





'''simple docstring'''

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

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


# 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(dirname(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     __magic_name__							(				__UpperCAmelCase   )    ->       int:

   '''simple docstring'''







   from transformers.testing_utils import pytest_addoption_shared

   pytest_addoption_shared(__UpperCAmelCase   )







def     __magic_name__							(				__UpperCAmelCase   )    ->       List[Any]:

   '''simple docstring'''







   from transformers.testing_utils import pytest_terminal_summary_main

   __SCREAMING_SNAKE_CASE   				=							terminalreporter.config.getoption("""--make-reports"""   )
   if make_reports:
      pytest_terminal_summary_main(__UpperCAmelCase				,						id=__UpperCAmelCase   )












'''simple docstring'''

from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a   	=    {
    "configuration_informer": [
        "INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "InformerConfig",
    ],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    a   	=    [
        "INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
        "InformerForPrediction",
        "InformerModel",
        "InformerPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_informer import (
            INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            InformerForPrediction,
            InformerModel,
            InformerPreTrainedModel,
        )

else:
    import sys

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





