



"""simple docstring"""







import os

from packaging import version

from .. import __version__
from .accelerate_utils import apply_forward_hook
from .constants import (
    CONFIG_NAME,
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    DIFFUSERS_DYNAMIC_MODULE_NAME,
    FLAX_WEIGHTS_NAME,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    ONNX_EXTERNAL_WEIGHTS_NAME,
    ONNX_WEIGHTS_NAME,
    SAFETENSORS_WEIGHTS_NAME,
    TEXT_ENCODER_ATTN_MODULE,
    WEIGHTS_NAME,
)
from .deprecation_utils import deprecate
from .doc_utils import replace_example_docstring
from .dynamic_modules_utils import get_class_from_dynamic_module
from .hub_utils import (
    HF_HUB_OFFLINE,
    _add_variant,
    _get_model_file,
    extract_commit_hash,
    http_user_agent,
)
from .import_utils import (
    BACKENDS_MAPPING,
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    is_accelerate_available,
    is_accelerate_version,
    is_bsa_available,
    is_flax_available,
    is_ftfy_available,
    is_inflect_available,
    is_invisible_watermark_available,
    is_k_diffusion_available,
    is_k_diffusion_version,
    is_librosa_available,
    is_note_seq_available,
    is_omegaconf_available,
    is_onnx_available,
    is_safetensors_available,
    is_scipy_available,
    is_tensorboard_available,
    is_tf_available,
    is_torch_available,
    is_torch_version,
    is_torchsde_available,
    is_transformers_available,
    is_transformers_version,
    is_unidecode_available,
    is_wandb_available,
    is_xformers_available,
    requires_backends,
)
from .logging import get_logger
from .outputs import BaseOutput
from .pil_utils import PIL_INTERPOLATION, numpy_to_pil, pt_to_pil
from .torch_utils import is_compiled_module, randn_tensor


if is_torch_available():
			from .testing_utils import (
			    floats_tensor,
			    load_hf_numpy,
			    load_image,
			    load_numpy,
			    load_pt,
			    nightly,
			    parse_flag_from_env,
			    print_tensor_test,
			    require_torch_a,
			    require_torch_gpu,
			    skip_mps,
			    slow,
			    torch_all_close,
			    torch_device,
			)
			from .torch_utils import maybe_allow_in_graph

from .testing_utils import export_to_gif, export_to_video


A    =	get_logger(__name__)

def    __SCREAMING_SNAKE_CASE		( lowerCamelCase_:       Optional[int]   ):
						"""simple docstring"""






						if version.parse(lowerCamelCase_   ) < version.parse(lowerCamelCase_   ):
												if "dev" in min_version:
																		snake_case      : Dict							=   (
																		    "This example requires a source install from HuggingFace diffusers (see "
																		    "`https://huggingface.co/docs/diffusers/installation#install-from-source`),"
																		)
												else:
																		snake_case      : Dict							=   f'''This example requires a minimum version of {min_version},'''
												error_message += f''' but the version found is {__version__}.\n'''
												raise ImportError(lowerCamelCase_   )








"""simple docstring"""







import unittest

from cer import CER


A    =	CER()

class 			_a     (   unittest.TestCase):



			def 							__lowercase				( self       :							Optional[Any]		)       ->				Tuple:
									snake_case      : Union[str, Any]							=   ["White House"]
									snake_case      : Tuple							=   ["white house"]
									# S = 2, D = 0, I = 0, N = 11, CER = 2 / 11
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.1818181818		) < 1E-6		)



			def 							__lowercase				( self       :							Optional[Any]		)       ->				Dict:
									snake_case      : Tuple							=   ["were wolf"]
									snake_case      : Union[str, Any]							=   ["werewolf"]
									# S = 0, D = 0, I = 1, N = 9, CER = 1 / 9
									snake_case      : List[str]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.1111111		) < 1E-6		)

									snake_case      : List[str]							=   ["werewolf"]
									snake_case      : Optional[Any]							=   ["weae     wolf"]
									# S = 1, D = 1, I = 0, N = 8, CER = 0.25
									snake_case      : Optional[int]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.25		) < 1E-6		)

									# consecutive whitespaces case 1
									snake_case      : Optional[int]							=   ["were wolf"]
									snake_case      : Dict							=   ["were               wolf"]
									# S = 0, D = 0, I = 0, N = 9, CER = 0
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.0		) < 1E-6		)

									# consecutive whitespaces case 2
									snake_case      : Dict							=   ["were   wolf"]
									snake_case      : Dict							=   ["were               wolf"]
									# S = 0, D = 0, I = 0, N = 9, CER = 0
									snake_case      : Optional[int]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.0		) < 1E-6		)



			def 							__lowercase				( self       :							List[Any]		)       ->				Union[str, Any]:
									snake_case      : str							=   ["werewolf"]
									snake_case      : List[Any]							=   ["weaewolf"]
									# S = 1, D = 0, I = 0, N = 8, CER = 0.125
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							int		)       ->				int:
									snake_case      : Dict							=   ["werewolf"]
									snake_case      : Optional[Any]							=   ["wereawolf"]
									# S = 0, D = 1, I = 0, N = 8, CER = 0.125
									snake_case      : List[str]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							Union[str, Any]		)       ->				List[Any]:
									snake_case      : Tuple							=   ["werewolf"]
									snake_case      : Union[str, Any]							=   ["wereolf"]
									# S = 0, D = 0, I = 1, N = 8, CER = 0.125
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.125		) < 1E-6		)



			def 							__lowercase				( self       :							int		)       ->				List[str]:
									snake_case      : int							=   ["werewolf"]
									snake_case      : Optional[Any]							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertEqual(_lowercase      ,  0.0		)



			def 							__lowercase				( self       :							List[Any]		)       ->				Optional[Any]:
									snake_case      : str							=   ["werewolf", "I am your father"]
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertEqual(_lowercase      ,  0.0		)

									snake_case      : Union[str, Any]							=   ["werewolf", "I am your father", "doge"]
									snake_case      : str							=   ["werxwolf", "I       am your father", "doge"]
									# S = 1, D = 0, I = 0, N = 28, CER = 1 / 28
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.03571428		) < 1E-6		)



			def 							__lowercase				( self       :							Any		)       ->				Union[str, Any]:
									snake_case      : Union[str, Any]							=   ["My hovercraft", "is full of eels"]
									snake_case      : List[str]							=   ["My hovercraft is full", " of eels"]
									# S = 0, D = 0, I = 2, N = 28, CER = 2 / 28
									# whitespace at the front of " of eels" will be strip during preporcessing
									# so need to insert 2 whitespaces
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase      ,  concatenate_texts=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.071428		) < 1E-6		)



			def 							__lowercase				( self       :							Any		)       ->				Dict:
									snake_case      : Dict							=   ["我能吞下玻璃而不伤身体"]
									snake_case      : List[str]							=   [" 能吞虾玻璃而 不霜身体啦"]
									# S = 3, D = 2, I = 0, N = 11, CER = 5 / 11
									snake_case      : str							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.4545454545		) < 1E-6		)

									snake_case      : List[Any]							=   ["我能吞下玻璃", "而不伤身体"]
									snake_case      : int							=   ["我    能 吞 下 玻 璃", "而不伤身体"]
									# S = 0, D = 5, I = 0, N = 11, CER = 5 / 11
									snake_case      : Dict							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertTrue(abs(char_error_rate - 0.454545454545		) < 1E-6		)

									snake_case      : int							=   ["我能吞下玻璃而不伤身体"]
									snake_case      : int							=   cer.compute(predictions=_lowercase      ,  references=_lowercase		)
									self.assertFalse(_lowercase      ,  0.0		)



			def 							__lowercase				( self       :							List[Any]		)       ->				List[Any]:
									snake_case      : int							=   [""]
									snake_case      : Optional[int]							=   ["Hypothesis"]
									with self.assertRaises(_lowercase		):
															cer.compute(predictions=_lowercase      ,  references=_lowercase		)


if __name__ == "__main__":
			unittest.main()



