#!/usr/bin/env python
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import re
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import numpy as np
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def forward_segment(text, seg_dict):
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word_list = []
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i = 0
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while i < len(text):
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longest_word = text[i]
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for j in range(i + 1, len(text) + 1):
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word = text[i:j]
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if word in seg_dict:
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if len(word) > len(longest_word):
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longest_word = word
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word_list.append(longest_word)
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i += len(longest_word)
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return word_list
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def seg_tokenize(txt, seg_dict):
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out_txt = ""
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for word in txt:
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if word in seg_dict:
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out_txt += seg_dict[word] + " "
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else:
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out_txt += "<unk>" + " "
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return out_txt.strip().split()
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def tokenize(data,
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vocab=None,
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seg_dict=None,
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punc_dict=None,
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bpe_tokenizer=None):
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assert "text" in data
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assert isinstance(vocab, dict)
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text = data["text"]
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token = []
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vad = -2
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if bpe_tokenizer is not None:
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text = bpe_tokenizer.text2tokens(text)
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if seg_dict is not None:
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assert isinstance(seg_dict, dict)
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txt = forward_segment("".join(text).lower(), seg_dict)
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text = seg_tokenize(txt, seg_dict)
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length = len(text)
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for i in range(length):
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x = text[i]
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if i == length-1 and "punc" in data and text[i].startswith("vad:"):
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vad = x[-1][4:]
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if len(vad) == 0:
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vad = -1
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else:
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vad = int(vad)
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elif x in vocab:
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token.append(vocab[x])
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else:
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token.append(vocab['<unk>'])
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if "punc" in data and punc_dict is not None:
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punc_token = []
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for punc in data["punc"]:
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if punc in punc_dict:
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punc_token.append(punc_dict[punc])
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else:
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punc_token.append(punc_dict["_"])
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data["punc"] = np.array(punc_token)
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data["text"] = np.array(token)
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if vad is not -2:
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data["vad_indexes"]=np.array([vad], dtype=np.int64)
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return data
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