




'''simple docstring'''






import unittest

from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available

from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin


if is_bsa_available():
      from transformers import MarkupLMFeatureExtractor






class        lowercase_      (						unittest.TestCase							):





     def __init__(     self     :					Dict     ,							__lowerCamelCase     :					Dict			):
           snake_case__       :   Union[str, Any]	      =    parent





     def 			_lowerCAmelCase      (     self     :					Optional[Any]			):
           return {}






def 		UpperCamelCase__      (		)    ->   Dict:
      snake_case__       :   Any	      =    '<HTML>\n\n    <HEAD>\n    <TITLE>sample document</TITLE>\n    </HEAD>\n\n    <BODY BGCOLOR="FFFFFF">\n    <HR>\n    <a href="http://google.com">Goog</a>\n    <H1>This is one header</H1>\n    <H2>This is a another Header</H2>\n    <P>Travel from\n        <P>\n        <B>SFO to JFK</B>\n        <BR>\n        <B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>\n        <HR>\n        <div style="color:#0000FF">\n            <h3>Traveler <b> name </b> is\n            <p> John Doe </p>\n        </div>'

      snake_case__       :   Dict	      =    '\n    <!DOCTYPE html>\n    <html>\n    <body>\n\n    <h1>My First Heading</h1>\n    <p>My first paragraph.</p>\n\n    </body>\n    </html>\n    '

      return [html_string_a, html_string_a]






@require_bsa
class        lowercase_      (						lowerCAmelCase_						,       unittest.TestCase							):
     A_											=			MarkupLMFeatureExtractor if is_bsa_available() else None





     def 			_lowerCAmelCase      (     self     :					str			):
           snake_case__       :   Dict	      =    MarkupLMFeatureExtractionTester(self			)





     @property
     def 			_lowerCAmelCase      (     self     :					Dict			):
           return self.feature_extract_tester.prepare_feat_extract_dict()





     def 			_lowerCAmelCase      (     self     :					Dict			):
           # Initialize feature_extractor
           snake_case__       :   Optional[Any]	      =    self.feature_extraction_class()

           # Test not batched input
           snake_case__       :   Any	      =    get_html_strings()[0]
           snake_case__       :   Tuple	      =    feature_extractor(__lowerCamelCase			)

           # fmt: off
           snake_case__       :   List[str]	      =    [['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']]
           snake_case__       :   str	      =    [['/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']]
           # fmt: on

           self.assertEqual(encoding.nodes     ,							__lowerCamelCase			)
           self.assertEqual(encoding.xpaths     ,							__lowerCamelCase			)

           # Test batched
           snake_case__       :   Any	      =    get_html_strings()
           snake_case__       :   Any	      =    feature_extractor(__lowerCamelCase			)

           # fmt: off
           snake_case__       :   Optional[int]	      =    expected_nodes + [['My First Heading', 'My first paragraph.']]
           snake_case__       :   str	      =    expected_xpaths + [['/html/body/h1', '/html/body/p']]

           self.assertEqual(len(encoding.nodes			)     ,							2			)
           self.assertEqual(len(encoding.xpaths			)     ,							2			)

           self.assertEqual(encoding.nodes     ,							__lowerCamelCase			)
           self.assertEqual(encoding.xpaths     ,							__lowerCamelCase			)






'''simple docstring'''






from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *
