


"""simple docstring"""






from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_openai import OpenAIGPTTokenizer


lowercase  		=			logging.get_logger(__name__)

lowercase  		=			{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

lowercase  		=			{
    """vocab_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/vocab.json"""},
    """merges_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/merges.txt"""},
    """tokenizer_file""": {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/tokenizer.json"""},
}

lowercase  		=			{
    """openai-gpt""": 512,
}


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     Any				  =  VOCAB_FILES_NAMES
							__magic_name__					:     List[str]				  =  PRETRAINED_VOCAB_FILES_MAP
							__magic_name__					:     List[Any]				  =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__magic_name__					:     Tuple				  =  ['''input_ids''', '''attention_mask''']
							__magic_name__					:     Optional[int]				  =  OpenAIGPTTokenizer




							def __init__(						self	,					lowerCamelCase__=None	,					lowerCamelCase__=None	,					lowerCamelCase__=None	,					lowerCamelCase__="<unk>"	,					**lowerCamelCase__)   ->	str:







								'''simple docstring'''




								super().__init__(lowerCamelCase__	,					lowerCamelCase__	,					tokenizer_file=lowerCamelCase__	,					unk_token=lowerCamelCase__	,					**lowerCamelCase__)




							@property
							def        UpperCAmelCase (						self)   ->	Tuple:







								'''simple docstring'''




								return True







							def        UpperCAmelCase (						self	,					lowerCamelCase__	,					lowerCamelCase__ = None)   ->	Tuple[str]:







								'''simple docstring'''




								snake_case__  :						Any		=      self._tokenizer.model.save(lowerCamelCase__	,					name=lowerCamelCase__)
								return tuple(lowerCamelCase__)









"""simple docstring"""






# 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 ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


lowercase  		=			"""Here is a text containing a lot of information: '''{text}'''.

Can you answer this question about the text: '{question}'"""


class 			SCREAMING_SNAKE_CASE_  (   _lowercase):




							'''simple docstring'''





							__magic_name__					:     List[Any]				  =  '''google/flan-t5-base'''
							__magic_name__					:     Dict				  =  (
							    '''This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the '''
							    '''text where to find the answer, and `question`, which is the question, and returns the answer to the question.'''
							)
							__magic_name__					:     Union[str, Any]				  =  '''text_qa'''
							__magic_name__					:     Union[str, Any]				  =  AutoTokenizer
							__magic_name__					:     List[Any]				  =  AutoModelForSeqaSeqLM

							__magic_name__					:     Tuple				  =  ['''text''', '''text''']
							__magic_name__					:     Tuple				  =  ['''text''']




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







								'''simple docstring'''




								snake_case__  :						str		=      QA_PROMPT.format(text=lowerCamelCase__	,					question=lowerCamelCase__)
								return self.pre_processor(lowerCamelCase__	,					return_tensors="pt")




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







								'''simple docstring'''




								snake_case__  :						Tuple		=      self.model.generate(**lowerCamelCase__)

								snake_case__,					snake_case__  :						Dict		=      inputs["input_ids"].shape
								snake_case__  :						List[Any]		=      output_ids.shape[0]

								return output_ids.reshape(lowerCamelCase__	,					out_b // in_b	,					*output_ids.shape[1:])[0][0]







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







								'''simple docstring'''




								return self.pre_processor.decode(lowerCamelCase__	,					skip_special_tokens=lowerCamelCase__	,					clean_up_tokenization_spaces=lowerCamelCase__)





