

"""simple docstring"""






import os

import numpy
import onnx





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      Tuple:
 __magic_name__     =      a.name
 __magic_name__     =      b.name

 __magic_name__     =      ''''''
 __magic_name__     =      ''''''

 __magic_name__     =      a == b

 __magic_name__     =      name_a
 __magic_name__     =      name_b

 return res





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase      ,   __UpperCamelCase						) ->      str:
 for i, input_name in enumerate(node_proto.input						):
  if input_name == name:
   node_proto.input.insert(__UpperCamelCase      ,   __UpperCamelCase						)
   node_proto.input.pop(i + 1						)

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





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase      ,   __UpperCamelCase						) ->      List[str]:
 for n in graph_proto.node:
  _node_replace_input_with(__UpperCamelCase      ,   __UpperCamelCase      ,   __UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase      ,   __UpperCamelCase						) ->      Union[str, Any]:
 __magic_name__     =      list(model.graph.initializer						)
 __magic_name__     =      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

  __magic_name__     =      inits[i].name
  __magic_name__     =      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      ,   __UpperCamelCase      ,   __UpperCamelCase						)





def 	lowercase      (   __UpperCamelCase						) ->      Optional[Any]:
 __magic_name__     =      os.path.dirname(__UpperCamelCase						)
 __magic_name__     =      os.path.basename(__UpperCamelCase						)

 __magic_name__     =      onnx.load(os.path.join(__UpperCamelCase      ,   __UpperCamelCase						)						)

 __magic_name__     =      list(model.graph.initializer						)

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

 __magic_name__     =      0

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

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

    __magic_name__     =      inits[j].data_type
    __magic_name__     =      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: '''      ,   __UpperCamelCase						)
    total_reduced_size += mem_size

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

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

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

 __magic_name__     =      sorted(__UpperCamelCase						)
 _remove_dup_initializers_from_model(__UpperCamelCase      ,   __UpperCamelCase      ,   __UpperCamelCase						)

 __magic_name__     =      '''optimized_''' + model_file_name
 __magic_name__     =      os.path.join(__UpperCamelCase      ,   __UpperCamelCase						)
 onnx.save(__UpperCamelCase      ,   __UpperCamelCase						)

 return new_model




"""simple docstring"""






import pytest

import datasets


# Import fixture modules as plugins
__lowerCamelCase										=		["tests.fixtures.files", "tests.fixtures.hub", "tests.fixtures.fsspec"]





def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      str:
 # Mark tests as "unit" by default if not marked as "integration" (or already marked as "unit")
 for item in items:
  if any(marker in item.keywords for marker in ['''integration''', '''unit''']						):
   continue
  item.add_marker(pytest.mark.unit						)





def 	lowercase      (   __UpperCamelCase						) ->      Union[str, Any]:
 config.addinivalue_line('''markers'''      ,   '''torchaudio_latest: mark test to run with torchaudio>=0.12'''						)





@pytest.fixture(autouse=__UpperCamelCase						)
def 	lowercase      (   __UpperCamelCase      ,   __UpperCamelCase						) ->      Dict:
 # test_hf_cache_home = tmp_path_factory.mktemp("cache")  # TODO: why a cache dir per test function does not work?
 __magic_name__     =      tmp_path_factory.getbasetemp() / '''cache'''
 __magic_name__     =      test_hf_cache_home / '''datasets'''
 __magic_name__     =      test_hf_cache_home / '''metrics'''
 __magic_name__     =      test_hf_cache_home / '''modules'''
 monkeypatch.setattr('''datasets.config.HF_DATASETS_CACHE'''      ,   str(__UpperCamelCase						)						)
 monkeypatch.setattr('''datasets.config.HF_METRICS_CACHE'''      ,   str(__UpperCamelCase						)						)
 monkeypatch.setattr('''datasets.config.HF_MODULES_CACHE'''      ,   str(__UpperCamelCase						)						)
 __magic_name__     =      test_hf_datasets_cache / '''downloads'''
 monkeypatch.setattr('''datasets.config.DOWNLOADED_DATASETS_PATH'''      ,   str(__UpperCamelCase						)						)
 __magic_name__     =      test_hf_datasets_cache / '''downloads''' / '''extracted'''
 monkeypatch.setattr('''datasets.config.EXTRACTED_DATASETS_PATH'''      ,   str(__UpperCamelCase						)						)





@pytest.fixture(autouse=__UpperCamelCase      ,   scope='''session'''						)
def 	lowercase      (   ) ->      Any:
 datasets.disable_progress_bar()





@pytest.fixture(autouse=__UpperCamelCase						)
def 	lowercase      (   __UpperCamelCase						) ->      str:
 # don't take tests into account when counting downloads
 monkeypatch.setattr('''datasets.config.HF_UPDATE_DOWNLOAD_COUNTS'''      ,   __UpperCamelCase						)





@pytest.fixture
def 	lowercase      (   __UpperCamelCase						) ->      int:
 # Required to suppress RemovedIn20Warning when feature(s) are not compatible with SQLAlchemy 2.0
 # To be removed once SQLAlchemy 2.0 supported
 monkeypatch.setattr('''sqlalchemy.util.deprecations.SILENCE_UBER_WARNING'''      ,   __UpperCamelCase						)

