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* [Speech2Text2] Enable tokenizers * minor fix * Apply suggestions from code review Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
98 lines
3.8 KiB
Python
98 lines
3.8 KiB
Python
# Copyright 2021 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import inspect
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import json
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import os
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import tempfile
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import unittest
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from transformers.models.speech_to_text_2 import Speech2Text2Tokenizer
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from transformers.models.speech_to_text_2.tokenization_speech_to_text_2 import VOCAB_FILES_NAMES
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from .test_tokenization_common import TokenizerTesterMixin
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class SpeechToTextTokenizerTest(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = Speech2Text2Tokenizer
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test_rust_tokenizer = False
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def setUp(self):
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super().setUp()
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vocab = "<s> <pad> </s> <unk> here@@ a couple of@@ words for the he@@ re@@ vocab".split(" ")
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merges = ["he re</w> 123", "here a 1456"]
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vocab_tokens = dict(zip(vocab, range(len(vocab))))
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self.special_tokens_map = {"pad_token": "<pad>", "unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>"}
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self.tmpdirname = tempfile.mkdtemp()
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self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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self.merges_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["merges_file"])
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with open(self.vocab_file, "w", encoding="utf-8") as fp:
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fp.write(json.dumps(vocab_tokens) + "\n")
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with open(self.merges_file, "w") as fp:
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fp.write("\n".join(merges))
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def test_get_vocab(self):
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vocab_keys = list(self.get_tokenizer().get_vocab().keys())
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self.assertEqual(vocab_keys[0], "<s>")
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self.assertEqual(vocab_keys[1], "<pad>")
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self.assertEqual(vocab_keys[-1], "vocab")
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self.assertEqual(len(vocab_keys), 14)
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def test_vocab_size(self):
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self.assertEqual(self.get_tokenizer().vocab_size, 14)
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def test_tokenizer_decode(self):
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tokenizer = Speech2Text2Tokenizer.from_pretrained(self.tmpdirname)
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# make sure @@ is correctly concatenated
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token_ids = [4, 6, 8, 7, 10] # ["here@@", "couple", "words", "of@@", "the"]
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output_string = tokenizer.decode(token_ids)
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self.assertTrue(output_string == "herecouple words ofthe")
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def test_load_no_merges_file(self):
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tokenizer = Speech2Text2Tokenizer.from_pretrained(self.tmpdirname)
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with tempfile.TemporaryDirectory() as tmp_dirname:
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tokenizer.save_pretrained(tmp_dirname)
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os.remove(os.path.join(tmp_dirname, "merges.txt"))
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# load tokenizer without merges file should not throw an error
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tokenizer = Speech2Text2Tokenizer.from_pretrained(tmp_dirname)
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with tempfile.TemporaryDirectory() as tmp_dirname:
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# save tokenizer and load again
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tokenizer.save_pretrained(tmp_dirname)
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tokenizer = Speech2Text2Tokenizer.from_pretrained(tmp_dirname)
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self.assertIsNotNone(tokenizer)
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# overwrite since merges_file is optional
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def test_tokenizer_slow_store_full_signature(self):
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if not self.test_slow_tokenizer:
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return
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signature = inspect.signature(self.tokenizer_class.__init__)
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tokenizer = self.get_tokenizer()
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for parameter_name, parameter in signature.parameters.items():
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if parameter.default != inspect.Parameter.empty and parameter_name != "merges_file":
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self.assertIn(parameter_name, tokenizer.init_kwargs)
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