

from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available



@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 						__lowercase       (				UpperCAmelCase_			):




			"""simple docstring"""







			_UpperCAmelCase     :							Union[List[PIL.Image.Image], np.ndarray]
			_UpperCAmelCase     :							Optional[List[bool]]


if is_transformers_available() and is_torch_available():
						from .modeling_roberta_series import RobertaSeriesModelWithTransformation
						from .pipeline_alt_diffusion import AltDiffusionPipeline
						from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline









import io
import json
import subprocess


lowerCAmelCase							:						Dict     			=		[
    ["""en""", """ru"""],
    ["""ru""", """en"""],
    ["""en""", """de"""],
    ["""de""", """en"""],
]

lowerCAmelCase							:						List[str]     			=		8







def     A_   (					_UpperCAmelCase       ,			_UpperCAmelCase					):
						SCREAMING_SNAKE_CASE_:				Dict							= {}
						for src, tgt in pairs:
												SCREAMING_SNAKE_CASE_:				Tuple							= f"{src}-{tgt}"
												SCREAMING_SNAKE_CASE_:				List[str]							= f"sacrebleu -t wmt19 -l {pair} --echo src".split()
												SCREAMING_SNAKE_CASE_:				int							= subprocess.run(_UpperCAmelCase       ,			stdout=subprocess.PIPE					).stdout.decode("utf-8"					).splitlines()
												SCREAMING_SNAKE_CASE_:				Optional[Any]							= f"sacrebleu -t wmt19 -l {pair} --echo ref".split()
												SCREAMING_SNAKE_CASE_:				Dict							= subprocess.run(_UpperCAmelCase       ,			stdout=subprocess.PIPE					).stdout.decode("utf-8"					).splitlines()
												SCREAMING_SNAKE_CASE_:				Tuple							= {"src": src_lines[:n_objs], "tgt": tgt_lines[:n_objs]}
						return text


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






