


from operator import delitem, getitem, setitem

import pytest

from data_structures.hashing.hash_map import HashMap







def        _lowerCamelCase(	lowercase__	)						->	Tuple:

		'''simple docstring'''







		return getitem, k







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	int:

		'''simple docstring'''







		return setitem, k, v







def        _lowerCamelCase(	lowercase__	)						->	List[str]:

		'''simple docstring'''







		return delitem, k







def        _lowerCamelCase(	lowercase__   , lowercase__   , *lowercase__	)						->	Tuple:

		'''simple docstring'''







		try:
				return fun(lowercase__   , *lowercase__	), None
		except Exception as e:
				return None, e


lowerCAmelCase           =		(
    _set('''key_a''', '''val_a'''),
    _set('''key_b''', '''val_b'''),
)

lowerCAmelCase           =		[
    _set('''key_a''', '''val_a'''),
    _set('''key_a''', '''val_b'''),
]

lowerCAmelCase           =		[
    _set('''key_a''', '''val_a'''),
    _set('''key_b''', '''val_b'''),
    _del('''key_a'''),
    _del('''key_b'''),
    _set('''key_a''', '''val_a'''),
    _del('''key_a'''),
]

lowerCAmelCase           =		[
    _get('''key_a'''),
    _del('''key_a'''),
    _set('''key_a''', '''val_a'''),
    _del('''key_a'''),
    _del('''key_a'''),
    _get('''key_a'''),
]

lowerCAmelCase           =		[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
]

lowerCAmelCase           =		[
    *[_set(x, x) for x in range(5)],  # guaranteed upsize
    *[_del(x) for x in range(5)],
    _set('''key_a''', '''val_b'''),
]







@pytest.mark.parametrize(
    'operations'   , (
        pytest.param(_add_items   , id='add items'	),
        pytest.param(_overwrite_items   , id='overwrite items'	),
        pytest.param(_delete_items   , id='delete items'	),
        pytest.param(_access_absent_items   , id='access absent items'	),
        pytest.param(_add_with_resize_up   , id='add with resize up'	),
        pytest.param(_add_with_resize_down   , id='add with resize down'	),
    )   , )
def        _lowerCamelCase(	lowercase__	)						->	List[Any]:

		'''simple docstring'''







		__lowercase=			HashMap(initial_block_size=4	)
		__lowercase=			{}
		for _, (fun, *args) in enumerate(lowercase__	):
				__lowercase,							__lowercase=			_run_operation(lowercase__   , lowercase__   , *lowercase__	)
				__lowercase,							__lowercase=			_run_operation(lowercase__   , lowercase__   , *lowercase__	)
				assert my_res == py_res
				assert str(lowercase__	) == str(lowercase__	)
				assert set(lowercase__	) == set(lowercase__	)
				assert len(lowercase__	) == len(lowercase__	)
				assert set(my.items()	) == set(py.items()	)







def        _lowerCamelCase(	)						->	str:

		'''simple docstring'''







		def is_public(lowercase__	) -> bool:
				return not name.startswith('_'	)

		__lowercase=			{name for name in dir({}	) if is_public(lowercase__	)}
		__lowercase=			{name for name in dir(HashMap()	) if is_public(lowercase__	)}

		assert dict_public_names > hash_public_names










import os

import numpy
import onnx







def        _lowerCamelCase(	lowercase__   , lowercase__	)						->	Union[str, Any]:

		'''simple docstring'''







		__lowercase=			a.name
		__lowercase=			b.name

		__lowercase=			''
		__lowercase=			''

		__lowercase=			a == b

		__lowercase=			name_a
		__lowercase=			name_b

		return res







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__	)						->	Union[str, Any]:

		'''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        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__	)						->	str:

		'''simple docstring'''







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







def        _lowerCamelCase(	lowercase__   , lowercase__   , lowercase__	)						->	Any:

		'''simple docstring'''







		__lowercase=			list(model.graph.initializer	)
		__lowercase=			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

				__lowercase=			inits[i].name
				__lowercase=			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        _lowerCamelCase(	lowercase__	)						->	Dict:

		'''simple docstring'''







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

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

		__lowercase=			list(model.graph.initializer	)

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

		__lowercase=			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__	)

								__lowercase=			inits[j].data_type
								__lowercase=			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

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

								if name_i in dup_map:
										dup_map[name_i].append(lowercase__	)
								else:
										__lowercase=			[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'	)

		__lowercase=			sorted(lowercase__	)
		_remove_dup_initializers_from_model(lowercase__   , lowercase__   , lowercase__	)

		__lowercase=			'optimized_' + model_file_name
		__lowercase=			os.path.join(lowercase__   , lowercase__	)
		onnx.save(lowercase__   , lowercase__	)

		return new_model






