452 lines
23 KiB
Python
452 lines
23 KiB
Python
# coding=utf-8
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# Copyright 2019 Hugging Face inc.
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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 unittest
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from transformers import FNetTokenizer, FNetTokenizerFast
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from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow, tooslow
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from transformers.tokenization_utils import AddedToken
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from ...test_tokenization_common import TokenizerTesterMixin
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SAMPLE_VOCAB = get_tests_dir("fixtures/spiece.model")
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@require_sentencepiece
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@require_tokenizers
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class FNetTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
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from_pretrained_id = "google/fnet-base"
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tokenizer_class = FNetTokenizer
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rust_tokenizer_class = FNetTokenizerFast
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test_rust_tokenizer = True
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test_sentencepiece = True
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test_sentencepiece_ignore_case = True
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test_seq2seq = False
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def setUp(self):
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super().setUp()
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# We have a SentencePiece fixture for testing
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tokenizer = FNetTokenizer(SAMPLE_VOCAB)
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tokenizer.save_pretrained(self.tmpdirname)
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def get_input_output_texts(self, tokenizer):
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input_text = "this is a test"
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output_text = "this is a test"
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return input_text, output_text
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def test_convert_token_and_id(self):
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"""Test ``_convert_token_to_id`` and ``_convert_id_to_token``."""
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token = "<pad>"
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token_id = 0
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self.assertEqual(self.get_tokenizer()._convert_token_to_id(token), token_id)
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self.assertEqual(self.get_tokenizer()._convert_id_to_token(token_id), token)
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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], "<pad>")
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self.assertEqual(vocab_keys[1], "<unk>")
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self.assertEqual(vocab_keys[-1], "▁eloquent")
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self.assertEqual(len(vocab_keys), 30_000)
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def test_vocab_size(self):
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self.assertEqual(self.get_tokenizer().vocab_size, 30_000)
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def test_rust_and_python_full_tokenizers(self):
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if not self.test_rust_tokenizer:
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return
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tokenizer = self.get_tokenizer()
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rust_tokenizer = self.get_rust_tokenizer()
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sequence = "I was born in 92000, and this is falsé."
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tokens = tokenizer.tokenize(sequence)
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rust_tokens = rust_tokenizer.tokenize(sequence)
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self.assertListEqual(tokens, rust_tokens)
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ids = tokenizer.encode(sequence, add_special_tokens=False)
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rust_ids = rust_tokenizer.encode(sequence, add_special_tokens=False)
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self.assertListEqual(ids, rust_ids)
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rust_tokenizer = self.get_rust_tokenizer()
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ids = tokenizer.encode(sequence)
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rust_ids = rust_tokenizer.encode(sequence)
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self.assertListEqual(ids, rust_ids)
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def test_full_tokenizer(self):
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tokenizer = FNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokens = tokenizer.tokenize("This is a test")
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self.assertListEqual(tokens, ["▁", "T", "his", "▁is", "▁a", "▁test"])
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self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [13, 1, 4398, 25, 21, 1289])
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tokens = tokenizer.tokenize("I was born in 92000, and this is falsé.")
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self.assertListEqual(
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tokens,
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["▁", "I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."],
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)
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ids = tokenizer.convert_tokens_to_ids(tokens)
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self.assertListEqual(ids, [13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9])
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(
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back_tokens,
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[
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"▁",
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"<unk>",
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"▁was",
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"▁born",
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"▁in",
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"▁9",
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"2000",
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",",
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"▁and",
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"▁this",
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"▁is",
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"▁fal",
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"s",
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"<unk>",
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".",
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],
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)
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def test_sequence_builders(self):
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tokenizer = FNetTokenizer(SAMPLE_VOCAB)
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text = tokenizer.encode("sequence builders")
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text_2 = tokenizer.encode("multi-sequence build")
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encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
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encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
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assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
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assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_2 + [
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tokenizer.sep_token_id
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]
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# Overriden Tests - loading the fast tokenizer from slow just takes too long
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def test_special_tokens_initialization(self):
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for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
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with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
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added_tokens = [AddedToken("<special>", lstrip=True)]
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tokenizer_r = self.rust_tokenizer_class.from_pretrained(
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pretrained_name, additional_special_tokens=added_tokens, **kwargs
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)
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r_output = tokenizer_r.encode("Hey this is a <special> token")
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special_token_id = tokenizer_r.encode("<special>", add_special_tokens=False)[0]
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self.assertTrue(special_token_id in r_output)
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if self.test_slow_tokenizer:
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tokenizer_p = self.tokenizer_class.from_pretrained(
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pretrained_name, additional_special_tokens=added_tokens, **kwargs
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)
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p_output = tokenizer_p.encode("Hey this is a <special> token")
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cr_output = tokenizer_r.encode("Hey this is a <special> token")
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self.assertEqual(p_output, r_output)
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self.assertEqual(cr_output, r_output)
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self.assertTrue(special_token_id in p_output)
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self.assertTrue(special_token_id in cr_output)
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@tooslow
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def test_special_tokens_initialization_from_slow(self):
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for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
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with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
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added_tokens = [AddedToken("<special>", lstrip=True)]
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tokenizer_r = self.rust_tokenizer_class.from_pretrained(
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pretrained_name, additional_special_tokens=added_tokens, **kwargs, from_slow=True
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)
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special_token_id = tokenizer_r.encode("<special>", add_special_tokens=False)[0]
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tokenizer_p = self.tokenizer_class.from_pretrained(
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pretrained_name, additional_special_tokens=added_tokens, **kwargs
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)
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p_output = tokenizer_p.encode("Hey this is a <special> token")
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cr_output = tokenizer_r.encode("Hey this is a <special> token")
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self.assertEqual(p_output, cr_output)
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self.assertTrue(special_token_id in p_output)
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self.assertTrue(special_token_id in cr_output)
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# Overriden Tests
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def test_padding(self, max_length=50):
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if not self.test_slow_tokenizer:
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# as we don't have a slow version, we can't compare the outputs between slow and fast versions
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return
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for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
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with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"):
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tokenizer_r = self.rust_tokenizer_class.from_pretrained(pretrained_name, **kwargs)
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tokenizer_p = self.tokenizer_class.from_pretrained(pretrained_name, **kwargs)
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self.assertEqual(tokenizer_p.pad_token_id, tokenizer_r.pad_token_id)
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pad_token_id = tokenizer_p.pad_token_id
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# Encode - Simple input
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input_r = tokenizer_r.encode("This is a simple input", max_length=max_length, pad_to_max_length=True)
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input_p = tokenizer_p.encode("This is a simple input", max_length=max_length, pad_to_max_length=True)
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self.assert_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.encode("This is a simple input", max_length=max_length, padding="max_length")
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input_p = tokenizer_p.encode("This is a simple input", max_length=max_length, padding="max_length")
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self.assert_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.encode("This is a simple input", padding="longest")
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input_p = tokenizer_p.encode("This is a simple input", padding=True)
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self.assert_padded_input_match(input_r, input_p, len(input_r), pad_token_id)
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# Encode - Pair input
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input_r = tokenizer_r.encode(
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"This is a simple input", "This is a pair", max_length=max_length, pad_to_max_length=True
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)
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input_p = tokenizer_p.encode(
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"This is a simple input", "This is a pair", max_length=max_length, pad_to_max_length=True
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)
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self.assert_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.encode(
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"This is a simple input", "This is a pair", max_length=max_length, padding="max_length"
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)
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input_p = tokenizer_p.encode(
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"This is a simple input", "This is a pair", max_length=max_length, padding="max_length"
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)
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self.assert_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.encode("This is a simple input", "This is a pair", padding=True)
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input_p = tokenizer_p.encode("This is a simple input", "This is a pair", padding="longest")
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self.assert_padded_input_match(input_r, input_p, len(input_r), pad_token_id)
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# Encode_plus - Simple input
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input_r = tokenizer_r.encode_plus(
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"This is a simple input", max_length=max_length, pad_to_max_length=True
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)
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input_p = tokenizer_p.encode_plus(
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"This is a simple input", max_length=max_length, pad_to_max_length=True
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)
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self.assert_padded_input_match(input_r["input_ids"], input_p["input_ids"], max_length, pad_token_id)
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input_r = tokenizer_r.encode_plus(
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"This is a simple input", max_length=max_length, padding="max_length"
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)
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input_p = tokenizer_p.encode_plus(
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"This is a simple input", max_length=max_length, padding="max_length"
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)
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self.assert_padded_input_match(input_r["input_ids"], input_p["input_ids"], max_length, pad_token_id)
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input_r = tokenizer_r.encode_plus("This is a simple input", padding="longest")
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input_p = tokenizer_p.encode_plus("This is a simple input", padding=True)
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self.assert_padded_input_match(
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input_r["input_ids"], input_p["input_ids"], len(input_r["input_ids"]), pad_token_id
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)
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# Encode_plus - Pair input
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input_r = tokenizer_r.encode_plus(
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"This is a simple input", "This is a pair", max_length=max_length, pad_to_max_length=True
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)
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input_p = tokenizer_p.encode_plus(
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"This is a simple input", "This is a pair", max_length=max_length, pad_to_max_length=True
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)
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self.assert_padded_input_match(input_r["input_ids"], input_p["input_ids"], max_length, pad_token_id)
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input_r = tokenizer_r.encode_plus(
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"This is a simple input", "This is a pair", max_length=max_length, padding="max_length"
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)
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input_p = tokenizer_p.encode_plus(
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"This is a simple input", "This is a pair", max_length=max_length, padding="max_length"
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)
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self.assert_padded_input_match(input_r["input_ids"], input_p["input_ids"], max_length, pad_token_id)
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input_r = tokenizer_r.encode_plus("This is a simple input", "This is a pair", padding="longest")
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input_p = tokenizer_p.encode_plus("This is a simple input", "This is a pair", padding=True)
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self.assert_padded_input_match(
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input_r["input_ids"], input_p["input_ids"], len(input_r["input_ids"]), pad_token_id
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)
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# Batch_encode_plus - Simple input
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input_r = tokenizer_r.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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pad_to_max_length=True,
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)
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input_p = tokenizer_p.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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pad_to_max_length=True,
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)
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self.assert_batch_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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padding="max_length",
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)
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input_p = tokenizer_p.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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padding="max_length",
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)
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self.assert_batch_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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padding="longest",
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)
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input_p = tokenizer_p.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"],
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max_length=max_length,
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padding=True,
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)
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self.assert_batch_padded_input_match(input_r, input_p, len(input_r["input_ids"][0]), pad_token_id)
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input_r = tokenizer_r.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"], padding="longest"
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)
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input_p = tokenizer_p.batch_encode_plus(
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["This is a simple input 1", "This is a simple input 2"], padding=True
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)
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self.assert_batch_padded_input_match(input_r, input_p, len(input_r["input_ids"][0]), pad_token_id)
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# Batch_encode_plus - Pair input
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input_r = tokenizer_r.batch_encode_plus(
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[
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("This is a simple input 1", "This is a simple input 2"),
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("This is a simple pair 1", "This is a simple pair 2"),
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],
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max_length=max_length,
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truncation=True,
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padding="max_length",
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)
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input_p = tokenizer_p.batch_encode_plus(
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[
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("This is a simple input 1", "This is a simple input 2"),
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("This is a simple pair 1", "This is a simple pair 2"),
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],
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max_length=max_length,
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truncation=True,
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padding="max_length",
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)
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self.assert_batch_padded_input_match(input_r, input_p, max_length, pad_token_id)
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input_r = tokenizer_r.batch_encode_plus(
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[
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("This is a simple input 1", "This is a simple input 2"),
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("This is a simple pair 1", "This is a simple pair 2"),
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],
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padding=True,
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)
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input_p = tokenizer_p.batch_encode_plus(
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[
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("This is a simple input 1", "This is a simple input 2"),
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("This is a simple pair 1", "This is a simple pair 2"),
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],
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padding="longest",
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)
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self.assert_batch_padded_input_match(input_r, input_p, len(input_r["input_ids"][0]), pad_token_id)
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# Using pad on single examples after tokenization
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input_r = tokenizer_r.encode_plus("This is a input 1")
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input_r = tokenizer_r.pad(input_r)
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input_p = tokenizer_r.encode_plus("This is a input 1")
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input_p = tokenizer_r.pad(input_p)
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self.assert_padded_input_match(
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input_r["input_ids"], input_p["input_ids"], len(input_r["input_ids"]), pad_token_id
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)
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# Using pad on single examples after tokenization
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input_r = tokenizer_r.encode_plus("This is a input 1")
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input_r = tokenizer_r.pad(input_r, max_length=max_length, padding="max_length")
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input_p = tokenizer_r.encode_plus("This is a input 1")
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input_p = tokenizer_r.pad(input_p, max_length=max_length, padding="max_length")
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self.assert_padded_input_match(input_r["input_ids"], input_p["input_ids"], max_length, pad_token_id)
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# Using pad after tokenization
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input_r = tokenizer_r.batch_encode_plus(
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["This is a input 1", "This is a much longer input whilch should be padded"]
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)
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input_r = tokenizer_r.pad(input_r)
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input_p = tokenizer_r.batch_encode_plus(
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["This is a input 1", "This is a much longer input whilch should be padded"]
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)
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input_p = tokenizer_r.pad(input_p)
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self.assert_batch_padded_input_match(input_r, input_p, len(input_r["input_ids"][0]), pad_token_id)
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# Using pad after tokenization
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input_r = tokenizer_r.batch_encode_plus(
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["This is a input 1", "This is a much longer input whilch should be padded"]
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)
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input_r = tokenizer_r.pad(input_r, max_length=max_length, padding="max_length")
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input_p = tokenizer_r.batch_encode_plus(
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["This is a input 1", "This is a much longer input whilch should be padded"]
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)
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input_p = tokenizer_r.pad(input_p, max_length=max_length, padding="max_length")
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self.assert_batch_padded_input_match(input_r, input_p, max_length, pad_token_id)
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@slow
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def test_save_pretrained(self):
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super().test_save_pretrained()
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@slow
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def test_save_slow_from_fast_and_reload_fast(self):
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super().test_save_slow_from_fast_and_reload_fast()
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def assert_batch_padded_input_match(
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self,
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input_r: dict,
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input_p: dict,
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max_length: int,
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pad_token_id: int,
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model_main_input_name: str = "input_ids",
|
|
):
|
|
for i_r in input_r.values():
|
|
(
|
|
self.assertEqual(len(i_r), 2),
|
|
self.assertEqual(len(i_r[0]), max_length),
|
|
self.assertEqual(len(i_r[1]), max_length),
|
|
)
|
|
(
|
|
self.assertEqual(len(i_r), 2),
|
|
self.assertEqual(len(i_r[0]), max_length),
|
|
self.assertEqual(len(i_r[1]), max_length),
|
|
)
|
|
|
|
for i_r, i_p in zip(input_r[model_main_input_name], input_p[model_main_input_name]):
|
|
self.assert_padded_input_match(i_r, i_p, max_length, pad_token_id)
|
|
|
|
@slow
|
|
def test_tokenizer_integration(self):
|
|
expected_encoding = {'input_ids': [[4, 4616, 107, 163, 328, 14, 63, 1726, 106, 11954, 16659, 23, 83, 16688, 11427, 328, 107, 36, 11954, 16659, 23, 83, 16688, 6153, 82, 961, 16688, 3474, 16710, 1696, 2306, 16688, 10854, 2524, 3827, 561, 163, 3474, 16680, 62, 226, 2092, 16680, 379, 3474, 16660, 16680, 2436, 16667, 16671, 16680, 999, 87, 3474, 16680, 2436, 16667, 5208, 800, 16710, 68, 2018, 2959, 3037, 163, 16663, 11617, 16710, 36, 2018, 2959, 4737, 163, 16663, 16667, 16674, 16710, 91, 372, 5087, 16745, 2205, 82, 961, 3608, 38, 1770, 16745, 7984, 36, 2565, 751, 9017, 1204, 864, 218, 1244, 16680, 11954, 16659, 23, 83, 36, 14686, 23, 7619, 16678, 5], [4, 28, 532, 65, 1929, 33, 391, 16688, 3979, 9, 2565, 7849, 299, 225, 34, 2040, 305, 167, 289, 16667, 16078, 32, 1966, 181, 4626, 63, 10575, 71, 851, 1491, 36, 624, 4757, 38, 208, 8038, 16678, 5, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3], [4, 13, 1467, 5187, 26, 2521, 4567, 16664, 372, 13, 16209, 3314, 16678, 5, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]], 'token_type_ids': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]} # fmt: skip
|
|
|
|
self.tokenizer_integration_test_util(
|
|
expected_encoding=expected_encoding,
|
|
model_name="google/fnet-base",
|
|
revision="34219a71ca20e280cc6000b89673a169c65d605c",
|
|
)
|