

import numpy as np



def        _lowerCAmelCase      (						UpperCAmelCase     :							Optional[Any]      ,							UpperCAmelCase     :							Tuple				):


					'''simple docstring'''






					UpperCamelCase__		:    Dict         =np.array(UpperCAmelCase				)
					UpperCamelCase__		:    Tuple         =np.array(UpperCAmelCase				)

					UpperCamelCase__		:    int         =abs(predict - actual				)
					UpperCamelCase__		:    Optional[int]         =difference.mean()

					return score



def        _lowerCAmelCase      (						UpperCAmelCase     :							Tuple      ,							UpperCAmelCase     :							Dict				):


					'''simple docstring'''






					UpperCamelCase__		:    List[Any]         =np.array(UpperCAmelCase				)
					UpperCamelCase__		:    int         =np.array(UpperCAmelCase				)

					UpperCamelCase__		:    Optional[int]         =predict - actual
					UpperCamelCase__		:    Optional[Any]         =np.square(UpperCAmelCase				)

					UpperCamelCase__		:    List[Any]         =square_diff.mean()
					return score



def        _lowerCAmelCase      (						UpperCAmelCase     :							List[str]      ,							UpperCAmelCase     :							int				):


					'''simple docstring'''






					UpperCamelCase__		:    Union[str, Any]         =np.array(UpperCAmelCase				)
					UpperCamelCase__		:    Optional[int]         =np.array(UpperCAmelCase				)

					UpperCamelCase__		:    Tuple         =predict - actual
					UpperCamelCase__		:    Tuple         =np.square(UpperCAmelCase				)
					UpperCamelCase__		:    Dict         =square_diff.mean()
					UpperCamelCase__		:    Dict         =np.sqrt(UpperCAmelCase				)
					return score



def        _lowerCAmelCase      (						UpperCAmelCase     :							int      ,							UpperCAmelCase     :							Dict				):


					'''simple docstring'''






					UpperCamelCase__		:    str         =np.array(UpperCAmelCase				)
					UpperCamelCase__		:    Dict         =np.array(UpperCAmelCase				)

					UpperCamelCase__		:    Any         =np.log(predict + 1				)
					UpperCamelCase__		:    str         =np.log(actual + 1				)

					UpperCamelCase__		:    Optional[Any]         =log_predict - log_actual
					UpperCamelCase__		:    int         =np.square(UpperCAmelCase				)
					UpperCamelCase__		:    Union[str, Any]         =square_diff.mean()

					UpperCamelCase__		:    Any         =np.sqrt(UpperCAmelCase				)

					return score



def        _lowerCAmelCase      (						UpperCAmelCase     :							str      ,							UpperCAmelCase     :							Dict				):


					'''simple docstring'''






					UpperCamelCase__		:    List[Any]         =np.array(UpperCAmelCase				)
					UpperCamelCase__		:    Optional[Any]         =np.array(UpperCAmelCase				)

					UpperCamelCase__		:    Union[str, Any]         =predict - actual
					UpperCamelCase__		:    Union[str, Any]         =np.sum(UpperCAmelCase				) / len(UpperCAmelCase				)
					UpperCamelCase__		:    List[str]         =np.sum(UpperCAmelCase				) / len(UpperCAmelCase				)
					# print(numerator, denumerator)
					UpperCamelCase__		:    List[str]         =float(UpperCAmelCase				) / denumerator * 100

					return score







def        _lowerCAmelCase      (						UpperCAmelCase     :							List[str]      ,							UpperCAmelCase     :							Union[str, Any]				):


					'''simple docstring'''






					return np.mean(np.array(UpperCAmelCase				) == np.array(UpperCAmelCase				)				)





"""simple docstring"""





import io
import json
import subprocess


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

_SCREAMING_SNAKE_CASE       :  str        = 8



def        _lowerCAmelCase      (						UpperCAmelCase     :							Tuple      ,							UpperCAmelCase     :							List[Any]				):


					'''simple docstring'''






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


_SCREAMING_SNAKE_CASE       :  List[str]        = 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       :  Any        = json.dump(text, f, indent=2, ensure_ascii=False)


