


'''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


UpperCAmelCase_	:     Tuple							     =	'Here is a text containing a lot of information: \'\'\'{text}\'\'\'.\n\nCan you answer this question about the text: \'{question}\''





class 					lowercase__						(		_snake_case      ):





							'''simple docstring'''


							A_							:   int   			=						"""google/flan-t5-base"""
							A_							:   Union[str, Any]   			=						(
							    """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."""
							)
							A_							:   Any   			=						"""text_qa"""
							A_							:   int   			=						AutoTokenizer
							A_							:   Union[str, Any]   			=						AutoModelForSeqaSeqLM

							A_							:   Dict   			=						["""text""", """text"""]
							A_							:   Dict   			=						["""text"""]






							def UpperCAmelCase_			(					self					,      __snake_case					,      __snake_case						):
											_SCREAMING_SNAKE_CASE				: Union[str, Any]  	=   QA_PROMPT.format(text=__snake_case					,      question=__snake_case						)
											return self.pre_processor(__snake_case					,      return_tensors="""pt"""						)






							def UpperCAmelCase_			(					self					,      __snake_case						):
											_SCREAMING_SNAKE_CASE				: List[Any]  	=   self.model.generate(**__snake_case						)

											_SCREAMING_SNAKE_CASE	, _SCREAMING_SNAKE_CASE				: Any  	=   inputs["""input_ids"""].shape
											_SCREAMING_SNAKE_CASE				: List[str]  	=   output_ids.shape[0]

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






							def UpperCAmelCase_			(					self					,      __snake_case						):
											return self.pre_processor.decode(__snake_case					,      skip_special_tokens=__snake_case					,      clean_up_tokenization_spaces=__snake_case						)








'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_	:     Any							     =	{
    'configuration_musicgen': [
        'MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MusicgenConfig',
        'MusicgenDecoderConfig',
    ],
    'processing_musicgen': ['MusicgenProcessor'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_	:     Any							     =	[
				    'MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MusicgenForConditionalGeneration',
				    'MusicgenForCausalLM',
				    'MusicgenModel',
				    'MusicgenPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_musicgen import (
				    MUSICGEN_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    MusicgenConfig,
				    MusicgenDecoderConfig,
				)
				from .processing_musicgen import MusicgenProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_musicgen import (
								    MUSICGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MusicgenForCausalLM,
								    MusicgenForConditionalGeneration,
								    MusicgenModel,
								    MusicgenPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_	:     Tuple							     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




