



# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import doctest
import sys
import warnings
from os.path import abspath, dirname, join

import _pytest

from transformers.testing_utils import HfDoctestModule, HfDocTestParser


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
__A   			=abspath(join(dirname(__file__), "src"))
sys.path.insert(1, git_repo_path)

# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action="ignore", category=FutureWarning)

def        a						(      _UpperCAmelCase							:					str						):







		'''simple docstring'''





		config.addinivalue_line(
		    '''markers''' ,   '''is_pt_tf_cross_test: mark test to run only when PT and TF interactions are tested'''						)
		config.addinivalue_line(
		    '''markers''' ,   '''is_pt_flax_cross_test: mark test to run only when PT and FLAX interactions are tested'''						)
		config.addinivalue_line('''markers''' ,   '''is_pipeline_test: mark test to run only when pipelines are tested'''						)
		config.addinivalue_line('''markers''' ,   '''is_staging_test: mark test to run only in the staging environment'''						)
		config.addinivalue_line('''markers''' ,   '''accelerate_tests: mark test that require accelerate'''						)
		config.addinivalue_line('''markers''' ,   '''tool_tests: mark the tool tests that are run on their specific schedule'''						)

def        a						(      _UpperCAmelCase							:					int						):







		'''simple docstring'''





		from transformers.testing_utils import pytest_addoption_shared

		pytest_addoption_shared(_UpperCAmelCase						)

def        a						(      _UpperCAmelCase							:					Tuple						):







		'''simple docstring'''





		from transformers.testing_utils import pytest_terminal_summary_main

		__UpperCAmelCase    :     Tuple													=	terminalreporter.config.getoption('''--make-reports'''						)
		if make_reports:
				pytest_terminal_summary_main(_UpperCAmelCase ,   id=_UpperCAmelCase						)

def        a						(      _UpperCAmelCase							:					int ,   _UpperCAmelCase							:					str						):







		'''simple docstring'''





		if exitstatus == 5:
				__UpperCAmelCase    :     str													=	0


# Doctest custom flag to ignore output.
__A   			=doctest.register_optionflag("IGNORE_RESULT")

__A   			=doctest.OutputChecker

class 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






			def  snake_case__     (   self							: Union[str, Any]       ,       a_							: str       ,       a_							: List[Any]       ,       a_							: Any ):
					'''simple docstring'''





					if IGNORE_RESULT & optionflags:
							return True
					return OutputChecker.check_output(self       ,       a_       ,       a_       ,       a_ )
__A   			=CustomOutputChecker
__A   			=HfDoctestModule
__A   			=HfDocTestParser










from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

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


if TYPE_CHECKING:
				from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


__A   			=logging.get_logger(__name__)

__A   			={
    "microsoft/deberta-v2-xlarge": "https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/config.json",
    "microsoft/deberta-v2-xxlarge": "https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/config.json",
    "microsoft/deberta-v2-xlarge-mnli": (
        "https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/config.json"
    ),
    "microsoft/deberta-v2-xxlarge-mnli": (
        "https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/config.json"
    ),
}

class 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






			UpperCamelCase									=       """deberta-v2"""




			def __init__(   self							: Optional[int]       ,       a_							: List[str]=12_81_00       ,       a_							: Optional[Any]=15_36       ,       a_							: Optional[Any]=24       ,       a_							: List[Any]=24       ,       a_							: Optional[int]=61_44       ,       a_							: List[Any]="gelu"       ,       a_							: Any=0.1       ,       a_							: Tuple=0.1       ,       a_							: Optional[Any]=5_12       ,       a_							: Tuple=0       ,       a_							: Dict=0.0_2       ,       a_							: Optional[Any]=1e-7       ,       a_							: List[str]=False       ,       a_							: List[Any]=-1       ,       a_							: List[str]=0       ,       a_							: Optional[Any]=True       ,       a_							: List[Any]=None       ,       a_							: Optional[int]=0       ,       a_							: Tuple="gelu"       ,       **a_							: List[str]       ,       ):
					'''simple docstring'''





					super().__init__(**a_ )

					__UpperCAmelCase    :     Any													=	hidden_size
					__UpperCAmelCase    :     Any													=	num_hidden_layers
					__UpperCAmelCase    :     List[Any]													=	num_attention_heads
					__UpperCAmelCase    :     Union[str, Any]													=	intermediate_size
					__UpperCAmelCase    :     List[str]													=	hidden_act
					__UpperCAmelCase    :     int													=	hidden_dropout_prob
					__UpperCAmelCase    :     List[str]													=	attention_probs_dropout_prob
					__UpperCAmelCase    :     str													=	max_position_embeddings
					__UpperCAmelCase    :     int													=	type_vocab_size
					__UpperCAmelCase    :     Tuple													=	initializer_range
					__UpperCAmelCase    :     Optional[int]													=	relative_attention
					__UpperCAmelCase    :     int													=	max_relative_positions
					__UpperCAmelCase    :     Any													=	pad_token_id
					__UpperCAmelCase    :     int													=	position_biased_input

					# Backwards compatibility
					if type(a_ ) == str:
							__UpperCAmelCase    :     Optional[Any]													=	[x.strip() for x in pos_att_type.lower().split('''|''' )]

					__UpperCAmelCase    :     Tuple													=	pos_att_type
					__UpperCAmelCase    :     int													=	vocab_size
					__UpperCAmelCase    :     Optional[Any]													=	layer_norm_eps

					__UpperCAmelCase    :     str													=	kwargs.get('''pooler_hidden_size'''       ,       a_ )
					__UpperCAmelCase    :     Union[str, Any]													=	pooler_dropout
					__UpperCAmelCase    :     Tuple													=	pooler_hidden_act

class 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






			@property
			def  snake_case__     (   self							: Optional[Any] ):
					'''simple docstring'''





					if self.task == "multiple-choice":
							__UpperCAmelCase    :     List[Any]													=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
					else:
							__UpperCAmelCase    :     int													=	{0: '''batch''', 1: '''sequence'''}
					if self._config.type_vocab_size > 0:
							return OrderedDict(
							    [('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis), ('''token_type_ids''', dynamic_axis)] )
					else:
							return OrderedDict([('''input_ids''', dynamic_axis), ('''attention_mask''', dynamic_axis)] )




			@property
			def  snake_case__     (   self							: Union[str, Any] ):
					'''simple docstring'''





					return 12




			def  snake_case__     (   self							: Any       ,       a_							: Union["PreTrainedTokenizerBase", "FeatureExtractionMixin"]       ,       a_							: int = -1       ,       a_							: int = -1       ,       a_							: int = -1       ,       a_							: bool = False       ,       a_							: Optional["TensorType"] = None       ,       a_							: int = 3       ,       a_							: int = 40       ,       a_							: int = 40       ,       a_							: "PreTrainedTokenizerBase" = None       ,       ):
					'''simple docstring'''





					__UpperCAmelCase    :     List[Any]													=	super().generate_dummy_inputs(preprocessor=a_       ,       framework=a_ )
					if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
							del dummy_inputs["token_type_ids"]
					return dummy_inputs





