84 lines
2.9 KiB
Python
84 lines
2.9 KiB
Python
# coding=utf-8
|
|
# Copyright 2020 HuggingFace Inc. team.
|
|
#
|
|
# 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 os
|
|
import unittest
|
|
|
|
from transformers import FunnelTokenizer, FunnelTokenizerFast
|
|
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
|
|
from transformers.testing_utils import require_tokenizers
|
|
|
|
from .test_tokenization_common import TokenizerTesterMixin
|
|
|
|
|
|
@require_tokenizers
|
|
class FunnelTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
|
|
|
|
tokenizer_class = FunnelTokenizer
|
|
rust_tokenizer_class = FunnelTokenizerFast
|
|
test_rust_tokenizer = True
|
|
space_between_special_tokens = True
|
|
|
|
def setUp(self):
|
|
super().setUp()
|
|
|
|
vocab_tokens = [
|
|
"<unk>",
|
|
"<cls>",
|
|
"<sep>",
|
|
"want",
|
|
"##want",
|
|
"##ed",
|
|
"wa",
|
|
"un",
|
|
"runn",
|
|
"##ing",
|
|
",",
|
|
"low",
|
|
"lowest",
|
|
]
|
|
self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
|
|
with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
|
|
vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
|
|
|
|
def get_tokenizer(self, **kwargs):
|
|
return FunnelTokenizer.from_pretrained(self.tmpdirname, **kwargs)
|
|
|
|
def get_rust_tokenizer(self, **kwargs):
|
|
return FunnelTokenizerFast.from_pretrained(self.tmpdirname, **kwargs)
|
|
|
|
def get_input_output_texts(self, tokenizer):
|
|
input_text = "UNwant\u00E9d,running"
|
|
output_text = "unwanted, running"
|
|
return input_text, output_text
|
|
|
|
def test_full_tokenizer(self):
|
|
tokenizer = self.tokenizer_class(self.vocab_file)
|
|
|
|
tokens = tokenizer.tokenize("UNwant\u00E9d,running")
|
|
self.assertListEqual(tokens, ["un", "##want", "##ed", ",", "runn", "##ing"])
|
|
self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [7, 4, 5, 10, 8, 9])
|
|
|
|
def test_token_type_ids(self):
|
|
tokenizers = self.get_tokenizers(do_lower_case=False)
|
|
for tokenizer in tokenizers:
|
|
inputs = tokenizer("UNwant\u00E9d,running")
|
|
sentence_len = len(inputs["input_ids"]) - 1
|
|
self.assertListEqual(inputs["token_type_ids"], [2] + [0] * sentence_len)
|
|
|
|
inputs = tokenizer("UNwant\u00E9d,running", "UNwant\u00E9d,running")
|
|
self.assertListEqual(inputs["token_type_ids"], [2] + [0] * sentence_len + [1] * sentence_len)
|