






'''simple docstring'''







import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


__lowerCAmelCase       		=      HUGGINGFACE_HUB_CACHE


__lowerCAmelCase       		=      'config.json'
__lowerCAmelCase       		=      'diffusion_pytorch_model.bin'
__lowerCAmelCase       		=      'diffusion_flax_model.msgpack'
__lowerCAmelCase       		=      'model.onnx'
__lowerCAmelCase       		=      'diffusion_pytorch_model.safetensors'
__lowerCAmelCase       		=      'weights.pb'
__lowerCAmelCase       		=      'https://huggingface.co'
__lowerCAmelCase       		=      default_cache_path
__lowerCAmelCase       		=      'diffusers_modules'
__lowerCAmelCase       		=      os.getenv('HF_MODULES_CACHE', os.path.join(hf_cache_home, 'modules'))
__lowerCAmelCase       		=      ['fp16', 'non-ema']
__lowerCAmelCase       		=      '.self_attn'












'''simple docstring'''







from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import pyarrow as pa


if TYPE_CHECKING:
		from .features import FeatureType





@dataclass
class 	SCREAMING_SNAKE_CASE					:
			snake_case__  =				42
			snake_case__  =				None
			# Automatically constructed
			snake_case__  =				"dict"
			snake_case__  =				None
			snake_case__  =				field(default="Translation"	,   init=SCREAMING_SNAKE_CASE_	,   repr=SCREAMING_SNAKE_CASE_       )






			def __call__( self      :			Dict					)			->			Tuple:
							return pa.struct({lang: pa.string() for lang in sorted(self.languages					)}					)







			def 			SCREAMING_SNAKE_CASE      ( self      :			Union[str, Any]					)			->			Union["FeatureType", Dict[str, "FeatureType"]]:
							from .features import Value

							return {k: Value('''string'''					) for k in sorted(self.languages					)}





@dataclass
class 	SCREAMING_SNAKE_CASE					:
			snake_case__  =				None
			snake_case__  =				None
			snake_case__  =				None
			# Automatically constructed
			snake_case__  =				"dict"
			snake_case__  =				None
			snake_case__  =				field(default="TranslationVariableLanguages"	,   init=SCREAMING_SNAKE_CASE_	,   repr=SCREAMING_SNAKE_CASE_       )






			def 			SCREAMING_SNAKE_CASE      ( self      :			Tuple					)			->			Dict:
							a_		:  List[str]											=      sorted(set(self.languages					)					) if self.languages else None
							a_		:  Optional[Any]											=      len(self.languages					) if self.languages else None






			def __call__( self      :			Any					)			->			Optional[Any]:
							return pa.struct({'''language''': pa.list_(pa.string()					), '''translation''': pa.list_(pa.string()					)}					)






			def 			SCREAMING_SNAKE_CASE      ( self      :			Optional[int]  ,						__SCREAMING_SNAKE_CASE      :			Optional[Any]					)			->			Optional[Any]:
							a_		:  str											=      set(self.languages					)
							if self.languages and set(__SCREAMING_SNAKE_CASE					) - lang_set:
											raise ValueError(
											    f'Some languages in example ({", ".join(sorted(set(__SCREAMING_SNAKE_CASE					) - lang_set					)					)}) are not in valid set ({", ".join(__SCREAMING_SNAKE_CASE					)}).'					)

							# Convert dictionary into tuples, splitting out cases where there are
							# multiple translations for a single language.
							a_		:  int											=      []
							for lang, text in translation_dict.items():
											if isinstance(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE					):
															translation_tuples.append((lang, text)					)
											else:
															translation_tuples.extend([(lang, el) for el in text]					)

        # Ensure translations are in ascending order by language code.
							a_				,			a_		:  List[Any]											=      zip(*sorted(__SCREAMING_SNAKE_CASE					)					)

							return {"language": languages, "translation": translations}







			def 			SCREAMING_SNAKE_CASE      ( self      :			Any					)			->			Union["FeatureType", Dict[str, "FeatureType"]]:
							from .features import Sequence, Value

							return {
							    "language": Sequence(Value('''string'''					)					),
							    "translation": Sequence(Value('''string'''					)					),
							}




