



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase   :							Union[str, Any]							 ={
    """configuration_efficientformer""": [
        """EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientFormerConfig""",
    ]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   :							List[str]							 =["""EfficientFormerImageProcessor"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   :							int							 =[
	    """EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """EfficientFormerForImageClassification""",
	    """EfficientFormerForImageClassificationWithTeacher""",
	    """EfficientFormerModel""",
	    """EfficientFormerPreTrainedModel""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	UpperCAmelCase   :							Union[str, Any]							 =[
	    """TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFEfficientFormerForImageClassification""",
	    """TFEfficientFormerForImageClassificationWithTeacher""",
	    """TFEfficientFormerModel""",
	    """TFEfficientFormerPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .image_processing_efficientformer import EfficientFormerImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_efficientformer import (
		    EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    EfficientFormerForImageClassification,
		    EfficientFormerForImageClassificationWithTeacher,
		    EfficientFormerModel,
		    EfficientFormerPreTrainedModel,
		)
	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_efficientformer import (
		    TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFEfficientFormerForImageClassification,
		    TFEfficientFormerForImageClassificationWithTeacher,
		    TFEfficientFormerModel,
		    TFEfficientFormerPreTrainedModel,
		)

else:
	import sys

	UpperCAmelCase   :							Any							 =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCAmelCase   :							Optional[Any]							 =pytest.mark.integration



@pytest.mark.parametrize("path"   ,	["paws", "csv"])
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase):
					inspect_dataset(_lowerCAmelCase   ,	_lowerCAmelCase)
					UpperCamelCase_		  =   path + ".py"
					assert script_name in os.listdir(_lowerCAmelCase)
					assert "__pycache__" not in os.listdir(_lowerCAmelCase)



@pytest.mark.filterwarnings("ignore:inspect_metric is deprecated:FutureWarning")
@pytest.mark.filterwarnings("ignore:metric_module_factory is deprecated:FutureWarning")
@pytest.mark.parametrize("path"   ,	["accuracy"])
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase):
					inspect_metric(_lowerCAmelCase   ,	_lowerCAmelCase)
					UpperCamelCase_		  =   path + ".py"
					assert script_name in os.listdir(_lowerCAmelCase)
					assert "__pycache__" not in os.listdir(_lowerCAmelCase)



@pytest.mark.parametrize(
    "path, config_name, expected_splits"   ,	[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase):
					UpperCamelCase_		  =   get_dataset_config_info(_lowerCAmelCase   ,	config_name=_lowerCAmelCase)
					assert info.config_name == config_name
					assert list(info.splits.keys()) == expected_splits



@pytest.mark.parametrize(
    "path, config_name, expected_exception"   ,	[
        ("paws", None, ValueError),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase):
					with pytest.raises(_lowerCAmelCase):
										get_dataset_config_info(_lowerCAmelCase   ,	config_name=_lowerCAmelCase)



@pytest.mark.parametrize(
    "path, expected"   ,	[
        ("squad", "plain_text"),
        ("acronym_identification", "default"),
        ("lhoestq/squad", "plain_text"),
        ("lhoestq/test", "default"),
        ("lhoestq/demo1", "lhoestq--demo1"),
        ("dalle-mini/wit", "dalle-mini--wit"),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase):
					UpperCamelCase_		  =   get_dataset_config_names(_lowerCAmelCase)
					assert expected in config_names



@pytest.mark.parametrize(
    "path, expected_configs, expected_splits_in_first_config"   ,	[
        ("squad", ["plain_text"], ["train", "validation"]),
        ("dalle-mini/wit", ["dalle-mini--wit"], ["train"]),
        ("paws", ["labeled_final", "labeled_swap", "unlabeled_final"], ["train", "test", "validation"]),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase):
					UpperCamelCase_		  =   get_dataset_infos(_lowerCAmelCase)
					assert list(infos.keys()) == expected_configs
					UpperCamelCase_		  =   expected_configs[0]
					assert expected_config in infos
					UpperCamelCase_		  =   infos[expected_config]
					assert info.config_name == expected_config
					assert list(info.splits.keys()) == expected_splits_in_first_config



@pytest.mark.parametrize(
    "path, expected_config, expected_splits"   ,	[
        ("squad", "plain_text", ["train", "validation"]),
        ("dalle-mini/wit", "dalle-mini--wit", ["train"]),
        ("paws", "labeled_final", ["train", "test", "validation"]),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase):
					UpperCamelCase_		  =   get_dataset_infos(_lowerCAmelCase)
					assert expected_config in infos
					UpperCamelCase_		  =   infos[expected_config]
					assert info.config_name == expected_config
					assert list(info.splits.keys()) == expected_splits






@pytest.mark.parametrize(
    "path, config_name, expected_exception"   ,	[
        ("paws", None, ValueError),
    ]   ,	)
def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase   ,	_lowerCAmelCase):
					with pytest.raises(_lowerCAmelCase):
										get_dataset_split_names(_lowerCAmelCase   ,	config_name=_lowerCAmelCase)
