorflow variables to the graph here and *reuse* them while building ...
# 需要导入模块: import data [as 别名]# 或者: from data importVocab[as 别名]def__init__(self):self.vocab =Vocab(config.vocab_path, config.vocab_size) self.batcher = Batcher(config.train_data_path, self.vocab, mode='train', batch_size=config.batch_size, single_pass=False) ...