"""simple docstring"""







import io
import json
import subprocess


_SCREAMING_SNAKE_CASE	:		List[Any]   =   [
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

_SCREAMING_SNAKE_CASE	:		Dict   =   8



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


_SCREAMING_SNAKE_CASE	:		Any   =   get_all_data(pairs, n_objs)
_SCREAMING_SNAKE_CASE	:		Optional[Any]   =   '''./fsmt_val_data.json'''
with io.open(filename, '''w''', encoding='''utf-8''') as f:
     _SCREAMING_SNAKE_CASE	:		List[str]   =   json.dump(text, f, indent=2, ensure_ascii=False)











"""simple docstring"""






from typing import TYPE_CHECKING

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


_lowercase					:					Any 		=		{
    "configuration_unispeech_sat": ["UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechSatConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_lowercase					:					Any 		=		[
		    "UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "UniSpeechSatForAudioFrameClassification",
		    "UniSpeechSatForCTC",
		    "UniSpeechSatForPreTraining",
		    "UniSpeechSatForSequenceClassification",
		    "UniSpeechSatForXVector",
		    "UniSpeechSatModel",
		    "UniSpeechSatPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_unispeech_sat import (
				    UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    UniSpeechSatForAudioFrameClassification,
				    UniSpeechSatForCTC,
				    UniSpeechSatForPreTraining,
				    UniSpeechSatForSequenceClassification,
				    UniSpeechSatForXVector,
				    UniSpeechSatModel,
				    UniSpeechSatPreTrainedModel,
				)

else:
		import sys

		_lowercase					:					int 		=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




