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test_data_vocab.py
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import pytest
import collections
import random
import uuid
import os
import numpy as np
from gluonnlp.data.vocab import Vocab
def test_vocab():
def check_same_vocab(vocab1, vocab2):
assert vocab1.all_tokens == vocab2.all_tokens
assert len(vocab1._special_token_kv) == len(vocab2._special_token_kv)
for k, v in vocab1._special_token_kv.items():
assert v == vocab2._special_token_kv[k]
assert getattr(vocab1, k) == getattr(vocab2, k)
def check_consistency(vocab):
for i, token in enumerate(vocab.all_tokens):
assert vocab[token] == i
if hasattr(vocab, 'unk_token'):
assert vocab['some1234123dasf'] == vocab[vocab.unk_token]
assert len(vocab) == len(vocab.all_tokens)
if len(vocab.all_tokens) > 0:
random_idx = [random.randint(0, len(vocab.all_tokens) - 1) for _ in range(20)]
assert vocab.to_tokens(random_idx) == [vocab.all_tokens[i] for i in random_idx]
assert vocab.to_tokens(np.array(random_idx)) == [vocab.all_tokens[i] for i in random_idx]
random_tokens = vocab.to_tokens(random_idx)
assert vocab[random_tokens] == random_idx
if vocab.has_unk:
assert vocab[random_tokens + ['213412hadhfk']]\
== random_idx + [vocab.unk_id]
for k, v in vocab.special_tokens_kv.items():
idx_property = k[:-6] + '_id'
assert getattr(vocab, idx_property) == vocab[v]
# Test for serialize/deserailze from json
json_str = vocab.to_json()
new_vocab = Vocab.from_json(json_str)
check_same_vocab(new_vocab, vocab)
# Test for save/load from file
while True:
fname = '{}.json'.format(uuid.uuid4())
if os.path.exists(fname):
continue
vocab.save(path=fname)
new_vocab = Vocab.load(fname)
check_same_vocab(new_vocab, vocab)
os.remove(fname)
break
words = ['a', 'a', 'b', 'd', 'c', 'b', 'a', 'c', 'd', 'd', 'd']
random.shuffle(words)
counter = collections.Counter(words)
vocab = Vocab(counter, max_size=2, min_freq=None)
check_consistency(vocab)
assert vocab.all_tokens == ['d', 'a', '<unk>']
# Test for unknown token
vocab = Vocab(tokens=counter, max_size=2, min_freq=None, unk_token='<unk2>')
check_consistency(vocab)
assert vocab.all_tokens == ['d', 'a', '<unk2>']
vocab = Vocab(tokens=counter, max_size=None, min_freq=None,
pad_token=Vocab.PAD_TOKEN, eos_token=Vocab.EOS_TOKEN,
bos_token=Vocab.BOS_TOKEN, cls_token=Vocab.CLS_TOKEN,
sep_token=Vocab.SEP_TOKEN, mask_token=Vocab.MASK_TOKEN)
check_consistency(vocab)
assert vocab.unk_token == Vocab.UNK_TOKEN
assert vocab.pad_token == Vocab.PAD_TOKEN
assert vocab.eos_token == Vocab.EOS_TOKEN
assert vocab.bos_token == Vocab.BOS_TOKEN
assert vocab.cls_token == Vocab.CLS_TOKEN
assert vocab.sep_token == Vocab.SEP_TOKEN
assert vocab.mask_token == Vocab.MASK_TOKEN
assert vocab.special_token_keys == ['unk_token', 'bos_token', 'cls_token', 'eos_token', 'mask_token', 'pad_token', 'sep_token']
assert vocab.special_tokens == ['<unk>', '<bos>', '<cls>', '<eos>', '<mask>', '<pad>', '<sep>']
assert vocab.all_tokens == ['d', 'a', 'c', 'b', '<unk>', '<bos>', '<cls>', '<eos>', '<mask>', '<pad>', '<sep>']
vocab = Vocab(counter, bos_token=Vocab.BOS_TOKEN, eos_token=Vocab.EOS_TOKEN,
pad_token=Vocab.PAD_TOKEN)
check_consistency(vocab)
assert vocab.all_tokens == ['d', 'a', 'c', 'b', '<unk>', '<bos>', '<eos>', '<pad>']
vocab = Vocab(counter, max_size=None, min_freq=None,
pad_token=Vocab.PAD_TOKEN, eos_token=Vocab.EOS_TOKEN,
bos_token=Vocab.BOS_TOKEN, mask_token='<mask2>',
other3_token='<other3>', other2_token='<other2>')
check_consistency(vocab)
assert vocab.all_tokens == ['d', 'a', 'c', 'b', '<unk>', '<bos>', '<eos>', '<mask2>', '<other2>', '<other3>', '<pad>']
assert vocab.mask_token == '<mask2>'
assert vocab.other2_token == '<other2>'
assert vocab.other3_token == '<other3>'
assert vocab.special_token_keys == ['unk_token', 'bos_token', 'eos_token', 'mask_token', 'other2_token', 'other3_token', 'pad_token']
assert vocab.special_tokens == ['<unk>', '<bos>', '<eos>', '<mask2>', '<other2>', '<other3>', '<pad>']
vocab = Vocab(counter, max_size=1, min_freq=10000, unk_token=None)
check_consistency(vocab)
assert vocab.all_tokens == []
vocab = Vocab([], pad_token=Vocab.PAD_TOKEN, eos_token=Vocab.EOS_TOKEN,
bos_token=Vocab.BOS_TOKEN, mask_token='<mask2>')
check_consistency(vocab)
assert vocab.all_tokens == ['<unk>', '<bos>', '<eos>', '<mask2>', '<pad>']
vocab = Vocab(pad_token=Vocab.PAD_TOKEN, eos_token=Vocab.EOS_TOKEN,
bos_token=Vocab.BOS_TOKEN, mask_token='<mask2>')
check_consistency(vocab)
assert vocab.all_tokens == ['<unk>', '<bos>', '<eos>', '<mask2>', '<pad>']
vocab = Vocab(['<unk2>', '<pad>', '<bos>', '<eos>', '<mask>', 'a'],
pad_token=Vocab.PAD_TOKEN, eos_token=Vocab.EOS_TOKEN,
bos_token=Vocab.BOS_TOKEN, mask_token='<mask>')
check_consistency(vocab)
assert vocab.all_tokens == ['<unk2>', '<pad>', '<bos>', '<eos>', '<mask>', 'a', '<unk>']
assert vocab.special_tokens == ['<pad>', '<bos>', '<eos>', '<mask>', '<unk>']
assert vocab.special_token_keys == ['pad_token', 'bos_token', 'eos_token', 'mask_token', 'unk_token']
# Check errors
with pytest.raises(ValueError):
vocab = Vocab(['a', 'a', 'a'])
with pytest.raises(ValueError):
vocab = Vocab(['a', 'b', 'c'], mask_token='<mask>', another_mask_token='<mask>')
with pytest.raises(ValueError):
vocab = Vocab(['a', 'b', 'c'], mask_token='<mask>', another_mask_token='<mask>')
vocab = Vocab(['a', 'b', 'c'])
check_consistency(vocab)
# Check emoji
all_tokens = ['<unk>', '😁']
vocab = Vocab(all_tokens, unk_token='<unk>')
vocab_file = str(uuid.uuid4()) + '.vocab'
vocab.save(vocab_file)
vocab = Vocab.load(vocab_file)
assert vocab.all_tokens == all_tokens
os.remove(vocab_file)