






"""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


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


def      UpperCamelCase       ( _A )     ->       Optional[int]:
				lowercase    :      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(3_000 ) )
								elif isinstance(_A  ,				_A ):
												inputs.append(create_inputs(_A ) )
								else:
												raise ValueError(F"""Invalid type requested: {input_type}""" )

				return inputs


def      UpperCamelCase       ( _A )     ->       List[Any]:
				lowercase    :      List[str]       = []

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

				return output_types


@is_tool_test
class      UpperCamelCase		:






						def      __snake_case      (		self  :Tuple				)      ->Optional[Any]:
										self.assertTrue(hasattr(self.tool			, """inputs"""				)				)
										self.assertTrue(hasattr(self.tool			, """outputs"""				)				)

										lowercase    :      int       = self.tool.inputs
										for _input in inputs:
														if isinstance(_input			, __magic_name__				):
																		for __input in _input:
																						self.assertTrue(__input in authorized_types				)
														else:
																		self.assertTrue(_input in authorized_types				)

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






						def      __snake_case      (		self  :List[str]				)      ->Optional[Any]:
										lowercase    :      Tuple       = create_inputs(self.tool.inputs				)
										lowercase    :      str       = self.tool(*__magic_name__				)

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

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






						def      __snake_case      (		self  :Any				)      ->Tuple:
										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      __snake_case      (		self  :Tuple				)      ->str:
										lowercase    :      List[str]       = create_inputs(self.tool.inputs				)
										lowercase    :      Dict       = self.tool(*__magic_name__				)

										if not isinstance(__magic_name__			, __magic_name__				):
														lowercase    :      Union[str, Any]       = [outputs]

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

										for output, output_type in zip(__magic_name__			, self.tool.outputs				):
														lowercase    :      List[str]       = AGENT_TYPE_MAPPING[output_type]
														self.assertTrue(isinstance(__magic_name__			, __magic_name__				)				)






						def      __snake_case      (		self  :str				)      ->Optional[int]:
										lowercase    :      Union[str, Any]       = create_inputs(self.tool.inputs				)

										lowercase    :      Any       = []

										for _input, input_type in zip(__magic_name__			, self.tool.inputs				):
														if isinstance(__magic_name__			, __magic_name__				):
																		_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
										lowercase    :      Union[str, Any]       = self.tool(*__magic_name__				)

										if not isinstance(__magic_name__			, __magic_name__				):
														lowercase    :      List[Any]       = [outputs]

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








"""simple docstring"""







import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_fnet import FNetTokenizer
else:
				_lowerCAmelCase            =	None

_lowerCAmelCase            =	logging.get_logger(__name__)
_lowerCAmelCase            =	{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_lowerCAmelCase            =	{
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

_lowerCAmelCase            =	{
    'google/fnet-base': 5_12,
    'google/fnet-large': 5_12,
}

_lowerCAmelCase            =	'▁'


class      UpperCamelCase		(__snake_case     ):
						_SCREAMING_SNAKE_CASE  : Dict												=		VOCAB_FILES_NAMES
						_SCREAMING_SNAKE_CASE  : Optional[Any]												=		PRETRAINED_VOCAB_FILES_MAP
						_SCREAMING_SNAKE_CASE  : Optional[Any]												=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_SCREAMING_SNAKE_CASE  : Optional[Any]												=		["""input_ids""", """token_type_ids"""]
						_SCREAMING_SNAKE_CASE  : Union[str, Any]												=		FNetTokenizer






						def __init__(		self  :Optional[Any]			, __magic_name__  :Union[str, Any]=None			, __magic_name__  :Any=None			, __magic_name__  :List[str]=False			, __magic_name__  :Any=True			, __magic_name__  :Any=True			, __magic_name__  :Union[str, Any]="<unk>"			, __magic_name__  :List[Any]="[SEP]"			, __magic_name__  :Union[str, Any]="<pad>"			, __magic_name__  :Tuple="[CLS]"			, __magic_name__  :Optional[int]="[MASK]"			, **__magic_name__  :Optional[int]			, )      ->Tuple:
										# Mask token behave like a normal word, i.e. include the space before it and
										# is included in the raw text, there should be a match in a non-normalized sentence.
										lowercase    :      Union[str, Any]       = (
										    AddedToken(__magic_name__			, lstrip=__magic_name__			, rstrip=__magic_name__			, normalized=__magic_name__				)
										    if isinstance(__magic_name__			, __magic_name__				)
										    else mask_token
										)

										super().__init__(
										    __magic_name__			, tokenizer_file=__magic_name__			, do_lower_case=__magic_name__			, remove_space=__magic_name__			, keep_accents=__magic_name__			, unk_token=__magic_name__			, sep_token=__magic_name__			, pad_token=__magic_name__			, cls_token=__magic_name__			, mask_token=__magic_name__			, **__magic_name__			, )

										lowercase    :      Tuple       = do_lower_case
										lowercase    :      Tuple       = remove_space
										lowercase    :      List[str]       = keep_accents
										lowercase    :      Union[str, Any]       = vocab_file
										lowercase    :      int       = False if not self.vocab_file else True






						def      __snake_case      (		self  :Any			, __magic_name__  :List[int]			, __magic_name__  :Optional[List[int]] = None				)      ->List[int]:
										lowercase    :      List[str]       = [self.sep_token_id]
										lowercase    :      Any       = [self.cls_token_id]
										if token_ids_a is None:
														return cls + token_ids_a + sep
										return cls + token_ids_a + sep + token_ids_a + sep






						def      __snake_case      (		self  :int			, __magic_name__  :List[int]			, __magic_name__  :Optional[List[int]] = None				)      ->List[int]:
										lowercase    :      Tuple       = [self.sep_token_id]
										lowercase    :      Union[str, Any]       = [self.cls_token_id]

										if token_ids_a is None:
														return len(cls + token_ids_a + sep				) * [0]
										return len(cls + token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]






						def      __snake_case      (		self  :int			, __magic_name__  :str			, __magic_name__  :Optional[str] = None				)      ->Tuple[str]:
										if not os.path.isdir(__magic_name__				):
														logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
														return
										lowercase    :      str       = os.path.join(
										    __magic_name__			, (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)

										if os.path.abspath(self.vocab_file				) != os.path.abspath(__magic_name__				):
														copyfile(self.vocab_file			, __magic_name__				)

										return (out_vocab_file,)
