



import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 					a	(  UpperCAmelCase__	,      unittest.TestCase       ):
  UpperCamelCase	:				Dict     						=					MgpstrTokenizer
  UpperCamelCase	:				Dict     						=					False
  UpperCamelCase	:				Optional[int]     						=					{}
  UpperCamelCase	:				Optional[int]     						=					False



  def 	lowerCamelCase__       (						self :					Optional[int]		)     ->					Union[str, Any]:


     '''simple docstring'''




     super().setUp()

     # fmt: off
     SCREAMING_SNAKE_CASE_: Optional[int]     			=["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
     # fmt: on
     SCREAMING_SNAKE_CASE_: Optional[int]     			=dict(zip(lowerCAmelCase       ,		range(len(lowerCAmelCase		)		)		)		)

     SCREAMING_SNAKE_CASE_: List[Any]     			=os.path.join(self.tmpdirname       ,		VOCAB_FILES_NAMES["""vocab_file"""]		)
     with open(self.vocab_file       ,		"""w"""       ,		encoding="""utf-8"""		) as fp:
        fp.write(json.dumps(lowerCAmelCase		) + """\n"""		)



  def 	lowerCamelCase__       (						self :					Any       ,		**lowerCAmelCase :					int		)     ->					Optional[int]:


     '''simple docstring'''




     return MgpstrTokenizer.from_pretrained(self.tmpdirname       ,		**lowerCAmelCase		)



  def 	lowerCamelCase__       (						self :					str       ,		lowerCAmelCase :					List[str]		)     ->					Optional[int]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			="""tester"""
     SCREAMING_SNAKE_CASE_: Tuple     			="""tester"""
     return input_text, output_text



  @unittest.skip("""MGP-STR always lower cases letters."""		)
  def 	lowerCamelCase__       (						self :					Tuple		)     ->					str:


     '''simple docstring'''




     pass



  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					List[str]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[Any]     			=self.get_tokenizers(do_lower_case=lowerCAmelCase		)
     for tokenizer in tokenizers:
        with self.subTest(f'''{tokenizer.__class__.__name__}'''		):
           SCREAMING_SNAKE_CASE_: int     			="""[SPECIAL_TOKEN]"""

           tokenizer.add_special_tokens({"""cls_token""": special_token}		)
           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer.encode([special_token]       ,		add_special_tokens=lowerCAmelCase		)
           self.assertEqual(len(lowerCAmelCase		)       ,		1		)

           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer.decode(lowerCAmelCase       ,		skip_special_tokens=lowerCAmelCase		)
           self.assertTrue(special_token not in decoded		)



  def 	lowerCamelCase__       (						self :					Optional[int]		)     ->					Optional[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: List[str]     			=self.get_tokenizers()
     for tokenizer in tokenizers:
        with self.subTest(f'''{tokenizer.__class__.__name__}'''		):
           SCREAMING_SNAKE_CASE_: List[Any]     			=self.get_input_output_texts(lowerCAmelCase		)

           SCREAMING_SNAKE_CASE_: List[str]     			=tokenizer.tokenize(lowerCAmelCase		)
           SCREAMING_SNAKE_CASE_: Optional[Any]     			=tokenizer.convert_tokens_to_ids(lowerCAmelCase		)
           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer.encode(lowerCAmelCase       ,		add_special_tokens=lowerCAmelCase		)
           self.assertListEqual(lowerCAmelCase       ,		lowerCAmelCase		)

           SCREAMING_SNAKE_CASE_: int     			=tokenizer.convert_ids_to_tokens(lowerCAmelCase		)
           self.assertNotEqual(len(lowerCAmelCase		)       ,		0		)
           SCREAMING_SNAKE_CASE_: Any     			=tokenizer.decode(lowerCAmelCase		)
           self.assertIsInstance(lowerCAmelCase       ,		lowerCAmelCase		)

           self.assertEqual(text_a.replace(""" """       ,		""""""		)       ,		lowerCAmelCase		)



  @unittest.skip("""MGP-STR tokenizer only handles one sequence."""		)
  def 	lowerCamelCase__       (						self :					Tuple		)     ->					Union[str, Any]:


     '''simple docstring'''




     pass





  @unittest.skip("""inputs cannot be pretokenized in MgpstrTokenizer"""		)
  def 	lowerCamelCase__       (						self :					Dict		)     ->					List[str]:


     '''simple docstring'''




     pass








"""simple docstring"""
from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
   import torch

if is_vision_available():
   from PIL import Image


_UpperCAmelCase     =			["""text""", """image""", """audio"""]





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: str     			=[]

   for input_type in input_types:
      if input_type == "text":
         inputs.append("""Text input""" )
      elif input_type == "image":
         inputs.append(
             Image.open(Path(get_tests_dir("""fixtures/tests_samples/COCO""" ) ) / """000000039769.png""" ).resize((512, 512) ) )
      elif input_type == "audio":
         inputs.append(torch.ones(3000 ) )
      elif isinstance(lowercase							,			lowercase ):
         inputs.append(create_inputs(lowercase ) )
      else:
         raise ValueError(f'''Invalid type requested: {input_type}''' )

   return inputs





def      __magic_name__				(							lowercase ):
   SCREAMING_SNAKE_CASE_: int     			=[]

   for output in outputs:
      if isinstance(lowercase							,			(str, AgentText) ):
         output_types.append("""text""" )
      elif isinstance(lowercase							,			(Image.Image, AgentImage) ):
         output_types.append("""image""" )
      elif isinstance(lowercase							,			(torch.Tensor, AgentAudio) ):
         output_types.append("""audio""" )
      else:
         raise ValueError(f'''Invalid output: {output}''' )

   return output_types
@is_tool_test
class 					a	:



  def 	lowerCamelCase__       (						self :					Tuple		)     ->					List[Any]:


     '''simple docstring'''




     self.assertTrue(hasattr(self.tool       ,		"""inputs"""		)		)
     self.assertTrue(hasattr(self.tool       ,		"""outputs"""		)		)

     SCREAMING_SNAKE_CASE_: Optional[int]     			=self.tool.inputs
     for _input in inputs:
        if isinstance(_input       ,		lowerCAmelCase		):
           for __input in _input:
              self.assertTrue(__input in authorized_types		)
        else:
           self.assertTrue(_input in authorized_types		)

     SCREAMING_SNAKE_CASE_: Any     			=self.tool.outputs
     for _output in outputs:
        self.assertTrue(_output in authorized_types		)



  def 	lowerCamelCase__       (						self :					str		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Dict     			=create_inputs(self.tool.inputs		)
     SCREAMING_SNAKE_CASE_: List[Any]     			=self.tool(*lowerCAmelCase		)

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

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



  def 	lowerCamelCase__       (						self :					str		)     ->					Optional[Any]:


     '''simple docstring'''




     self.assertTrue(hasattr(self.tool       ,		"""description"""		)		)
     self.assertTrue(hasattr(self.tool       ,		"""default_checkpoint"""		)		)
     self.assertTrue(self.tool.description.startswith("""This is a tool that"""		)		)



  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: str     			=create_inputs(self.tool.inputs		)
     SCREAMING_SNAKE_CASE_: Tuple     			=self.tool(*lowerCAmelCase		)

     if not isinstance(lowerCAmelCase       ,		lowerCAmelCase		):
        SCREAMING_SNAKE_CASE_: int     			=[outputs]

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

     for output, output_type in zip(lowerCAmelCase       ,		self.tool.outputs		):
        SCREAMING_SNAKE_CASE_: int     			=AGENT_TYPE_MAPPING[output_type]
        self.assertTrue(isinstance(lowerCAmelCase       ,		lowerCAmelCase		)		)





  def 	lowerCamelCase__       (						self :					List[Any]		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=create_inputs(self.tool.inputs		)

     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=[]

     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
     SCREAMING_SNAKE_CASE_: Dict     			=self.tool(*lowerCAmelCase		)

     if not isinstance(lowerCAmelCase       ,		lowerCAmelCase		):
        SCREAMING_SNAKE_CASE_: List[str]     			=[outputs]

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



