





"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)







@dataclass
class       a							(   a__  ):
 snake_case__             =       42
 snake_case__             =       42
 snake_case__             =       42


try:
       if not (is_transformers_available() and is_torch_available()):
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
       from .pipeline_if import IFPipeline
       from .pipeline_if_imgaimg import IFImgaImgPipeline
       from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
       from .pipeline_if_inpainting import IFInpaintingPipeline
       from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
       from .pipeline_if_superresolution import IFSuperResolutionPipeline
       from .safety_checker import IFSafetyChecker
       from .watermark import IFWatermarker












"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase     :						Optional[Any]						       =  logging.get_logger(__name__)

__UpperCamelCase     :						List[Any]						       =  {
    # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}







class       a							(   a__  ):
 snake_case__             =       '''megatron-bert'''



 def __init__(     self				,       _snake_case=2_90_56				,       _snake_case=10_24				,       _snake_case=24				,       _snake_case=16				,       _snake_case=40_96				,       _snake_case="gelu"				,       _snake_case=0.1				,       _snake_case=0.1				,       _snake_case=5_12				,       _snake_case=2				,       _snake_case=0.02				,       _snake_case=1E-12				,       _snake_case=0				,       _snake_case="absolute"				,       _snake_case=True				,       **_snake_case				,       ):







  """simple docstring"""






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

  lowerCAmelCase    				= vocab_size
  lowerCAmelCase    				= hidden_size
  lowerCAmelCase    				= num_hidden_layers
  lowerCAmelCase    				= num_attention_heads
  lowerCAmelCase    				= hidden_act
  lowerCAmelCase    				= intermediate_size
  lowerCAmelCase    				= hidden_dropout_prob
  lowerCAmelCase    				= attention_probs_dropout_prob
  lowerCAmelCase    				= max_position_embeddings
  lowerCAmelCase    				= type_vocab_size
  lowerCAmelCase    				= initializer_range
  lowerCAmelCase    				= layer_norm_eps
  lowerCAmelCase    				= position_embedding_type
  lowerCAmelCase    				= use_cache





