

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


lowercase_   							=  logging.get_logger(__name__)

lowercase_   							=  {
    'SCUT-DLVCLab/lilt-roberta-en-base': (
        'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json'
    ),
}





class 					__lowerCAmelCase	(   SCREAMING_SNAKE_CASE				):
  _a		     =    """lilt"""




  def __init__(							self				,  lowerCAmelCase=30_522				,  lowerCAmelCase=768				,  lowerCAmelCase=12				,  lowerCAmelCase=12				,  lowerCAmelCase=3_072				,  lowerCAmelCase="gelu"				,  lowerCAmelCase=0.1				,  lowerCAmelCase=0.1				,  lowerCAmelCase=512				,  lowerCAmelCase=2				,  lowerCAmelCase=0.02				,  lowerCAmelCase=1e-12				,  lowerCAmelCase=0				,  lowerCAmelCase="absolute"				,  lowerCAmelCase=None				,  lowerCAmelCase=4				,  lowerCAmelCase=1_024				,  **lowerCAmelCase				,  )    ->					List[Any]:
        '''simple docstring'''






        super().__init__(pad_token_id=lowerCAmelCase				,  **lowerCAmelCase   )

        _lowercase      			=vocab_size
        _lowercase      			=hidden_size
        _lowercase      			=num_hidden_layers
        _lowercase      			=num_attention_heads
        _lowercase      			=hidden_act
        _lowercase      			=intermediate_size
        _lowercase      			=hidden_dropout_prob
        _lowercase      			=attention_probs_dropout_prob
        _lowercase      			=max_position_embeddings
        _lowercase      			=type_vocab_size
        _lowercase      			=initializer_range
        _lowercase      			=layer_norm_eps
        _lowercase      			=position_embedding_type
        _lowercase      			=classifier_dropout
        _lowercase      			=channel_shrink_ratio
        _lowercase      			=max_ad_position_embeddings





from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available





@dataclass
class 					__lowerCAmelCase	(   SCREAMING_SNAKE_CASE				):
  _a		     =    42
  _a		     =    42


if is_transformers_available() and is_torch_available():
  from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline


