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68 lines
2.0 KiB
68 lines
2.0 KiB
"""Contains the text featurizer class."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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class TextFeaturizer(object):
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"""Text featurizer, for processing or extracting features from text.
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Currently, it only supports char-level tokenizing and conversion into
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a list of token indices. Note that the token indexing order follows the
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given vocabulary file.
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:param vocab_filepath: Filepath to load vocabulary for token indices
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conversion.
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:type specgram_type: basestring
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"""
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def __init__(self, vocab_filepath):
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self._vocab_dict, self._vocab_list = self._load_vocabulary_from_file(
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vocab_filepath)
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def featurize(self, text):
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"""Convert text string to a list of token indices in char-level.Note
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that the token indexing order follows the given vocabulary file.
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:param text: Text to process.
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:type text: basestring
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:return: List of char-level token indices.
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:rtype: list
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"""
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tokens = self._char_tokenize(text)
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return [self._vocab_dict[token] for token in tokens]
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@property
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def vocab_size(self):
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"""Return the vocabulary size.
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:return: Vocabulary size.
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:rtype: int
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"""
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return len(self._vocab_list)
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@property
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def vocab_list(self):
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"""Return the vocabulary in list.
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:return: Vocabulary in list.
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:rtype: list
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"""
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return self._vocab_list
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def _char_tokenize(self, text):
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"""Character tokenizer."""
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return list(text.strip())
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def _load_vocabulary_from_file(self, vocab_filepath):
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"""Load vocabulary from file."""
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vocab_lines = []
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with open(vocab_filepath, 'r') as file:
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vocab_lines.extend(file.readlines())
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vocab_list = [line[:-1] for line in vocab_lines]
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vocab_dict = dict(
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[(token, id) for (id, token) in enumerate(vocab_list)])
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return vocab_dict, vocab_list
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