





'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_     :       Union[str, Any]									=  logging.get_logger(__name__)

snake_case_     :       List[Any]									=  {
    '''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
        '''https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json'''
    ),
}


class 					__a      (snake_case__     ):
							__a					:   Tuple									=       '''gptsan-japanese'''
							__a					:   Optional[int]									=       [
							    '''past_key_values''',
							]
							__a					:   Dict									=       {
							    '''hidden_size''': '''d_model''',
							    '''num_attention_heads''': '''num_heads''',
							    '''num_hidden_layers''': '''num_layers''',
							}

							def __init__(							self							:     Any       ,     __magic_name__							:     str=3_60_00       ,     __magic_name__							:     List[Any]=12_80       ,     __magic_name__							:     Optional[Any]=10_24       ,     __magic_name__							:     Union[str, Any]=81_92       ,     __magic_name__							:     Any=40_96       ,     __magic_name__							:     Union[str, Any]=1_28       ,     __magic_name__							:     List[Any]=10       ,     __magic_name__							:     List[str]=0       ,     __magic_name__							:     Optional[int]=16       ,     __magic_name__							:     str=16       ,     __magic_name__							:     List[Any]=1_28       ,     __magic_name__							:     Tuple=0.0       ,     __magic_name__							:     int=1E-5       ,     __magic_name__							:     Optional[Any]=False       ,     __magic_name__							:     List[str]=0.0       ,     __magic_name__							:     List[Any]="float32"       ,     __magic_name__							:     List[str]=False       ,     __magic_name__							:     List[Any]=False       ,     __magic_name__							:     Optional[Any]=False       ,     __magic_name__							:     Tuple=0.0_0_2       ,     __magic_name__							:     List[Any]=False       ,     __magic_name__							:     Tuple=True       ,     __magic_name__							:     Optional[Any]=3_59_98       ,     __magic_name__							:     Dict=3_59_95       ,     __magic_name__							:     List[str]=3_59_99       ,     **__magic_name__							:     List[Any]       ,     )					->       int:







													"""simple docstring"""
													UpperCAmelCase_			:      int     						=  vocab_size
													UpperCAmelCase_			:      Dict     						=  max_position_embeddings
													UpperCAmelCase_			:      Dict     						=  d_model
													UpperCAmelCase_			:      Optional[int]     						=  d_ff
													UpperCAmelCase_			:      List[str]     						=  d_ext
													UpperCAmelCase_			:      Dict     						=  d_spout
													UpperCAmelCase_			:      Any     						=  num_switch_layers
													UpperCAmelCase_			:      List[str]     						=  num_ext_layers
													UpperCAmelCase_			:      int     						=  num_switch_layers + num_ext_layers
													UpperCAmelCase_			:      Any     						=  num_heads
													UpperCAmelCase_			:      Optional[Any]     						=  num_experts
													UpperCAmelCase_			:      Optional[Any]     						=  expert_capacity
													UpperCAmelCase_			:      str     						=  dropout_rate
													UpperCAmelCase_			:      Tuple     						=  layer_norm_epsilon
													UpperCAmelCase_			:      Tuple     						=  router_bias
													UpperCAmelCase_			:      List[str]     						=  router_jitter_noise
													UpperCAmelCase_			:      List[str]     						=  router_dtype
													UpperCAmelCase_			:      Tuple     						=  router_ignore_padding_tokens
													UpperCAmelCase_			:      int     						=  output_hidden_states
													UpperCAmelCase_			:      Any     						=  output_attentions
													UpperCAmelCase_			:      int     						=  initializer_factor
													UpperCAmelCase_			:      str     						=  output_router_logits
													UpperCAmelCase_			:      Optional[Any]     						=  use_cache

													super().__init__(
													    separator_token_id=_A       ,     pad_token_id=_A       ,     eos_token_id=_A       ,     **_A       ,     )












'''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 typing import TYPE_CHECKING

import torch

from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
					from PIL import Image


class 					__a      (lowerCamelCase     ):
							__a					:   int									=       "dandelin/vilt-b32-finetuned-vqa"
							__a					:   Any									=       (
							    "This is a tool that answers a question about an image. It takes an input named `image` which should be the "
							    "image containing the information, as well as a `question` which should be the question in English. It "
							    "returns a text that is the answer to the question."
							)
							__a					:   Any									=       "image_qa"
							__a					:   str									=       AutoProcessor
							__a					:   Any									=       AutoModelForVisualQuestionAnswering

							__a					:   List[Any]									=       ["image", "text"]
							__a					:   int									=       ["text"]

							def __init__(							self							:     Tuple       ,     *__magic_name__							:     Any       ,     **__magic_name__							:     Any   )					->       Tuple:







													"""simple docstring"""
													requires_backends(self       ,     ['''vision''']   )
													super().__init__(*__magic_name__       ,     **__magic_name__   )

							def     UpperCAmelCase__	(							self							:     Union[str, Any]       ,     __magic_name__							:     "Image"       ,     __magic_name__							:     str   )					->       Tuple:







													"""simple docstring"""
													return self.pre_processor(__magic_name__       ,     __magic_name__       ,     return_tensors='''pt'''   )

							def     UpperCAmelCase__	(							self							:     Any       ,     __magic_name__							:     List[str]   )					->       Optional[Any]:







													"""simple docstring"""
													with torch.no_grad():
																			return self.model(**__magic_name__   ).logits



							def     UpperCAmelCase__	(							self							:     int       ,     __magic_name__							:     int   )					->       Optional[int]:







													"""simple docstring"""
													UpperCAmelCase_			:      Dict     						=  outputs.argmax(-1   ).item()
													return self.model.config.idalabel[idx]





