






# 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.
__UpperCamelCase					:		str	  =						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_ (      _A  )			->			Optional[Any]:







				"""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_ (      _A  )			->			int:







				"""simple docstring"""
				from transformers.testing_utils import pytest_addoption_shared

				pytest_addoption_shared(_A  )
def      a_ (      _A  )			->			Any:







				"""simple docstring"""
				from transformers.testing_utils import pytest_terminal_summary_main

				snake_case__									=     terminalreporter.config.getoption('--make-reports'  )
				if make_reports:
								pytest_terminal_summary_main(_A      ,   id=_A  )
def      a_ (      _A      ,   _A  )			->			Dict:







				"""simple docstring"""
				# If no tests are collected, pytest exists with code 5, which makes the CI fail.
				if exitstatus == 5:
								snake_case__									=     0


# Doctest custom flag to ignore output.
__UpperCamelCase					:		List[str]	  =						doctest.register_optionflag("""IGNORE_RESULT""")

__UpperCamelCase					:		List[Any]	  =						doctest.OutputChecker


class   __SCREAMING_SNAKE_CASE(	a_	):
							def lowerCAmelCase_ (     self:      Union[str, Any]       ,	UpperCamelCase:      List[Any]       ,	UpperCamelCase:      int       ,	UpperCamelCase:      str						)		->		List[str]:
											if IGNORE_RESULT & optionflags:
															return True
											return OutputChecker.check_output(self       ,	UpperCamelCase       ,	UpperCamelCase       ,	UpperCamelCase						)


__UpperCamelCase					:		List[Any]	  =						CustomOutputChecker
__UpperCamelCase					:		Optional[int]	  =						HfDoctestModule


__UpperCamelCase					:		List[str]	  =						HfDocTestParser












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCamelCase					:		int	  =						{"""configuration_xglm""": ["""XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XGLMConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Dict	  =						["""XGLMTokenizer"""]

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Optional[int]	  =						["""XGLMTokenizerFast"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		List[str]	  =						[
							    """XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """XGLMForCausalLM""",
							    """XGLMModel""",
							    """XGLMPreTrainedModel""",
							]


try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		Any	  =						[
							    """FlaxXGLMForCausalLM""",
							    """FlaxXGLMModel""",
							    """FlaxXGLMPreTrainedModel""",
							]


try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase					:		str	  =						[
							    """TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFXGLMForCausalLM""",
							    """TFXGLMModel""",
							    """TFXGLMPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xglm import XGLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_xglm_fast import XGLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_xglm import (
														    TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFXGLMForCausalLM,
														    TFXGLMModel,
														    TFXGLMPreTrainedModel,
														)


else:
							import sys

							__UpperCamelCase					:		Union[str, Any]	  =						_LazyModule(__name__, globals()["""__file__"""], _import_structure)




