

"""simple docstring"""



# 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,
)


SCREAMING_SNAKE_CASE_       :						List[str]					=    {
    '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:
 SCREAMING_SNAKE_CASE_       :						Any					=    ['DocumentQuestionAnsweringTool']
 SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    ['ImageCaptioningTool']
 SCREAMING_SNAKE_CASE_       :						int					=    ['ImageQuestionAnsweringTool']
 SCREAMING_SNAKE_CASE_       :						Tuple					=    ['ImageSegmentationTool']
 SCREAMING_SNAKE_CASE_       :						Optional[int]					=    ['SpeechToTextTool']
 SCREAMING_SNAKE_CASE_       :						Dict					=    ['TextClassificationTool']
 SCREAMING_SNAKE_CASE_       :						Tuple					=    ['TextQuestionAnsweringTool']
 SCREAMING_SNAKE_CASE_       :						str					=    ['TextSummarizationTool']
 SCREAMING_SNAKE_CASE_       :						Union[str, Any]					=    ['TextToSpeechTool']
 SCREAMING_SNAKE_CASE_       :						Optional[int]					=    ['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

 SCREAMING_SNAKE_CASE_       :						Dict					=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












UpperCamelCase__						=		[
    [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
]






def    snake_case   (				A		,  A		,  A		,  A     )				->				bool:




	'''simple docstring'''


	return 0 <= row < rows and 0 <= col < cols






def    snake_case   (				A		,  A		,  A		,  A     )				->				int:




	'''simple docstring'''


	lowerCamelCase_				:						List[str]				  =				len(A     )
	lowerCamelCase_				:						Any				  =				len(mat[0]     )
	if is_safe(A		,  A		,  A		,  A     ) and (row, col) not in seen and mat[row][col] == 1:
		seen.add((row, col)     )
		return (
		    1
		    + depth_first_search(row + 1		,  A		,  A		,  A     )
		    + depth_first_search(row - 1		,  A		,  A		,  A     )
		    + depth_first_search(A		,  col + 1		,  A		,  A     )
		    + depth_first_search(A		,  col - 1		,  A		,  A     )
		)
	else:
		return 0






def    snake_case   (				A     )				->				int:




	'''simple docstring'''


	lowerCamelCase_				:						set				  =				set()

	lowerCamelCase_				:						Optional[Any]				  =				0
	for row, line in enumerate(A     ):
		for col, item in enumerate(A     ):
			if item == 1 and (row, col) not in seen:
				# Maximizing the area
				lowerCamelCase_				:						Optional[Any]				  =				max(A		,  depth_first_search(A		,  A		,  A		,  A     )     )
	return max_area


if __name__ == "__main__":
							import doctest

							print(find_max_area(matrix))  # Output -> 6
							doctest.testmod()
