





import os

import numpy
import onnx




def     a__ (					lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_											=a.name
   UpperCAmelCase_											=b.name

   UpperCAmelCase_											=""
   UpperCAmelCase_											=""

   UpperCAmelCase_											=a == b

   UpperCAmelCase_											=name_a
   UpperCAmelCase_											=name_b

   return res




def     a__ (					lowercase__  ,    lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   for i, input_name in enumerate(node_proto.input  ):
      if input_name == name:
         node_proto.input.insert(lowercase__  ,    lowercase__  )
         node_proto.input.pop(i + 1  )

   if node_proto.op_type == "If":
      _graph_replace_input_with(node_proto.attribute[0].g  ,    lowercase__  ,    lowercase__  )
      _graph_replace_input_with(node_proto.attribute[1].g  ,    lowercase__  ,    lowercase__  )
   if node_proto.op_type == "Loop":
      _graph_replace_input_with(node_proto.attribute[0].g  ,    lowercase__  ,    lowercase__  )




def     a__ (					lowercase__  ,    lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   for n in graph_proto.node:
      _node_replace_input_with(lowercase__  ,    lowercase__  ,    lowercase__  )




def     a__ (					lowercase__  ,    lowercase__  ,    lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_											=list(model.graph.initializer  )
   UpperCAmelCase_											=list(model_without_ext.graph.initializer  )
   for i, ref_i in ind_to_replace:
      assert inits_with_data[i].name == inits[i].name
      assert inits_with_data[ref_i].name == inits[ref_i].name
      assert i > ref_i

      UpperCAmelCase_											=inits[i].name
      UpperCAmelCase_											=inits[ref_i].name

      model_without_ext.graph.initializer.remove(inits[i]  )

      # for n in model.graph.node:
      _graph_replace_input_with(model_without_ext.graph  ,    lowercase__  ,    lowercase__  )





def     a__ (					lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_											=os.path.dirname(lowercase__  )
   UpperCAmelCase_											=os.path.basename(lowercase__  )

   UpperCAmelCase_											=onnx.load(os.path.join(lowercase__  ,    lowercase__  )  )

   UpperCAmelCase_											=list(model.graph.initializer  )

   UpperCAmelCase_											=set()
   UpperCAmelCase_											={}
   UpperCAmelCase_											=[]

   UpperCAmelCase_											=0

   for i in range(len(lowercase__  )  ):
      if i in dup_set:
         continue

      for j in range(i + 1  ,    len(lowercase__  )  ):
         if j in dup_set:
            continue
         if _is_equal_tensor_proto(inits[i]  ,    inits[j]  ):
            dup_set.add(lowercase__  )
            dup_set.add(lowercase__  )

            UpperCAmelCase_											=inits[j].data_type
            UpperCAmelCase_											=numpy.prod(inits[j].dims  )
            if dtype == 1:
               mem_size *= 4
            elif dtype == 6:
               mem_size *= 4
            elif dtype == 7 or dtype == 1_1:
               mem_size *= 8
            else:
               print("unexpected data type: "  ,    lowercase__  )
            total_reduced_size += mem_size

            UpperCAmelCase_											=inits[i].name
            UpperCAmelCase_											=inits[j].name

            if name_i in dup_map:
               dup_map[name_i].append(lowercase__  )
            else:
               UpperCAmelCase_											=[name_j]
            ind_to_replace.append((j, i)  )

   print("total reduced size: "  ,    total_reduced_size / 1_0_2_4 / 1_0_2_4 / 1_0_2_4  ,    "GB"  )

   UpperCAmelCase_											=sorted(lowercase__  )
   _remove_dup_initializers_from_model(lowercase__  ,    lowercase__  ,    lowercase__  )

   UpperCAmelCase_											="optimized_" + model_file_name
   UpperCAmelCase_											=os.path.join(lowercase__  ,    lowercase__  )
   onnx.save(lowercase__  ,    lowercase__  )

   return new_model











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


__lowercase  :   Optional[int]						      =logging.get_logger(__name__)

__lowercase  :   Union[str, Any]						      ={
    """Visual-Attention-Network/van-base""": (
        """https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
    ),
}

class      A       (	__lowercase						):
      _snake_case							     ='''van'''



      def __init__(	self:						str		,  _lowerCAmelCase:						List[Any]=224		,  _lowerCAmelCase:						Any=3		,  _lowerCAmelCase:						Tuple=[7, 3, 3, 3]		,  _lowerCAmelCase:						Union[str, Any]=[4, 2, 2, 2]		,  _lowerCAmelCase:						List[str]=[64, 128, 320, 512]		,  _lowerCAmelCase:						Tuple=[3, 3, 12, 3]		,  _lowerCAmelCase:						Union[str, Any]=[8, 8, 4, 4]		,  _lowerCAmelCase:						Any="gelu"		,  _lowerCAmelCase:						Optional[int]=0.02		,  _lowerCAmelCase:						List[str]=1e-6		,  _lowerCAmelCase:						Any=1e-2		,  _lowerCAmelCase:						Any=0.0		,  _lowerCAmelCase:						Optional[Any]=0.0		,  **_lowerCAmelCase:						List[str]		,  )						->    Dict:
         '''simple docstring'''

         super().__init__(**_lowerCAmelCase       )
         UpperCAmelCase_											=image_size
         UpperCAmelCase_											=num_channels
         UpperCAmelCase_											=patch_sizes
         UpperCAmelCase_											=strides
         UpperCAmelCase_											=hidden_sizes
         UpperCAmelCase_											=depths
         UpperCAmelCase_											=mlp_ratios
         UpperCAmelCase_											=hidden_act
         UpperCAmelCase_											=initializer_range
         UpperCAmelCase_											=layer_norm_eps
         UpperCAmelCase_											=layer_scale_init_value
         UpperCAmelCase_											=drop_path_rate
         UpperCAmelCase_											=dropout_rate




