dnc/Dataset/NLP/Vocabulary.py
2018-11-15 20:31:23 +01:00

50 lines
1.7 KiB
Python

# Copyright 2017 Robert Csordas. 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.
#
# ==============================================================================
class Vocabulary:
def __init__(self):
self.words = {"-" : 0, "?": 1, "<UNK>": 2}
self.inv_words = {0 : "-", 1: "?", 2: "<UNK>"}
self.next_id = 3
self.punctations = [".", "?", ","]
def _process_word(self, w, add_words):
if not w.isalpha() and w not in self.punctations:
print("WARNING: word with unknown characters: %s", w)
w = "<UNK>"
if w not in self.words:
if add_words:
self.words[w] = self.next_id
self.inv_words[self.next_id] = w
self.next_id += 1
else:
w = "<UNK>"
return self.words[w]
def sentence_to_indices(self, sentence, add_words=True):
for p in self.punctations:
sentence = sentence.replace(p, " %s " % p)
return [self._process_word(w, add_words) for w in sentence.lower().split(" ") if w]
def indices_to_sentence(self, indices):
return [self.inv_words[i] for i in indices]
def __len__(self):
return len(self.words)