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from picklable_itertools import iter_, chain |
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from fuel.datasets import Dataset |
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from fuel.utils.formats import open_ |
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class TextFile(Dataset): |
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r"""Reads text files and numberizes them given a dictionary. |
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Parameters |
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---------- |
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files : list of str |
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The names of the files in order which they should be read. Each |
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file is expected to have a sentence per line. If the filename ends |
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with `.gz` it will be opened using `gzip`. Note however that `gzip` |
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file handles aren't picklable on legacy Python. |
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dictionary : str or dict |
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Either the path to a Pickled dictionary mapping tokens to integers, |
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or the dictionary itself. At the very least this dictionary must |
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map the unknown word-token to an integer. |
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bos_token : str or None, optional |
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The beginning-of-sentence (BOS) token in the dictionary that |
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denotes the beginning of a sentence. Is ``<S>`` by default. If |
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passed ``None`` no beginning of sentence markers will be added. |
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eos_token : str or None, optional |
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The end-of-sentence (EOS) token is ``</S>`` by default, see |
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``bos_taken``. |
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unk_token : str, optional |
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The token in the dictionary to fall back on when a token could not |
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be found in the dictionary. ``<UNK>`` by default. Pass ``None`` if |
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the dataset doesn't contain any out-of-vocabulary words/characters |
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(the data request is going to crash if meets an unknown symbol). |
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level : 'word' or 'character', optional |
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If 'word' the dictionary is expected to contain full words. The |
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sentences in the text file will be split at the spaces, and each |
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word replaced with its number as given by the dictionary, resulting |
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in each example being a single list of numbers. If 'character' the |
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dictionary is expected to contain single letters as keys. A single |
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example will be a list of character numbers, starting with the |
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first non-whitespace character and finishing with the last one. The |
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default is 'word'. |
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preprocess : function, optional |
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A function which takes a sentence (string) as an input and returns |
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a modified string. For example ``str.lower`` in order to lowercase |
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the sentence before numberizing. |
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encoding : str, optional |
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The encoding to use to read the file. Defaults to ``None``. Use |
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UTF-8 if the dictionary you pass contains UTF-8 characters, but |
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note that this makes the dataset unpicklable on legacy Python. |
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Examples |
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-------- |
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>>> with open('sentences.txt', 'w') as f: |
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... _ = f.write("This is a sentence\n") |
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... _ = f.write("This another one") |
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>>> dictionary = {'<UNK>': 0, '</S>': 1, 'this': 2, 'a': 3, 'one': 4} |
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>>> def lower(s): |
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... return s.lower() |
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>>> text_data = TextFile(files=['sentences.txt'], |
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... dictionary=dictionary, bos_token=None, |
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... preprocess=lower) |
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>>> from fuel.streams import DataStream |
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>>> for data in DataStream(text_data).get_epoch_iterator(): |
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... print(data) |
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([2, 0, 3, 0, 1],) |
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([2, 0, 4, 1],) |
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>>> full_dictionary = {'this': 0, 'a': 3, 'is': 4, 'sentence': 5, |
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... 'another': 6, 'one': 7} |
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>>> text_data = TextFile(files=['sentences.txt'], |
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... dictionary=full_dictionary, bos_token=None, |
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... eos_token=None, unk_token=None, |
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... preprocess=lower) |
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>>> for data in DataStream(text_data).get_epoch_iterator(): |
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... print(data) |
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([0, 4, 3, 5],) |
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([0, 6, 7],) |
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.. doctest:: |
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:hide: |
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>>> import os |
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>>> os.remove('sentences.txt') |
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""" |
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provides_sources = ('features',) |
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example_iteration_scheme = None |
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def __init__(self, files, dictionary, bos_token='<S>', eos_token='</S>', |
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unk_token='<UNK>', level='word', preprocess=None, |
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encoding=None): |
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self.files = files |
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self.dictionary = dictionary |
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if bos_token is not None and bos_token not in dictionary: |
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raise ValueError( |
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"BOS token '{}' is not in the dictionary".format(bos_token)) |
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self.bos_token = bos_token |
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if eos_token is not None and eos_token not in dictionary: |
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raise ValueError( |
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"EOS token '{}' is not in the dictionary".format(eos_token)) |
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self.eos_token = eos_token |
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if unk_token is not None and unk_token not in dictionary: |
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raise ValueError( |
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"UNK token '{}' is not in the dictionary".format(unk_token)) |
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self.unk_token = unk_token |
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if level not in ('word', 'character'): |
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raise ValueError( |
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"level should be 'word' or 'character', not '{}'" |
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.format(level)) |
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self.level = level |
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self.preprocess = preprocess |
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self.encoding = encoding |
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super(TextFile, self).__init__() |
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def open(self): |
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return chain(*[iter_(open_(f, encoding=self.encoding)) |
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for f in self.files]) |
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def _get_from_dictionary(self, symbol): |
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value = self.dictionary.get(symbol) |
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if value is not None: |
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return value |
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else: |
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if self.unk_token is None: |
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raise KeyError("token '{}' not found in dictionary and no " |
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"`unk_token` given".format(symbol)) |
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return self.dictionary[self.unk_token] |
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def get_data(self, state=None, request=None): |
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if request is not None: |
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raise ValueError |
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sentence = next(state) |
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if self.preprocess is not None: |
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sentence = self.preprocess(sentence) |
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data = [self.dictionary[self.bos_token]] if self.bos_token else [] |
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if self.level == 'word': |
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data.extend(self._get_from_dictionary(word) |
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for word in sentence.split()) |
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else: |
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data.extend(self._get_from_dictionary(char) |
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for char in sentence.strip()) |
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if self.eos_token: |
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data.append(self.dictionary[self.eos_token]) |
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return (data,) |
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mila-udem /
fuel
