import unittest

from transformers import load_tool
from transformers.tools.agent_types import AGENT_TYPE_MAPPING

from .test_tools_common import ToolTesterMixin, output_types




class  __lowerCAmelCase	(							unittest.TestCase,						a_    ):



 '''simple docstring'''

 def        __snake_case       (      self							:		Any	)			->				Optional[Any]:
        _UpperCamelCase  :							int	    =	load_tool('translation'	)
        self.tool.setup()
        _UpperCamelCase  :							str	    =	load_tool('translation'							,      remote=lowerCamelCase	)

 def        __snake_case       (      self							:		Dict	)			->				Any:
        _UpperCamelCase  :							Union[str, Any]	    =	self.tool('Hey, what\'s up?'							,      src_lang='English'							,      tgt_lang='French'	)
        self.assertEqual(lowerCamelCase							,      '- Hé, comment ça va?'	)

 def        __snake_case       (      self							:		Any	)			->				Tuple:
        _UpperCamelCase  :							str	    =	self.remote_tool('Hey, what\'s up?'							,      src_lang='English'							,      tgt_lang='French'	)
        self.assertEqual(lowerCamelCase							,      '- Hé, comment ça va?'	)

 def        __snake_case       (      self							:		List[Any]	)			->				List[str]:
        _UpperCamelCase  :							Optional[Any]	    =	self.tool(text='Hey, what\'s up?'							,      src_lang='English'							,      tgt_lang='French'	)
        self.assertEqual(lowerCamelCase							,      '- Hé, comment ça va?'	)

 def        __snake_case       (      self							:		List[Any]	)			->				str:
        _UpperCamelCase  :							str	    =	self.remote_tool(text='Hey, what\'s up?'							,      src_lang='English'							,      tgt_lang='French'	)
        self.assertEqual(lowerCamelCase							,      '- Hé, comment ça va?'	)

 def        __snake_case       (      self							:		Tuple	)			->				Dict:
        _UpperCamelCase  :							Any	    =	['Hey, what\'s up?', 'English', 'Spanish']
        _UpperCamelCase  :							Dict	    =	self.tool(*lowerCamelCase	)

        # There is a single output
        if len(self.tool.outputs	) == 1:
               _UpperCamelCase  :							List[str]	    =	[outputs]

        self.assertListEqual(output_types(lowerCamelCase	)							,      self.tool.outputs	)

 def        __snake_case       (      self							:		Union[str, Any]	)			->				int:
        _UpperCamelCase  :							str	    =	['Hey, what\'s up?', 'English', 'Spanish']
        _UpperCamelCase  :							str	    =	self.tool(*lowerCamelCase	)

        if not isinstance(lowerCamelCase							,      lowerCamelCase	):
               _UpperCamelCase  :							List[Any]	    =	[outputs]

        self.assertEqual(len(lowerCamelCase	)							,      len(self.tool.outputs	)	)

        for output, output_type in zip(lowerCamelCase							,      self.tool.outputs	):
               _UpperCamelCase  :							List[Any]	    =	AGENT_TYPE_MAPPING[output_type]
               self.assertTrue(isinstance(lowerCamelCase							,      lowerCamelCase	)	)

 def        __snake_case       (      self							:		Any	)			->				List[str]:
        _UpperCamelCase  :							Optional[int]	    =	['Hey, what\'s up?', 'English', 'Spanish']

        _UpperCamelCase  :							List[str]	    =	[]

        for _input, input_type in zip(lowerCamelCase							,      self.tool.inputs	):
               if isinstance(lowerCamelCase							,      lowerCamelCase	):
                      _inputs.append([AGENT_TYPE_MAPPING[_input_type](_input	) for _input_type in input_type]	)
               else:
                      _inputs.append(AGENT_TYPE_MAPPING[input_type](_input	)	)

        # Should not raise an error
        _UpperCamelCase  :							Any	    =	self.tool(*lowerCamelCase	)

        if not isinstance(lowerCamelCase							,      lowerCamelCase	):
               _UpperCamelCase  :							List[Any]	    =	[outputs]

        self.assertEqual(len(lowerCamelCase	)							,      len(self.tool.outputs	)	)







import torch

from transformers import AutoTokenizer







class      _lowercase					(				lowercase__):


       """simple docstring"""




       def __init__(  self				:     Optional[Any]   , __lowerCamelCase				:     Dict			):


             '''simple docstring'''



             lowerCamelCase__						:							int       =    AutoTokenizer.from_pretrained(__lowerCamelCase			)





       def 		lowerCAmelCase	(  self				:     Union[str, Any]   , __lowerCamelCase				:     str			):


             '''simple docstring'''



             if isinstance(__lowerCamelCase   , __lowerCamelCase			) and all(isinstance(_x   , __lowerCamelCase			) for _x in x			):
                   lowerCamelCase__						:							List[Any]       =    None
                   for l in x:
                         lowerCamelCase__						:							str       =    self.tokenizer(
                             __lowerCamelCase   , padding="max_length"   , max_length=384   , truncation=__lowerCamelCase   , return_tensors="pt"   , )
                         lowerCamelCase__						:							Dict       =    torch.tensor([len(__lowerCamelCase			)]			)
                         if d is not None:
                               for k in d.keys():
                                     lowerCamelCase__						:							Tuple       =    torch.cat((d[k], t[k])   , 0			)
                         else:
                               lowerCamelCase__						:							Union[str, Any]       =    t

                   lowerCamelCase__						:							List[Any]       =    torch.tensor(self.tokenizer.convert_tokens_to_ids("[E]"			)			)
                   lowerCamelCase__						:							Dict       =    torch.tensor(self.tokenizer.convert_tokens_to_ids("[/E]"			)			)

             elif isinstance(__lowerCamelCase   , __lowerCamelCase			) and all(isinstance(_x   , __lowerCamelCase			) for _x in x			):
                   lowerCamelCase__						:							Tuple       =    self.tokenizer(
                       __lowerCamelCase   , padding="max_length"   , max_length=384   , truncation=__lowerCamelCase   , return_tensors="pt"   , )

             else:
                   raise Exception(
                       "Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of"
                       " strings` for supports are supported."			)

             return d





       def 		lowerCAmelCase	(  self				:     List[Any]   , __lowerCamelCase				:     List[str]   , __lowerCamelCase				:     List[str]   , __lowerCamelCase				:     Dict   , __lowerCamelCase				:     Any   , __lowerCamelCase				:     Optional[Any]=0.7_0			):


             '''simple docstring'''



             lowerCamelCase__						:							Union[str, Any]       =    []
             for idx in range(len(W_query["input_ids"]			)			):
                   lowerCamelCase__						:							str       =    range(p_start.shape[1]			)

                   lowerCamelCase__						:							int       =    []
                   for start_id in start_indexes:
                         for end_id in end_indexes:
                               if start_id < end_id:
                                     output.append(
                                         (
                                             start_id,
                                             end_id,
                                             p_start[idx][start_id].item(),
                                             p_end[idx][end_id].item(),
                                         )			)

                   output.sort(key=lambda __lowerCamelCase			: (tup[2] * tup[3])   , reverse=__lowerCamelCase			)
                   lowerCamelCase__						:							str       =    []
                   for k in range(len(__lowerCamelCase			)			):
                         if output[k][2] * output[k][3] >= thresh:
                               lowerCamelCase__       ,  lowerCamelCase__						:							Optional[int]       =    output[k][0], output[k][1]
                               lowerCamelCase__						:							Tuple       =    self.tokenizer.decode(W_query["input_ids"][idx][c_start_pos:c_end_pos]			)
                               temp.append((decoded, output[k][2] * output[k][3])			)

                   final_outputs.append(__lowerCamelCase			)

             return final_outputs


