





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 							_UpperCamelCase					(	unittest.TestCase     ):

       def __init__(		self: int					,   _SCREAMING_SNAKE_CASE: Tuple		)       -> Any:




              """simple docstring"""


              UpperCamelCase_          =  parent



       def lowercase (		self: int		)       -> Optional[int]:




              """simple docstring"""


              return {}




def  lowerCAmelCase_ (							)     ->		Dict:
       UpperCamelCase_          =  "<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>"

       UpperCamelCase_          =  "\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 							_UpperCamelCase					(	lowerCAmelCase_  ,						unittest.TestCase     ):
       _UpperCamelCase				:					Tuple         =   MarkupLMFeatureExtractor if is_bsa_available() else None

       def lowercase (		self: List[str]		)       -> str:




              """simple docstring"""


              UpperCamelCase_          =  MarkupLMFeatureExtractionTester(self		)

       @property
       def lowercase (		self: Optional[Any]		)       -> str:




              """simple docstring"""


              return self.feature_extract_tester.prepare_feat_extract_dict()



       def lowercase (		self: Dict		)       -> List[str]:




              """simple docstring"""


              UpperCamelCase_          =  self.feature_extraction_class()

              # Test not batched input
              UpperCamelCase_          =  get_html_strings()[0]
              UpperCamelCase_          =  feature_extractor(_SCREAMING_SNAKE_CASE		)

              # fmt: off
              UpperCamelCase_          =  [["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_          =  [["/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					,   _SCREAMING_SNAKE_CASE		)
              self.assertEqual(encoding.xpaths					,   _SCREAMING_SNAKE_CASE		)

              # Test batched
              UpperCamelCase_          =  get_html_strings()
              UpperCamelCase_          =  feature_extractor(_SCREAMING_SNAKE_CASE		)

              # fmt: off
              UpperCamelCase_          =  expected_nodes + [["My First Heading", "My first paragraph."]]
              UpperCamelCase_          =  expected_xpaths + [["/html/body/h1", "/html/body/p"]]

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

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








import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


_UpperCAmelCase        =				logging.get_logger(__name__)

_UpperCAmelCase        =				'T5Config'




def  lowerCAmelCase_ (							UpperCamelCase_					,		UpperCamelCase_					,		UpperCamelCase_  )     ->		jnp.ndarray:
       UpperCamelCase_          =  jnp.zeros_like(UpperCamelCase_  )
       UpperCamelCase_          =  shifted_input_ids.at[:, 1:].set(input_ids[:, :-1]  )
       UpperCamelCase_          =  shifted_input_ids.at[:, 0].set(UpperCamelCase_  )

       UpperCamelCase_          =  jnp.where(shifted_input_ids == -100					,		UpperCamelCase_					,		UpperCamelCase_  )
       return shifted_input_ids



class 							_UpperCamelCase					(	lowerCAmelCase_     ):
       _UpperCamelCase				:					Dict         =   '''mt5'''
       _UpperCamelCase				:					Union[str, Any]         =   MTaConfig



class 							_UpperCamelCase					(	lowerCAmelCase_     ):
       _UpperCamelCase				:					Dict         =   '''mt5'''
       _UpperCamelCase				:					Optional[int]         =   MTaConfig



class 							_UpperCamelCase					(	lowerCAmelCase_     ):
       _UpperCamelCase				:					Union[str, Any]         =   '''mt5'''
       _UpperCamelCase				:					List[Any]         =   MTaConfig

