len_{label}和len_{pred}代表标签序列和预测序列中的词元数,即句子长度。第一项指数项用来惩罚过短的预测序列。比如label长度5,预测长度2,那么第一项就是exp(-1.5),小于完美预测的exp(0)。 第二项中的pn代表n-gram精确度,比如标签序列ABCDE,预测序列是ABCCD。 预测序列中一元语法匹配了A,B,C,D四个项,标...
len_q, len_k, len_v = q.size(0), q.size(1), k.size(1), v.size(1) residual = q # Pass through the pre-attention projection: b x lq x (n*dv) # Separate different heads: b x lq x n x dv q = self.w_qs(q).view(sz_b, len_q, n_head, d_k) k = self.w_ks(...
#将一个batch中的input_dialog转化为有pad填充的tensor,并返回tensor和记录长度的变量#返回的tensor是batch_first的defbatchInput2paddedTensor(batch, voc):#先转换为id序列,但是这个id序列不对齐batch_index_seqs = [sentenceToIndex(sentence, voc)forsentenceinbatch] length_tensor= torch.tensor([len(index_seq...
- decoder_input: decoder端输入 '''# 1. Embeddingtarget_vocab_size=len(target_letter_to_int)decoder_embeddings=tf.Variable(tf.random_uniform([target_vocab_size,decoding_embedding_size]))decoder_embed_input=tf.nn.embedding_lookup(decoder_embeddings,decoder_input)# 2. 构造Decoder中的RNN单元defget_...
# 将一个序列中所有的词记录在all_tokens中以便之后构造词典,然后在该序列后面添加PAD直到序列# 长度变为max_seq_len,然后将序列保存在all_seqs中defprocess_one_seq(seq_tokens,all_tokens,all_seqs,max_seq_len):all_tokens.extend(seq_tokens)seq_tokens+=[EOS]+[PAD]*(max_seq_len-len(seq_tokens)-...
I am using an old version of faster-transformer which limit the max_seq_len for using FusedAttentionLayer is 384(512 now in the main branch). I found when the model is using fp16 and the sequence length exceeds 384, the Bert.cc go to call UnfusedAttentionLayer and raise this error: ...
(1, series_len+1)) series = series.reshape(1, 1, -1) train_idx, valid_idx = forward_split(np.arange(series_len), enc_len=enc_len, valid_size=valid_size+test_size) valid_idx, test_idx = forward_split(valid_idx, enc_len, test_size) # mask test, will not be used for ...
sample(len(parend_df)) # Create the unique ids based on the index. parent_samples.index.name = join_on parent_samples = parent_samples.reset_index() # Generate the relational observations. child_samples = child_model.sample( input_unique_ids=parent_samples[join_on], input_df=parent_...
中文长文本分类、短句子分类、多标签分类、两句子相似度(Chinese Text Classification of Keras NLP, multi-label classify, or sentence classify, long or short),字词句向量嵌入层(embeddings)和网络层(graph)构建基类,FastText,TextCNN,CharCNN,TextRNN, RC
这个函数位于seq2seq_data.py文件中,调用generate_seq2seq_data(batch_size=4, maxlen=10),表示生成一个batch的训练数据,batch_size为4,且输入输出的最大长度为10,此时返回: [ ('b', 'B'), ('abCA', 'ABCA'), ('CaccC', 'CACCC'),