






'''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      A     (   unittest.TestCase    ):






 """simple docstring"""





 def __init__(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: Any            =				parent





 def 	_UpperCAmelCase							(				self			):
       return {}






def 				snake_case       (  )							->					List[Any]:





      """simple docstring"""

      UpperCamelCase_					: Optional[int]            =				"""<HTML>

    <HEAD>
    <TITLE>sample document</TITLE>
    </HEAD>

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

      UpperCamelCase_					: str            =				"""
    <!DOCTYPE html>
    <html>
    <body>

    <h1>My First Heading</h1>
    <p>My first paragraph.</p>

    </body>
    </html>
    """

      return [html_string_a, html_string_a]




@require_bsa
class      A     (   SCREAMING_SNAKE_CASE__, unittest.TestCase    ):






 """simple docstring"""





 __a      :    List[str]			  =    MarkupLMFeatureExtractor if is_bsa_available() else None
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[str]            =				MarkupLMFeatureExtractionTester(self			)
 @property
 def 	_UpperCAmelCase							(				self			):
       return self.feature_extract_tester.prepare_feat_extract_dict()





 def 	_UpperCAmelCase							(				self			):
       # Initialize feature_extractor
       UpperCamelCase_					: str            =				self.feature_extraction_class()

       # Test not batched input
       UpperCamelCase_					: int            =				get_html_strings()[0]
       UpperCamelCase_					: List[str]            =				feature_extractor(__lowerCAmelCase			)

       # fmt: off
       UpperCamelCase_					: 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"""]]
       UpperCamelCase_					: Dict            =				[["""/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
       UpperCamelCase_					: List[Any]            =				get_html_strings()
       UpperCamelCase_					: Dict            =				feature_extractor(__lowerCAmelCase			)

       # fmt: off
       UpperCamelCase_					: List[str]            =				expected_nodes + [["""My First Heading""", """My first paragraph."""]]
       UpperCamelCase_					: List[Any]            =				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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase      					={
    "configuration_clap": [
        "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
        "ClapAudioConfig",
        "ClapConfig",
        "ClapTextConfig",
    ],
    "processing_clap": ["ClapProcessor"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase      					=[
          "CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
          "ClapModel",
          "ClapPreTrainedModel",
          "ClapTextModel",
          "ClapTextModelWithProjection",
          "ClapAudioModel",
          "ClapAudioModelWithProjection",
      ]
      UpperCamelCase      					=["ClapFeatureExtractor"]

if TYPE_CHECKING:
      from .configuration_clap import (
          CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
          ClapAudioConfig,
          ClapConfig,
          ClapTextConfig,
      )
      from .processing_clap import ClapProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_clap import ClapFeatureExtractor
            from .modeling_clap import (
                CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
                ClapAudioModel,
                ClapAudioModelWithProjection,
                ClapModel,
                ClapPreTrainedModel,
                ClapTextModel,
                ClapTextModelWithProjection,
            )


else:
      import sys

      UpperCamelCase      					=_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






