
"""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


SCREAMING_SNAKE_CASE_    					=						['''text''', '''image''', '''audio''']




def     lowercase__						(					lowerCAmelCase				:					List[str] ) ->      Any:
    UpperCAmelCase									=					[]

    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(lowerCAmelCase ,				lowerCAmelCase ):
            inputs.append(create_inputs(lowerCAmelCase ) )
        else:
            raise ValueError(F"Invalid type requested: {input_type}" )

    return inputs




def     lowercase__						(					lowerCAmelCase				:					List ) ->      int:
    UpperCAmelCase									=					[]

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

    return output_types







@is_tool_test
class      _UpperCAmelCase							:




      def     a_      (							self							)						->					Optional[Any]:
          self.assertTrue(hasattr(self.tool   ,       'inputs'							)							)
          self.assertTrue(hasattr(self.tool   ,       'outputs'							)							)

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

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




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					create_inputs(self.tool.inputs							)
          UpperCAmelCase									=					self.tool(*lowercase_							)

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

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




      def     a_      (							self							)						->					Any:
          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     a_      (							self							)						->					Dict:
          UpperCAmelCase									=					create_inputs(self.tool.inputs							)
          UpperCAmelCase									=					self.tool(*lowercase_							)

          if not isinstance(lowercase_   ,       lowercase_							):
              UpperCAmelCase									=					[outputs]

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

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




      def     a_      (							self							)						->					List[Any]:
          UpperCAmelCase									=					create_inputs(self.tool.inputs							)

          UpperCAmelCase									=					[]

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

          if not isinstance(lowercase_   ,       lowercase_							):
              UpperCAmelCase									=					[outputs]

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





"""simple docstring"""

import json
import os
import unittest

from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin
class      _UpperCAmelCase							(		SCREAMING_SNAKE_CASE_     ,			unittest.TestCase							):
      __SCREAMING_SNAKE_CASE   :							str							      =	CTRLTokenizer
      __SCREAMING_SNAKE_CASE   :							int							      =	False
      __SCREAMING_SNAKE_CASE   :							Optional[Any]							      =	False




      def     a_      (							self							)						->					Dict:
          super().setUp()

          # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
          UpperCAmelCase									=					['adapt', 're@@', 'a@@', 'apt', 'c@@', 't', '<unk>']
          UpperCAmelCase									=					dict(zip(lowercase_   ,       range(len(lowercase_							)							)							)							)
          UpperCAmelCase									=					['#version: 0.2', 'a p', 'ap t</w>', 'r e', 'a d', 'ad apt</w>', '']
          UpperCAmelCase									=					{'unk_token': '<unk>'}

          UpperCAmelCase									=					os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES['vocab_file']							)
          UpperCAmelCase									=					os.path.join(self.tmpdirname   ,       VOCAB_FILES_NAMES['merges_file']							)
          with open(self.vocab_file   ,       'w'   ,       encoding='utf-8'							) as fp:
              fp.write(json.dumps(lowercase_							) + '\n'							)
          with open(self.merges_file   ,       'w'   ,       encoding='utf-8'							) as fp:
              fp.write('\n'.join(lowercase_							)							)




      def     a_      (							self   ,       **lowercase_							)						->					Tuple:
          kwargs.update(self.special_tokens_map							)
          return CTRLTokenizer.from_pretrained(self.tmpdirname   ,       **lowercase_							)




      def     a_      (							self   ,       lowercase_							)						->					Tuple:
          UpperCAmelCase									=					'adapt react readapt apt'
          UpperCAmelCase									=					'adapt react readapt apt'
          return input_text, output_text




      def     a_      (							self							)						->					Union[str, Any]:
          UpperCAmelCase									=					CTRLTokenizer(self.vocab_file   ,       self.merges_file   ,       **self.special_tokens_map							)
          UpperCAmelCase									=					'adapt react readapt apt'
          UpperCAmelCase									=					'adapt re@@ a@@ c@@ t re@@ adapt apt'.split()
          UpperCAmelCase									=					tokenizer.tokenize(lowercase_							)
          self.assertListEqual(lowercase_   ,       lowercase_							)

          UpperCAmelCase									=					tokens + [tokenizer.unk_token]

          UpperCAmelCase									=					[0, 1, 2, 4, 5, 1, 0, 3, 6]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_							)   ,       lowercase_							)



