# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

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


_snake_case			=						{
    '''agents''': ['''Agent''', '''AzureOpenAiAgent''', '''HfAgent''', '''LocalAgent''', '''OpenAiAgent'''],
    '''base''': ['''PipelineTool''', '''RemoteTool''', '''Tool''', '''launch_gradio_demo''', '''load_tool'''],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						['''DocumentQuestionAnsweringTool''']
	_snake_case			=						['''ImageCaptioningTool''']
	_snake_case			=						['''ImageQuestionAnsweringTool''']
	_snake_case			=						['''ImageSegmentationTool''']
	_snake_case			=						['''SpeechToTextTool''']
	_snake_case			=						['''TextClassificationTool''']
	_snake_case			=						['''TextQuestionAnsweringTool''']
	_snake_case			=						['''TextSummarizationTool''']
	_snake_case			=						['''TextToSpeechTool''']
	_snake_case			=						['''TranslationTool''']

if TYPE_CHECKING:
	from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
	from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .document_question_answering import DocumentQuestionAnsweringTool
		from .image_captioning import ImageCaptioningTool
		from .image_question_answering import ImageQuestionAnsweringTool
		from .image_segmentation import ImageSegmentationTool
		from .speech_to_text import SpeechToTextTool
		from .text_classification import TextClassificationTool
		from .text_question_answering import TextQuestionAnsweringTool
		from .text_summarization import TextSummarizationTool
		from .text_to_speech import TextToSpeechTool
		from .translation import TranslationTool
else:
	import sys

	_snake_case			=						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





import io
import json
import subprocess


_snake_case			=						[
    ['''en''', '''ru'''],
    ['''ru''', '''en'''],
    ['''en''', '''de'''],
    ['''de''', '''en'''],
]

_snake_case			=						8




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




