




'''simple docstring'''




import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union






class      UpperCamelCase_  (enum.Enum  ):







						"""simple docstring"""


						_lowerCAmelCase         =       'timm'
						_lowerCAmelCase         =       'transformers'






def     snake_case__     (			lowerCamelCase__					: Optional[Iterable[str]]      ,		lowerCamelCase__					: Optional[Iterable[int]]      ,		lowerCamelCase__					: Optional[Iterable[str]]      ) -> Tuple:
					if stage_names is None:
										raise ValueError('''Stage_names must be set for transformers backbones'''      )

					if out_features is not None:
										if not isinstance(lowerCamelCase__      ,		(list,)      ):
															raise ValueError(f'out_features must be a list {type(lowerCamelCase__      )}'      )
										if any(feat not in stage_names for feat in out_features      ):
															raise ValueError(f'out_features must be a subset of stage_names: {stage_names} got {out_features}'      )

					if out_indices is not None:
										if not isinstance(lowerCamelCase__      ,		(list, tuple)      ):
															raise ValueError(f'out_indices must be a list or tuple, got {type(lowerCamelCase__      )}'      )
										if any(idx >= len(lowerCamelCase__      ) for idx in out_indices      ):
															raise ValueError('''out_indices must be valid indices for stage_names {stage_names}, got {out_indices}'''      )

					if out_features is not None and out_indices is not None:
										if len(lowerCamelCase__      ) != len(lowerCamelCase__      ):
															raise ValueError('''out_features and out_indices should have the same length if both are set'''      )
										if out_features != [stage_names[idx] for idx in out_indices]:
															raise ValueError('''out_features and out_indices should correspond to the same stages if both are set'''      )




def     snake_case__     (			lowerCamelCase__					: Optional[List[str]]      ,		lowerCamelCase__					: Optional[Union[List[int], Tuple[int]]]      ,		lowerCamelCase__					: List[str]      ,		) -> List[str]:
					if out_indices is None and out_features is None:
										A_			:  Optional[Any]			=				[len(lowerCamelCase__      ) - 1]
										A_			:  Dict			=				[stage_names[-1]]
					elif out_indices is None and out_features is not None:
										A_			:  Optional[Any]			=				[stage_names.index(lowerCamelCase__      ) for layer in out_features]
					elif out_features is None and out_indices is not None:
										A_			:  Union[str, Any]			=				[stage_names[idx] for idx in out_indices]
					return out_features, out_indices




def     snake_case__     (			lowerCamelCase__					: Optional[List[str]]      ,		lowerCamelCase__					: Optional[Union[List[int], Tuple[int]]]      ,		lowerCamelCase__					: List[str]      ,		) -> Tuple[List[str], List[int]]:
					verify_out_features_out_indices(out_features=lowerCamelCase__      ,		out_indices=lowerCamelCase__      ,		stage_names=lowerCamelCase__      )
					A_			,A_			:  Dict			=				_align_output_features_output_indices(
					    out_features=lowerCamelCase__      ,		out_indices=lowerCamelCase__      ,		stage_names=lowerCamelCase__      )
					# Verify that the aligned out_features and out_indices are valid
					verify_out_features_out_indices(out_features=lowerCamelCase__      ,		out_indices=lowerCamelCase__      ,		stage_names=lowerCamelCase__      )
					return output_features, output_indices






class      UpperCamelCase_  :







						"""simple docstring"""


						_lowerCAmelCase         =       None







						def    _a     (  self   :							Any				,			_lowerCamelCase   :							Dict     ):





											"""simple docstring"""







											if getattr(self				,			'''_backbone'''				,			_lowerCamelCase     ) is None:
																raise ValueError('''self._backbone must be set before calling _init_timm_backbone'''     )

											# These will diagree with the defaults for the transformers models e.g. for resnet50
											# the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
											# the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
											A_			:  Union[str, Any]			=				[stage['''module'''] for stage in self._backbone.feature_info.info]
											A_			:  List[Any]			=				[stage['''num_chs'''] for stage in self._backbone.feature_info.info]
											A_			:  int			=				self._backbone.feature_info.out_indices
											A_			:  Union[str, Any]			=				self._backbone.feature_info.module_name()

											# We verify the out indices and out features are valid
											verify_out_features_out_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=self.stage_names     )
											A_			,A_			:  Optional[int]			=				out_features, out_indices







						def    _a     (  self   :							Tuple				,			_lowerCamelCase   :							str     ):





											"""simple docstring"""







											A_			:  Union[str, Any]			=				getattr(_lowerCamelCase				,			'''stage_names'''     )
											A_			:  str			=				getattr(_lowerCamelCase				,			'''out_features'''				,			_lowerCamelCase     )
											A_			:  Tuple			=				getattr(_lowerCamelCase				,			'''out_indices'''				,			_lowerCamelCase     )

											A_			:  Union[str, Any]			=				stage_names
											A_			,A_			:  Tuple			=				get_aligned_output_features_output_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=_lowerCamelCase     )
											# Number of channels for each stage. This is set in the transformer backbone model init
											A_			:  Tuple			=				None







						def    _a     (  self   :							Union[str, Any]				,			_lowerCamelCase   :							Union[str, Any]     ):





											"""simple docstring"""







											A_			:  Optional[int]			=				config

											A_			:  Union[str, Any]			=				getattr(_lowerCamelCase				,			'''use_timm_backbone'''				,			_lowerCamelCase     )
											A_			:  Tuple			=				BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

											if self.backbone_type == BackboneType.TIMM:
																self._init_timm_backbone(_lowerCamelCase     )
											elif self.backbone_type == BackboneType.TRANSFORMERS:
																self._init_transformers_backbone(_lowerCamelCase     )
											else:
																raise ValueError(f'backbone_type {self.backbone_type} not supported.'     )







						@property
						def    _a     (  self   :							List[str]     ):





											"""simple docstring"""







											return self._out_features







						@out_features.setter
						def    _a     (  self   :							List[str]				,			_lowerCamelCase   :							List[str]     ):





											"""simple docstring"""







											A_			,A_			:  Tuple			=				get_aligned_output_features_output_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=self.stage_names     )







						@property
						def    _a     (  self   :							Union[str, Any]     ):





											"""simple docstring"""







											return self._out_indices







						@out_indices.setter
						def    _a     (  self   :							str				,			_lowerCamelCase   :							Union[Tuple[int], List[int]]     ):





											"""simple docstring"""







											A_			,A_			:  Tuple			=				get_aligned_output_features_output_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=self.stage_names     )







						@property
						def    _a     (  self   :							List[Any]     ):





											"""simple docstring"""







											return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names     )}







						@property
						def    _a     (  self   :							Union[str, Any]     ):





											"""simple docstring"""







											return [self.out_feature_channels[name] for name in self.out_features]







						def    _a     (  self   :							List[str]				,			*_lowerCamelCase   :							int				,			**_lowerCamelCase   :							List[str]     ):





											"""simple docstring"""







											A_			:  Optional[Any]			=				dict(inspect.signature(self.forward     ).parameters     )
											A_			:  str			=				{k: v for k, v in kwargs.items() if k in signature}
											return self(*_lowerCamelCase				,			**_lowerCamelCase     )







						def    _a     (  self   :							List[str]				,			_lowerCamelCase   :							str				,			_lowerCamelCase   :							Optional[bool] = None				,			_lowerCamelCase   :							Optional[bool] = None				,			_lowerCamelCase   :							Optional[bool] = None				,			):





											"""simple docstring"""







											raise NotImplementedError('''This method should be implemented by the derived class.'''     )







						def    _a     (  self   :							Tuple     ):





											"""simple docstring"""







											A_			:  Optional[int]			=				super().to_dict()
											A_			:  Union[str, Any]			=				output.pop('''_out_features'''     )
											A_			:  Optional[Any]			=				output.pop('''_out_indices'''     )
											return output






class      UpperCamelCase_  :







						"""simple docstring"""


						@property
						def    _a     (  self   :							Union[str, Any]     ):





											"""simple docstring"""







											return self._out_features







						@out_features.setter
						def    _a     (  self   :							Any				,			_lowerCamelCase   :							List[str]     ):





											"""simple docstring"""







											A_			,A_			:  Union[str, Any]			=				get_aligned_output_features_output_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=self.stage_names     )







						@property
						def    _a     (  self   :							Any     ):





											"""simple docstring"""







											return self._out_indices







						@out_indices.setter
						def    _a     (  self   :							Optional[int]				,			_lowerCamelCase   :							Union[Tuple[int], List[int]]     ):





											"""simple docstring"""







											A_			,A_			:  List[str]			=				get_aligned_output_features_output_indices(
											    out_features=_lowerCamelCase				,			out_indices=_lowerCamelCase				,			stage_names=self.stage_names     )







						def    _a     (  self   :							int     ):





											"""simple docstring"""







											A_			:  Optional[Any]			=				super().to_dict()
											A_			:  Optional[Any]			=				output.pop('''_out_features'''     )
											A_			:  Tuple			=				output.pop('''_out_indices'''     )
											return output









'''simple docstring'''




import io
import json
import subprocess


snake_case__ 							=    [
    ["""en""", """ru"""],
    ["""ru""", """en"""],
    ["""en""", """de"""],
    ["""de""", """en"""],
]

snake_case__ 							=    8




def     snake_case__     (			lowerCamelCase__					: Union[str, Any]      ,		lowerCamelCase__					: Optional[int]      ) -> List[Any]:
					A_			:  Tuple			=				{}
					for src, tgt in pairs:
										A_			:  List[str]			=				f'{src}-{tgt}'
										A_			:  Optional[int]			=				f'sacrebleu -t wmt19 -l {pair} --echo src'.split()
										A_			:  int			=				subprocess.run(lowerCamelCase__      ,		stdout=subprocess.PIPE      ).stdout.decode('''utf-8'''      ).splitlines()
										A_			:  List[str]			=				f'sacrebleu -t wmt19 -l {pair} --echo ref'.split()
										A_			:  Any			=				subprocess.run(lowerCamelCase__      ,		stdout=subprocess.PIPE      ).stdout.decode('''utf-8'''      ).splitlines()
										A_			:  List[Any]			=				{'''src''': src_lines[:n_objs], '''tgt''': tgt_lines[:n_objs]}
					return text


snake_case__ 							=    get_all_data(pairs, n_objs)
snake_case__ 							=    """./fsmt_val_data.json"""
with io.open(filename, """w""", encoding="""utf-8""") as f:
							snake_case__ 							=    json.dump(text, f, indent=2, ensure_ascii=False)



