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https://github.com/huggingface/transformers.git
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f3d2f7a6e0
* First draft * Make basic test work * Fix most tokenizer tests * More improvements * Make more tests pass * Fix more tests * Fix some code quality * Improve truncation * Implement feature extractor * Improve feature extractor and add tests * Improve feature extractor tests * Fix pair_input test partly * Add fast tokenizer * Improve implementation * Fix rebase * Fix rebase * Fix most of the tokenizer tests. * propose solution for fast * add: integration test for fasttokenizer, warning for decode, fix template in slow tokenizer * add: modify markuplmconverter * add: some modify on converter and tokenizerfast * Fix style, copies * Make fixup * Update tokenization_markuplm.py * Update test_tokenization_markuplm.py * Update markuplm related * Improve processor, add integration test * Add processor test file * Improve processor * Improve processor tests * Fix more processor tests * Fix processor tests * Update docstrings * Add Copied from statements * Add more Copied from statements * Add code examples * Improve code examples * Add model to doc tests * Adding dependency check * Add dummy file * Add requires_backends * Add model to toctree * Fix more things, disable dependency check for now * Apply more suggestions * Add soft dependency * Add annotators to tests * Fix style * Remove from_slow=True * Remove print statements * Add sanity check * Fix processor test * Fix processor tests, add more docs * Add doc tests for mdx file * Add more tips * Apply suggestions Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local> Co-authored-by: lockon-n <45759388+lockon-n@users.noreply.github.com> Co-authored-by: SaulLu <lucilesaul.com@gmail.com> Co-authored-by: lockon-n <dd098309@126.com>
115 lines
3.6 KiB
Python
115 lines
3.6 KiB
Python
# coding=utf-8
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# Copyright 2022 HuggingFace 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.testing_utils import require_bs4
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from transformers.utils import is_bs4_available
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from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
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if is_bs4_available():
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from transformers import MarkupLMFeatureExtractor
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class MarkupLMFeatureExtractionTester(unittest.TestCase):
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def __init__(self, parent):
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self.parent = parent
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def prepare_feat_extract_dict(self):
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return {}
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def get_html_strings():
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html_string_1 = """<HTML>
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<HEAD>
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<TITLE>sample document</TITLE>
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</HEAD>
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<BODY BGCOLOR="FFFFFF">
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<HR>
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<a href="http://google.com">Goog</a>
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<H1>This is one header</H1>
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<H2>This is a another Header</H2>
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<P>Travel from
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<P>
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<B>SFO to JFK</B>
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<BR>
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<B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>
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<HR>
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<div style="color:#0000FF">
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<h3>Traveler <b> name </b> is
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<p> John Doe </p>
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</div>"""
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html_string_2 = """
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<!DOCTYPE html>
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<html>
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<body>
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<h1>My First Heading</h1>
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<p>My first paragraph.</p>
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</body>
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</html>
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"""
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return [html_string_1, html_string_2]
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@require_bs4
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class MarkupLMFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.TestCase):
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feature_extraction_class = MarkupLMFeatureExtractor if is_bs4_available() else None
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def setUp(self):
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self.feature_extract_tester = MarkupLMFeatureExtractionTester(self)
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@property
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def feat_extract_dict(self):
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return self.feature_extract_tester.prepare_feat_extract_dict()
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def test_call(self):
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# Initialize feature_extractor
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feature_extractor = self.feature_extraction_class()
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# Test not batched input
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html_string = get_html_strings()[0]
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encoding = feature_extractor(html_string)
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# fmt: off
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expected_nodes = [['sample document', 'Goog', 'This is one header', 'This is a another Header', 'Travel from', 'SFO to JFK', 'on May 2, 2015 at 2:00 pm. For details go to confirm.com', 'Traveler', 'name', 'is', 'John Doe']]
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expected_xpaths = [['/html/head/title', '/html/body/a', '/html/body/h1', '/html/body/h2', '/html/body/p', '/html/body/p/p/b[1]', '/html/body/p/p/b[2]/i', '/html/body/p/p/div/h3', '/html/body/p/p/div/h3/b', '/html/body/p/p/div/h3', '/html/body/p/p/div/h3/p']]
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# fmt: on
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self.assertEqual(encoding.nodes, expected_nodes)
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self.assertEqual(encoding.xpaths, expected_xpaths)
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# Test batched
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html_strings = get_html_strings()
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encoding = feature_extractor(html_strings)
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# fmt: off
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expected_nodes = expected_nodes + [['My First Heading', 'My first paragraph.']]
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expected_xpaths = expected_xpaths + [['/html/body/h1', '/html/body/p']]
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self.assertEqual(len(encoding.nodes), 2)
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self.assertEqual(len(encoding.xpaths), 2)
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self.assertEqual(encoding.nodes, expected_nodes)
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self.assertEqual(encoding.xpaths, expected_xpaths)
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