




from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase__			:       List[Any]         =							logging.get_logger(__name__)

lowerCamelCase__			:       Optional[int]         =							{
    'facebook/data2vec-vision-base-ft': (
        'https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json'
    ),
}





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   "data2vec-vision"



 def __init__(							self  :		str    ,    _lowerCAmelCase  :		Optional[Any]=768    ,    _lowerCAmelCase  :		Optional[int]=12    ,    _lowerCAmelCase  :		Tuple=12    ,    _lowerCAmelCase  :		str=3_072    ,    _lowerCAmelCase  :		List[Any]="gelu"    ,    _lowerCAmelCase  :		List[Any]=0.0    ,    _lowerCAmelCase  :		Optional[Any]=0.0    ,    _lowerCAmelCase  :		str=0.02    ,    _lowerCAmelCase  :		Optional[int]=1E-12    ,    _lowerCAmelCase  :		Tuple=224    ,    _lowerCAmelCase  :		Dict=16    ,    _lowerCAmelCase  :		str=3    ,    _lowerCAmelCase  :		List[str]=False    ,    _lowerCAmelCase  :		Optional[Any]=False    ,    _lowerCAmelCase  :		Dict=False    ,    _lowerCAmelCase  :		Tuple=False    ,    _lowerCAmelCase  :		Optional[int]=0.1    ,    _lowerCAmelCase  :		List[str]=0.1    ,    _lowerCAmelCase  :		Any=True    ,    _lowerCAmelCase  :		Dict=[3, 5, 7, 11]    ,    _lowerCAmelCase  :		List[str]=[1, 2, 3, 6]    ,    _lowerCAmelCase  :		Tuple=True    ,    _lowerCAmelCase  :		Optional[int]=0.4    ,    _lowerCAmelCase  :		Dict=256    ,    _lowerCAmelCase  :		int=1    ,    _lowerCAmelCase  :		Optional[Any]=False    ,    _lowerCAmelCase  :		Union[str, Any]=255    ,    **_lowerCAmelCase  :		int    ,    ):
       super().__init__(**_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      hidden_size
       SCREAMING_SNAKE_CASE_     						=      num_hidden_layers
       SCREAMING_SNAKE_CASE_     						=      num_attention_heads
       SCREAMING_SNAKE_CASE_     						=      intermediate_size
       SCREAMING_SNAKE_CASE_     						=      hidden_act
       SCREAMING_SNAKE_CASE_     						=      hidden_dropout_prob
       SCREAMING_SNAKE_CASE_     						=      attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE_     						=      initializer_range
       SCREAMING_SNAKE_CASE_     						=      layer_norm_eps

       SCREAMING_SNAKE_CASE_     						=      image_size
       SCREAMING_SNAKE_CASE_     						=      patch_size
       SCREAMING_SNAKE_CASE_     						=      num_channels
       SCREAMING_SNAKE_CASE_     						=      use_mask_token
       SCREAMING_SNAKE_CASE_     						=      use_absolute_position_embeddings
       SCREAMING_SNAKE_CASE_     						=      use_relative_position_bias
       SCREAMING_SNAKE_CASE_     						=      use_shared_relative_position_bias
       SCREAMING_SNAKE_CASE_     						=      layer_scale_init_value
       SCREAMING_SNAKE_CASE_     						=      drop_path_rate
       SCREAMING_SNAKE_CASE_     						=      use_mean_pooling
       # decode head attributes (semantic segmentation)
       SCREAMING_SNAKE_CASE_     						=      out_indices
       SCREAMING_SNAKE_CASE_     						=      pool_scales
       # auxiliary head attributes (semantic segmentation)
       SCREAMING_SNAKE_CASE_     						=      use_auxiliary_head
       SCREAMING_SNAKE_CASE_     						=      auxiliary_loss_weight
       SCREAMING_SNAKE_CASE_     						=      auxiliary_channels
       SCREAMING_SNAKE_CASE_     						=      auxiliary_num_convs
       SCREAMING_SNAKE_CASE_     						=      auxiliary_concat_input
       SCREAMING_SNAKE_CASE_     						=      semantic_loss_ignore_index





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   version.parse("1.11" )



 @property
 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       return OrderedDict(
           [
               ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
           ]						)




 @property
 def 				lowerCAmelCase_  (							self  :		Tuple						):
       return 1E-4





import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


lowerCamelCase__			:       List[Any]         =							logging.get_logger(__name__)  # pylint: disable=invalid-name





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 def __init__(							self  :		List[Any]    ,    _lowerCAmelCase  :		Dict    ,    _lowerCAmelCase  :		Tuple=768						):
       super().__init__(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      proj_size

       SCREAMING_SNAKE_CASE_     						=      CLIPVisionModel(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      PaintByExampleMapper(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      nn.LayerNorm(config.hidden_size						)
       SCREAMING_SNAKE_CASE_     						=      nn.Linear(config.hidden_size    ,    self.proj_size						)

       # uncondition for scaling
       SCREAMING_SNAKE_CASE_     						=      nn.Parameter(torch.randn((1, 1, self.proj_size)						)						)




 def 				lowerCAmelCase_  (							self  :		Any    ,    _lowerCAmelCase  :		int    ,    _lowerCAmelCase  :		int=False						):
       SCREAMING_SNAKE_CASE_     						=      self.model(pixel_values=_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      clip_output.pooler_output
       SCREAMING_SNAKE_CASE_     						=      self.mapper(latent_states[:, None]						)
       SCREAMING_SNAKE_CASE_     						=      self.final_layer_norm(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      self.proj_out(_lowerCAmelCase						)
       if return_uncond_vector:
             return latent_states, self.uncond_vector

       return latent_states





class 	lowerCamelCase_							(				nn.Module ):


 '''simple docstring'''







 def __init__(							self  :		int    ,    _lowerCAmelCase  :		Optional[Any]						):
       super().__init__()
       SCREAMING_SNAKE_CASE_     						=      (config.num_hidden_layers + 1) // 5
       SCREAMING_SNAKE_CASE_     						=      config.hidden_size
       SCREAMING_SNAKE_CASE_     						=      1
       SCREAMING_SNAKE_CASE_     						=      nn.ModuleList(
           [
               BasicTransformerBlock(_lowerCAmelCase    ,    _lowerCAmelCase    ,    _lowerCAmelCase    ,    activation_fn='gelu'    ,    attention_bias=_lowerCAmelCase						)
               for _ in range(_lowerCAmelCase						)
           ]						)




 def 				lowerCAmelCase_  (							self  :		Union[str, Any]    ,    _lowerCAmelCase  :		Optional[Any]						):
       for block in self.blocks:
             SCREAMING_SNAKE_CASE_     						=      block(_lowerCAmelCase						)

       return hidden_states