




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__SCREAMING_SNAKE_CASE    :   List[Any]       =logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE    :   Optional[int]       ={
    """google/rembert""": """https://huggingface.co/google/rembert/resolve/main/config.json""",
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:	Any     ="rembert"




     def __init__(    self  :   str	,  A__  :   Union[str, Any]=2_5_0_3_0_0	,  A__  :   Any=1_1_5_2	,  A__  :   List[Any]=3_2	,  A__  :   int=1_8	,  A__  :   Any=2_5_6	,  A__  :   Optional[Any]=1_6_6_4	,  A__  :   Optional[Any]=4_6_0_8	,  A__  :   List[Any]="gelu"	,  A__  :   Dict=0.0	,  A__  :   str=0.0	,  A__  :   Union[str, Any]=0.1	,  A__  :   Union[str, Any]=5_1_2	,  A__  :   Optional[Any]=2	,  A__  :   Optional[int]=0.02	,  A__  :   Union[str, Any]=1E-12	,  A__  :   Dict=True	,  A__  :   Dict=0	,  A__  :   Tuple=3_1_2	,  A__  :   Optional[Any]=3_1_3	,  **A__  :   Optional[int]	,  )				->       Tuple:
           super().__init__(pad_token_id=A__	,  bos_token_id=A__	,  eos_token_id=A__	,  **A__			)

           lowerCamelCase__        =				vocab_size
           lowerCamelCase__        =				input_embedding_size
           lowerCamelCase__        =				output_embedding_size
           lowerCamelCase__        =				max_position_embeddings
           lowerCamelCase__        =				hidden_size
           lowerCamelCase__        =				num_hidden_layers
           lowerCamelCase__        =				num_attention_heads
           lowerCamelCase__        =				intermediate_size
           lowerCamelCase__        =				hidden_act
           lowerCamelCase__        =				hidden_dropout_prob
           lowerCamelCase__        =				attention_probs_dropout_prob
           lowerCamelCase__        =				classifier_dropout_prob
           lowerCamelCase__        =				initializer_range
           lowerCamelCase__        =				type_vocab_size
           lowerCamelCase__        =				layer_norm_eps
           lowerCamelCase__        =				use_cache
           lowerCamelCase__        =				False






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     @property
     def  __snake_case   (    self  :   Any			)				->       Mapping[str, Mapping[int, str]]:
           if self.task == "multiple-choice":
                 lowerCamelCase__        =				{0: 'batch', 1: 'choice', 2: 'sequence'}
           else:
                 lowerCamelCase__        =				{0: 'batch', 1: 'sequence'}
           return OrderedDict(
               [
                   ('input_ids', dynamic_axis),
                   ('attention_mask', dynamic_axis),
                   ('token_type_ids', dynamic_axis),
               ]			)




     @property
     def  __snake_case   (    self  :   Optional[int]			)				->       float:
           return 1E-4





import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


__SCREAMING_SNAKE_CASE    :   int       =importlib.metadata.version("""numpy""")
__SCREAMING_SNAKE_CASE    :   Optional[int]       =""".""".join([str(x) for x in sys.version_info[:3]])






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     def  __snake_case   (    self  :   List[Any]			)				->       Optional[int]:
           # lt + different version strings
           require_version_core('numpy<1000.4.5'			)
           require_version_core('numpy<1000.4'			)
           require_version_core('numpy<1000'			)

           # le
           require_version_core('numpy<=1000.4.5'			)
           require_version_core(F"""numpy<={numpy_ver}"""			)

           # eq
           require_version_core(F"""numpy=={numpy_ver}"""			)

           # ne
           require_version_core('numpy!=1000.4.5'			)

           # ge
           require_version_core('numpy>=1.0'			)
           require_version_core('numpy>=1.0.0'			)
           require_version_core(F"""numpy>={numpy_ver}"""			)

           # gt
           require_version_core('numpy>1.0.0'			)

           # mix
           require_version_core('numpy>1.0.0,<1000'			)

           # requirement w/o version
           require_version_core('numpy'			)

           # unmet requirements due to version conflict
           for req in ["numpy==1.0.0", "numpy>=1000.0.0", F"""numpy<{numpy_ver}"""]:
                 try:
                       require_version_core(A__			)
                 except ImportError as e:
                       self.assertIn(F"""{req} is required"""	,  str(A__			)			)
                       self.assertIn('but found'	,  str(A__			)			)

        # unmet requirements due to missing module
           for req in ["numpipypie>1", "numpipypie2"]:
                 try:
                       require_version_core(A__			)
                 except importlib.metadata.PackageNotFoundError as e:
                       self.assertIn(F"""The '{req}' distribution was not found and is required by this application"""	,  str(A__			)			)
                       self.assertIn('Try: pip install transformers -U'	,  str(A__			)			)

        # bogus requirements formats:
        # 1. whole thing
           for req in ["numpy??1.0.0", "numpy1.0.0"]:
                 try:
                       require_version_core(A__			)
                 except ValueError as e:
                       self.assertIn('requirement needs to be in the pip package format'	,  str(A__			)			)
        # 2. only operators
           for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
                 try:
                       require_version_core(A__			)
                 except ValueError as e:
                       self.assertIn('need one of '	,  str(A__			)			)




     def  __snake_case   (    self  :   str			)				->       Optional[int]:
           # matching requirement
           require_version('python>=3.6.0'			)

           # not matching requirements
           for req in ["python>9.9.9", "python<3.0.0"]:
                 try:
                       require_version_core(A__			)
                 except ImportError as e:
                       self.assertIn(F"""{req} is required"""	,  str(A__			)			)
                       self.assertIn(F"""but found python=={python_ver}"""	,  str(A__			)			)