




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

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


UpperCamelCase__						=		{
    'agents': ['Agent', 'AzureOpenAiAgent', 'HfAgent', 'LocalAgent', 'OpenAiAgent'],
    'base': ['PipelineTool', 'RemoteTool', 'Tool', 'launch_gradio_demo', 'load_tool'],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		['DocumentQuestionAnsweringTool']
							UpperCamelCase__						=		['ImageCaptioningTool']
							UpperCamelCase__						=		['ImageQuestionAnsweringTool']
							UpperCamelCase__						=		['ImageSegmentationTool']
							UpperCamelCase__						=		['SpeechToTextTool']
							UpperCamelCase__						=		['TextClassificationTool']
							UpperCamelCase__						=		['TextQuestionAnsweringTool']
							UpperCamelCase__						=		['TextSummarizationTool']
							UpperCamelCase__						=		['TextToSpeechTool']
							UpperCamelCase__						=		['TranslationTool']

if TYPE_CHECKING:
							from .agents import Agent, AzureOpenAiAgent, HfAgent, LocalAgent, OpenAiAgent
							from .base import PipelineTool, RemoteTool, Tool, launch_gradio_demo, load_tool

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .document_question_answering import DocumentQuestionAnsweringTool
														from .image_captioning import ImageCaptioningTool
														from .image_question_answering import ImageQuestionAnsweringTool
														from .image_segmentation import ImageSegmentationTool
														from .speech_to_text import SpeechToTextTool
														from .text_classification import TextClassificationTool
														from .text_question_answering import TextQuestionAnsweringTool
														from .text_summarization import TextSummarizationTool
														from .text_to_speech import TextToSpeechTool
														from .translation import TranslationTool
else:
							import sys

							UpperCamelCase__						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""simple docstring"""

import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase

@require_tokenizers
class     A_				(   unittest.TestCase	):
				UpperCAmelCase__										=					EsmTokenizer







				def      _snake_case       (				self				:    List[str]						)					->       Dict:
										super().setUp()
										__magic_name__      =  tempfile.mkdtemp()
										# fmt: off
										__magic_name__      =  ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
										# fmt: on
										__magic_name__      =  os.path.join(self.tmpdirname    ,     VOCAB_FILES_NAMES["vocab_file"]						)
										with open(self.vocab_file    ,     "w"    ,     encoding="utf-8"						) as vocab_writer:
																vocab_writer.write("".join([x + "\n" for x in vocab_tokens]						)						)







				def      _snake_case       (				self				:    Optional[Any]    ,     **__lowerCamelCase				:    str						)					->       List[PreTrainedTokenizerBase]:
										return [self.get_tokenizer(**__lowerCamelCase						)]







				def      _snake_case       (				self				:    Dict    ,     **__lowerCamelCase				:    int						)					->       PreTrainedTokenizer:
										return self.tokenizer_class.from_pretrained(self.tmpdirname    ,     **__lowerCamelCase						)







				def      _snake_case       (				self				:    str						)					->       Optional[int]:
										__magic_name__      =  self.tokenizer_class(self.vocab_file						)

										__magic_name__      =  tokenizer.tokenize("LAGVS"						)
										self.assertListEqual(__lowerCamelCase    ,     ["L", "A", "G", "V", "S"]						)
										self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase						)    ,     [4, 5, 6, 7, 8]						)







				def      _snake_case       (				self				:    int						)					->       Dict:
										__magic_name__      =  self.tokenizer_class(self.vocab_file						)

										__magic_name__      =  "LAGVS"
										self.assertListEqual(tokenizer.encode(__lowerCamelCase						)    ,     [0, 4, 5, 6, 7, 8, 2]						)







				def      _snake_case       (				self				:    List[Any]						)					->       Tuple:
										__magic_name__      =  self.tokenizer_class(self.vocab_file						)

										__magic_name__      =  ["LAGVS", "WCB"]
										__magic_name__      =  tokenizer(__lowerCamelCase    ,     padding=__lowerCamelCase						)["input_ids"]

										self.assertListEqual(__lowerCamelCase    ,     [[0, 4, 5, 6, 7, 8, 2], [0, 2_2, 2_3, 2_5, 2]]						)







				def      _snake_case       (				self				:    Union[str, Any]						)					->       List[str]:
										__magic_name__      =  self.tokenizer_class(self.vocab_file						)

										__magic_name__      =  ["LAGVS", "WCB"]
										__magic_name__      =  tokenizer(__lowerCamelCase    ,     padding=__lowerCamelCase						)["input_ids"]

										self.assertListEqual(__lowerCamelCase    ,     [[0, 4, 5, 6, 7, 8, 2], [0, 2_2, 2_3, 2_5, 2, 1, 1]]						)







				def      _snake_case       (				self				:    Union[str, Any]						)					->       Dict:
										__magic_name__      =  self.get_tokenizers(fast=__lowerCamelCase						)
										for tokenizer in tokenizers:
																with self.subTest(f'''{tokenizer.__class__.__name__}'''						):
																						__magic_name__      =  "<unk>"
																						__magic_name__      =  "<mask>"

																						__magic_name__      =  tokenizer.tokenize(__lowerCamelCase						)
																						__magic_name__      =  tokenizer.tokenize(__lowerCamelCase						)

																						self.assertEqual(len(__lowerCamelCase						)    ,     1						)
																						self.assertEqual(len(__lowerCamelCase						)    ,     1						)
																						self.assertEqual(token_a[0]    ,     __lowerCamelCase						)
																						self.assertEqual(token_a[0]    ,     __lowerCamelCase						)



