# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np import io import six from paddlerec.core.reader import Reader from paddlerec.core.utils import envs class EvaluateReader(Reader): def init(self): dict_path = envs.get_global_env("word_id_dict_path", None, "evaluate.reader") self.word_to_id = dict() self.id_to_word = dict() with io.open(dict_path, 'r', encoding='utf-8') as f: for line in f: self.word_to_id[line.split(' ')[0]] = int(line.split(' ')[1]) self.id_to_word[int(line.split(' ')[1])] = line.split(' ')[0] self.dict_size = len(self.word_to_id) def native_to_unicode(self, s): if self._is_unicode(s): return s try: return self._to_unicode(s) except UnicodeDecodeError: res = self._to_unicode(s, ignore_errors=True) return res def _is_unicode(self, s): if six.PY2: if isinstance(s, unicode): return True else: if isinstance(s, str): return True return False def _to_unicode(self, s, ignore_errors=False): if self._is_unicode(s): return s error_mode = "ignore" if ignore_errors else "strict" return s.decode("utf-8", errors=error_mode) def strip_lines(self, line, vocab): return self._replace_oov(vocab, self.native_to_unicode(line)) def _replace_oov(self, original_vocab, line): """Replace out-of-vocab words with "". This maintains compatibility with published results. Args: original_vocab: a set of strings (The standard vocabulary for the dataset) line: a unicode string - a space-delimited sequence of words. Returns: a unicode string - a space-delimited sequence of words. """ return u" ".join([ word if word in original_vocab else u"" for word in line.split() ]) def generate_sample(self, line): def reader(): features = self.strip_lines(line.lower(), self.word_to_id) features = features.split() yield [('analogy_a', [self.word_to_id[features[0]]]), ('analogy_b', [self.word_to_id[features[1]]]), ('analogy_c', [self.word_to_id[features[2]]]), ('analogy_d', [self.word_to_id[features[3]]])] return reader