"""simple docstring"""





import os
import sys
import unittest


_UpperCamelCase     :		str											=					os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
_UpperCamelCase     :		Union[str, Any]											=					os.path.join(git_repo_path, "src", "diffusers")


class   UpperCAmelCase_			(					unittest.TestCase):


						def 	_UpperCAmelCase (     self							) ->      Any:
													lowercase__    :	Optional[int]     					=			find_backend('    if not is_torch_available():'							)
													self.assertEqual(a_	,    'torch'							)

													# backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
													# self.assertEqual(backend_with_underscore, "tensorflow_text")

													lowercase__    :	Any     					=			find_backend('    if not (is_torch_available() and is_transformers_available()):'							)
													self.assertEqual(a_	,    'torch_and_transformers'							)

													# double_backend_with_underscore = find_backend(
													#    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"
													# )
													# self.assertEqual(double_backend_with_underscore, "sentencepiece_and_tensorflow_text")

													lowercase__    :	Union[str, Any]     					=			find_backend(
													    '    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):'							)
													self.assertEqual(a_	,    'torch_and_transformers_and_onnx'							)


						def 	_UpperCAmelCase (     self							) ->      List[str]:
													lowercase__    :	Dict     					=			read_init()
													# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
													self.assertIn('torch'	,    a_							)
													self.assertIn('torch_and_transformers'	,    a_							)
													self.assertIn('flax_and_transformers'	,    a_							)
													self.assertIn('torch_and_transformers_and_onnx'	,    a_							)

													# Likewise, we can't assert on the exact content of a key
													self.assertIn('UNet2DModel'	,    objects['torch']							)
													self.assertIn('FlaxUNet2DConditionModel'	,    objects['flax']							)
													self.assertIn('StableDiffusionPipeline'	,    objects['torch_and_transformers']							)
													self.assertIn('FlaxStableDiffusionPipeline'	,    objects['flax_and_transformers']							)
													self.assertIn('LMSDiscreteScheduler'	,    objects['torch_and_scipy']							)
													self.assertIn('OnnxStableDiffusionPipeline'	,    objects['torch_and_transformers_and_onnx']							)


						def 	_UpperCAmelCase (     self							) ->      str:
													lowercase__    :	Optional[Any]     					=			create_dummy_object('CONSTANT'	,    '\'torch\''							)
													self.assertEqual(a_	,    '\nCONSTANT = None\n'							)

													lowercase__    :	Optional[int]     					=			create_dummy_object('function'	,    '\'torch\''							)
													self.assertEqual(
													    a_	,    '\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'							)

													lowercase__    :	List[Any]     					=			"""
class FakeClass(metaclass=DummyObject):
    _backends = 'torch'

    def __init__(self, *args, **kwargs):
        requires_backends(self, 'torch')

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, 'torch')

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, 'torch')
"""
													lowercase__    :	Union[str, Any]     					=			create_dummy_object('FakeClass'	,    '\'torch\''							)
													self.assertEqual(a_	,    a_							)


						def 	_UpperCAmelCase (     self							) ->      Dict:
													lowercase__    :	Union[str, Any]     					=			"""# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, [\"torch\"])


class FakeClass(metaclass=DummyObject):
    _backends = [\"torch\"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, [\"torch\"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, [\"torch\"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, [\"torch\"])
"""
													lowercase__    :	List[Any]     					=			create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']}							)
													self.assertEqual(dummy_files['torch']	,    a_							)


"""simple docstring"""





from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
    LineByLineTextDataset,
    LineByLineWithRefDataset,
    LineByLineWithSOPTextDataset,
    TextDataset,
    TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments

