





# 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,
)


_UpperCAmelCase				       = {
    '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:
     _UpperCAmelCase				       = ['DocumentQuestionAnsweringTool']
     _UpperCAmelCase				       = ['ImageCaptioningTool']
     _UpperCAmelCase				       = ['ImageQuestionAnsweringTool']
     _UpperCAmelCase				       = ['ImageSegmentationTool']
     _UpperCAmelCase				       = ['SpeechToTextTool']
     _UpperCAmelCase				       = ['TextClassificationTool']
     _UpperCAmelCase				       = ['TextQuestionAnsweringTool']
     _UpperCAmelCase				       = ['TextSummarizationTool']
     _UpperCAmelCase				       = ['TextToSpeechTool']
     _UpperCAmelCase				       = ['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

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








import io
import json
import subprocess


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

_UpperCAmelCase				       = 8




def        lowerCAmelCase_       (							UpperCamelCase_    ,						UpperCamelCase_     )   ->						Union[str, Any]:
       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


_UpperCAmelCase				       = get_all_data(pairs, n_objs)
_UpperCAmelCase				       = './fsmt_val_data.json'
with io.open(filename, 'w', encoding='utf-8') as f:
     _UpperCAmelCase				       = json.dump(text, f, indent=2, ensure_ascii=False)

