


# 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.
_lowercase				     = abspath(join(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 		__lowerCAmelCase   (							_UpperCamelCase		)    ->				Tuple:






      '''simple docstring'''

      from diffusers.utils.testing_utils import pytest_addoption_shared

      pytest_addoption_shared(_lowerCAmelCase		)


def 		__lowerCAmelCase   (							_UpperCamelCase		)    ->				Dict:






      '''simple docstring'''

      from diffusers.utils.testing_utils import pytest_terminal_summary_main

      lowerCamelCase__:						int							   = terminalreporter.config.getoption("""--make-reports"""		)
      if make_reports:
            pytest_terminal_summary_main(_lowerCAmelCase       ,			id=_lowerCAmelCase		)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A				:       List[str]      =  {
    'configuration_time_series_transformer': [
        'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TimeSeriesTransformerConfig',
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       str      =  [
	    'TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'TimeSeriesTransformerForPrediction',
	    'TimeSeriesTransformerModel',
	    'TimeSeriesTransformerPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_time_series_transformer import (
	    TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    TimeSeriesTransformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_time_series_transformer import (
		    TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TimeSeriesTransformerForPrediction,
		    TimeSeriesTransformerModel,
		    TimeSeriesTransformerPreTrainedModel,
		)

else:
	import sys

	A				:       str      =  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





