


'''simple docstring'''


import os

import numpy
import onnx




def      lowerCamelCase					(      lowerCamelCase  :      Tuple							,						lowerCamelCase  :      Tuple):
      A_						:  Tuple          =				a.name
      A_						:  int          =				b.name

      A_						:  str          =				""""""
      A_						:  List[str]          =				""""""

      A_						:  str          =				a == b

      A_						:  Union[str, Any]          =				name_a
      A_						:  Optional[int]          =				name_b

      return res




def      lowerCamelCase					(      lowerCamelCase  :      Dict							,						lowerCamelCase  :      List[str]							,						lowerCamelCase  :      str):
      for i, input_name in enumerate(node_proto.input):
            if input_name == name:
                  node_proto.input.insert(lowerCamelCase							,						lowerCamelCase)
                  node_proto.input.pop(i + 1)

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




def      lowerCamelCase					(      lowerCamelCase  :      List[Any]							,						lowerCamelCase  :      Any							,						lowerCamelCase  :      Any):
      for n in graph_proto.node:
            _node_replace_input_with(lowerCamelCase							,						lowerCamelCase							,						lowerCamelCase)




def      lowerCamelCase					(      lowerCamelCase  :      Dict							,						lowerCamelCase  :      List[Any]							,						lowerCamelCase  :      Tuple):
      A_						:  int          =				list(model.graph.initializer)
      A_						:  str          =				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

            A_						:  Tuple          =				inits[i].name
            A_						:  List[str]          =				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							,						lowerCamelCase							,						lowerCamelCase)






def      lowerCamelCase					(      lowerCamelCase  :      Optional[int]):
      A_						:  Any          =				os.path.dirname(lowerCamelCase)
      A_						:  Optional[Any]          =				os.path.basename(lowerCamelCase)

      A_						:  Tuple          =				onnx.load(os.path.join(lowerCamelCase							,						lowerCamelCase))

      A_						:  str          =				list(model.graph.initializer)

      A_						:  Union[str, Any]          =				set()
      A_						:  Dict          =				{}
      A_						:  int          =				[]

      A_						:  Optional[Any]          =				0

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

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

                        A_						:  str          =				inits[j].data_type
                        A_						:  int          =				numpy.prod(inits[j].dims)
                        if dtype == 1:
                              mem_size *= 4
                        elif dtype == 6:
                              mem_size *= 4
                        elif dtype == 7 or dtype == 11:
                              mem_size *= 8
                        else:
                              print("""unexpected data type: """							,						lowerCamelCase)
                        total_reduced_size += mem_size

                        A_						:  List[Any]          =				inits[i].name
                        A_						:  List[Any]          =				inits[j].name

                        if name_i in dup_map:
                              dup_map[name_i].append(lowerCamelCase)
                        else:
                              A_						:  Any          =				[name_j]
                        ind_to_replace.append((j, i))

      print("""total reduced size: """							,						total_reduced_size / 1024 / 1024 / 1024							,						"""GB""")

      A_						:  List[Any]          =				sorted(lowerCamelCase)
      _remove_dup_initializers_from_model(lowerCamelCase							,						lowerCamelCase							,						lowerCamelCase)

      A_						:  Optional[int]          =				"""optimized_""" + model_file_name
      A_						:  List[str]          =				os.path.join(lowerCamelCase							,						lowerCamelCase)
      onnx.save(lowerCamelCase							,						lowerCamelCase)

      return new_model




'''simple docstring'''


import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
     print('Googling.....')
     __magic_name__			=      'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
     __magic_name__			=      requests.get(url, headers={'UserAgent': UserAgent().random})
     # res.raise_for_status()
     with open('project1a.html', 'wb') as out_file:  # only for knowing the class
          for data in res.iter_content(10_000):
               out_file.write(data)
     __magic_name__			=      BeautifulSoup(res.text, 'html.parser')
     __magic_name__			=      list(soup.select('.eZt8xd'))[:5]

     print(len(links))
     for link in links:
          if link.text == "Maps":
               webbrowser.open(link.get('href'))
          else:
               webbrowser.open(f"""https://google.com{link.get('href')}""")
