"""simple docstring"""


from typing import TYPE_CHECKING

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


UpperCAmelCase__			=    {}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase__			=    ['''NllbTokenizer''']

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase__			=    ['''NllbTokenizerFast''']


if TYPE_CHECKING:
    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_nllb import NllbTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_nllb_fast import NllbTokenizerFast

else:
    import sys

    UpperCAmelCase__			=    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






'''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_		:     int          =		['''text''', '''image''', '''audio''']





def       __a      (  _UpperCamelCase:       List[str]       )		->					Dict:

     """simple docstring"""




     _snake_case				= []

     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(3_000       )       )
          elif isinstance(_UpperCamelCase   ,		_UpperCamelCase       ):
               inputs.append(create_inputs(_UpperCamelCase       )       )
          else:
               raise ValueError(F"""Invalid type requested: {input_type}"""       )

     return inputs





def       __a      (  _UpperCamelCase:       List       )		->					Dict:

     """simple docstring"""




     _snake_case				= []

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

     return output_types





@is_tool_test
class   _a							:






     def 							_lowercase      (					self       )				->     Any:
          self.assertTrue(hasattr(self.tool   ,"inputs"       )       )
          self.assertTrue(hasattr(self.tool   ,"outputs"       )       )

          _snake_case				= self.tool.inputs
          for _input in inputs:
               if isinstance(_input   ,_SCREAMING_SNAKE_CASE       ):
                    for __input in _input:
                         self.assertTrue(__input in authorized_types       )
               else:
                    self.assertTrue(_input in authorized_types       )

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






     def 							_lowercase      (					self       )				->     Any:
          _snake_case				= create_inputs(self.tool.inputs       )
          _snake_case				= self.tool(*_SCREAMING_SNAKE_CASE       )

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

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






     def 							_lowercase      (					self       )				->     str:
          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 							_lowercase      (					self       )				->     Tuple:
          _snake_case				= create_inputs(self.tool.inputs       )
          _snake_case				= self.tool(*_SCREAMING_SNAKE_CASE       )

          if not isinstance(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       ):
               _snake_case				= [outputs]

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

          for output, output_type in zip(_SCREAMING_SNAKE_CASE   ,self.tool.outputs       ):
               _snake_case				= AGENT_TYPE_MAPPING[output_type]
               self.assertTrue(isinstance(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       )       )






     def 							_lowercase      (					self       )				->     Optional[Any]:
          _snake_case				= create_inputs(self.tool.inputs       )

          _snake_case				= []

          for _input, input_type in zip(_SCREAMING_SNAKE_CASE   ,self.tool.inputs       ):
               if isinstance(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       ):
                    _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
          _snake_case				= self.tool(*_SCREAMING_SNAKE_CASE       )

          if not isinstance(_SCREAMING_SNAKE_CASE   ,_SCREAMING_SNAKE_CASE       ):
               _snake_case				= [outputs]

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


