63 lines
2.5 KiB
Python
63 lines
2.5 KiB
Python
def get_tokenizer(tokenizer, decap=False):
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if callable(tokenizer):
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return tokenizer
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if tokenizer == "spacy":
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try:
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import spacy
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spacy_en = spacy.load('en')
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return lambda s: [tok.text for tok in spacy_en.tokenizer(s)]
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except ImportError:
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print("Please install SpaCy and the SpaCy English tokenizer. "
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"See the docs at https://spacy.io for more information.")
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raise
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except AttributeError:
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print("Please install SpaCy and the SpaCy English tokenizer. "
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"See the docs at https://spacy.io for more information.")
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raise
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elif tokenizer == "moses":
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try:
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from nltk.tokenize.moses import MosesTokenizer
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moses_tokenizer = MosesTokenizer()
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return moses_tokenizer.tokenize
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except ImportError:
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print("Please install NLTK. "
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"See the docs at http://nltk.org for more information.")
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raise
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except LookupError:
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print("Please install the necessary NLTK corpora. "
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"See the docs at http://nltk.org for more information.")
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raise
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elif tokenizer == 'revtok':
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try:
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import revtok
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return revtok.tokenize
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except ImportError:
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print("Please install revtok.")
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raise
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elif tokenizer == 'subword':
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try:
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import revtok
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return revtok.tokenize
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except ImportError:
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print("Please install revtok.")
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raise
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raise ValueError("Requested tokenizer {}, valid choices are a "
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"callable that takes a single string as input, "
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"\"revtok\" for the revtok reversible tokenizer, "
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"\"subword\" for the revtok caps-aware tokenizer, "
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"\"spacy\" for the SpaCy English tokenizer, or "
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"\"moses\" for the NLTK port of the Moses tokenization "
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"script.".format(tokenizer))
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def interleave_keys(a, b):
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"""Interleave bits from two sort keys to form a joint sort key.
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Examples that are similar in both of the provided keys will have similar
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values for the key defined by this function. Useful for tasks with two
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text fields like machine translation or natural language inference.
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"""
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def interleave(args):
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return ''.join([x for t in zip(*args) for x in t])
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return int(''.join(interleave(format(x, '016b') for x in (a, b))), base=2)
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