

import io
import json
import subprocess


__A    :   Optional[int]          =       [
    ["en", "ru"],
    ["ru", "en"],
    ["en", "de"],
    ["de", "en"],
]

__A    :   Optional[Any]          =       8





def 						__SCREAMING_SNAKE_CASE  (    UpperCamelCase__      ,      UpperCamelCase__			)  ->    Dict:







			'''simple docstring'''

			UpperCAmelCase       		=    {}
			for src, tgt in pairs:
						UpperCAmelCase       		=    F"""{src}-{tgt}"""
						UpperCAmelCase       		=    F"""sacrebleu -t wmt19 -l {pair} --echo src""".split()
						UpperCAmelCase       		=    subprocess.run(UpperCamelCase__      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
						UpperCAmelCase       		=    F"""sacrebleu -t wmt19 -l {pair} --echo ref""".split()
						UpperCAmelCase       		=    subprocess.run(UpperCamelCase__      ,      stdout=subprocess.PIPE			).stdout.decode('''utf-8'''			).splitlines()
						UpperCAmelCase       		=    {'''src''': src_lines[:n_objs], '''tgt''': tgt_lines[:n_objs]}
			return text


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










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


__A    :   Tuple          =       {
    "configuration_mobilevitv2": [
        "MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileViTV2Config",
        "MobileViTV2OnnxConfig",
    ],
}


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__A    :   List[str]          =       [
				    "MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "MobileViTV2ForImageClassification",
				    "MobileViTV2ForSemanticSegmentation",
				    "MobileViTV2Model",
				    "MobileViTV2PreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_mobilevitva import (
				    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    MobileViTVaConfig,
				    MobileViTVaOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mobilevitva import (
								    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MobileViTVaForImageClassification,
								    MobileViTVaForSemanticSegmentation,
								    MobileViTVaModel,
								    MobileViTVaPreTrainedModel,
								)

else:
				import sys

				__A    :   Tuple          =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



