
'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowerCAmelCase												=	{
    'configuration_pix2struct': [
        'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'Pix2StructConfig',
        'Pix2StructTextConfig',
        'Pix2StructVisionConfig',
    ],
    'processing_pix2struct': ['Pix2StructProcessor'],
}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase												=	['Pix2StructImageProcessor']


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCAmelCase												=	[
				    'PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'Pix2StructPreTrainedModel',
				    'Pix2StructForConditionalGeneration',
				    'Pix2StructVisionModel',
				    'Pix2StructTextModel',
				]

if TYPE_CHECKING:
				from .configuration_pixastruct import (
				    PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    PixaStructConfig,
				    PixaStructTextConfig,
				    PixaStructVisionConfig,
				)
				from .processing_pixastruct import PixaStructProcessor

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_pixastruct import PixaStructImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_pixastruct import (
								    PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    PixaStructForConditionalGeneration,
								    PixaStructPreTrainedModel,
								    PixaStructTextModel,
								    PixaStructVisionModel,
								)

else:
				import sys

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

'''simple docstring'''
import logging

from transformers.configuration_utils import PretrainedConfig


__lowerCAmelCase												=	logging.getLogger(__name__)


class       _lowerCAmelCase   (   __snake_case				):







							'''simple docstring'''

							lowerCAmelCase_ 						=						"masked_bert"

							def __init__(self  ,  UpperCAmelCase=30522  ,  UpperCAmelCase=768  ,  UpperCAmelCase=12  ,  UpperCAmelCase=12  ,  UpperCAmelCase=3072  ,  UpperCAmelCase="gelu"  ,  UpperCAmelCase=0.1  ,  UpperCAmelCase=0.1  ,  UpperCAmelCase=512  ,  UpperCAmelCase=2  ,  UpperCAmelCase=0.02  ,  UpperCAmelCase=1e-1_2  ,  UpperCAmelCase=0  ,  UpperCAmelCase="topK"  ,  UpperCAmelCase="constant"  ,  UpperCAmelCase=0.0  ,  **UpperCAmelCase  ,  )					->       int:
														super().__init__(pad_token_id=UpperCAmelCase  ,  **UpperCAmelCase  )

														_snake_case       =  vocab_size
														_snake_case       =  hidden_size
														_snake_case       =  num_hidden_layers
														_snake_case       =  num_attention_heads
														_snake_case       =  hidden_act
														_snake_case       =  intermediate_size
														_snake_case       =  hidden_dropout_prob
														_snake_case       =  attention_probs_dropout_prob
														_snake_case       =  max_position_embeddings
														_snake_case       =  type_vocab_size
														_snake_case       =  initializer_range
														_snake_case       =  layer_norm_eps
														_snake_case       =  pruning_method
														_snake_case       =  mask_init
														_snake_case       =  mask_scale