import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil




class    _UpperCamelCase      (						_UpperCAmelCase ):


			"""simple docstring"""






			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence([1, 2, 3]						)						)
							self.assertEqual(arr.type      ,   pa.intaa()						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							with self.assertRaises(lowerCAmelCase__						):
											__lowercase 			=							pa.array(TypedSequence([1, 2, 3]						)      ,   type=pa.intaa()						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					List[str]:

							'''simple docstring'''


							with self.assertRaises(lowerCAmelCase__						):
											__lowercase 			=							pa.array(TypedSequence([1, 2, 3]      ,   try_type=Value('''bool'''						)      ,   type=Value('''int64'''						)						)						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					int:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence([1, 2, 3]      ,   type=Value('''int32'''						)						)						)
							self.assertEqual(arr.type      ,   pa.intaa()						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Optional[Any]:

							'''simple docstring'''


							with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
											__lowercase 			=							pa.array(TypedSequence(['''foo''', '''bar''']      ,   type=Value('''int64'''						)						)						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Tuple:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence([1, 2, 3]      ,   try_type=Value('''int32'''						)						)						)
							self.assertEqual(arr.type      ,   pa.intaa()						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Optional[Any]:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence(['''foo''', '''bar''']      ,   try_type=Value('''int64'''						)						)						)
							self.assertEqual(arr.type      ,   pa.string()						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence([[[1, 2, 3]]]      ,   type=ArrayaD((1, 3)      ,   '''int64'''						)						)						)
							self.assertEqual(arr.type      ,   ArrayaDExtensionType((1, 3)      ,   '''int64'''						)						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					List[str]:

							'''simple docstring'''


							with self.assertRaises((TypeError, pa.lib.ArrowInvalid)						):
											__lowercase 			=							pa.array(TypedSequence(['''foo''', '''bar''']      ,   type=ArrayaD((1, 3)      ,   '''int64'''						)						)						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Tuple:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence([[[1, 2, 3]]]      ,   try_type=ArrayaD((1, 3)      ,   '''int64'''						)						)						)
							self.assertEqual(arr.type      ,   ArrayaDExtensionType((1, 3)      ,   '''int64'''						)						)





			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Dict:

							'''simple docstring'''


							__lowercase 			=							pa.array(TypedSequence(['''foo''', '''bar''']      ,   try_type=ArrayaD((1, 3)      ,   '''int64'''						)						)						)
							self.assertEqual(arr.type      ,   pa.string()						)





			@require_pil
			def        _SCREAMING_SNAKE_CASE			(   self						)     ->					Tuple:

							'''simple docstring'''


							import PIL.Image

							__lowercase 			=							PIL.Image.fromarray(np.arange(10      ,   dtype=np.uinta						).reshape(2      ,   5						)						)
							with patch(
							    '''datasets.arrow_writer.cast_to_python_objects'''      ,   side_effect=lowerCAmelCase__						) as mock_cast_to_python_objects:
											__lowercase 			=							pa.array(TypedSequence([{'''path''': None, '''bytes''': B'''image_bytes'''}, pil_image]      ,   type=Image()						)						)
											__lowercase 			=							mock_cast_to_python_objects.call_args_list[-1]
											self.assertIn('''optimize_list_casting'''      ,   lowerCAmelCase__						)
											self.assertFalse(kwargs['''optimize_list_casting''']						)





def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferReader(SCREAMING_SNAKE_CASE__							) if isinstance(SCREAMING_SNAKE_CASE__							,			pa.Buffer							) else pa.memory_map(SCREAMING_SNAKE_CASE__							)
				__lowercase 			=							pa.ipc.open_stream(SCREAMING_SNAKE_CASE__							)
				__lowercase 			=							f.read_all()
				assert len(pa_table.to_batches()							) == expected_num_chunks
				assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
				del pa_table





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 1, 10]							)
@pytest.mark.parametrize(
    '''fields'''							,			[None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				__lowercase 			=							pa.schema(SCREAMING_SNAKE_CASE__							) if fields else None
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							,			schema=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write({'''col_1''': '''foo''', '''col_2''': 1}							)
								writer.write({'''col_1''': '''bar''', '''col_2''': 2}							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				if not fields:
								__lowercase 			=							{"""col_1""": pa.string(), """col_2""": pa.intaa()}
				assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__							,			metadata=writer._schema.metadata							)
				_check_output(output.getvalue()							,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





def 				UpperCAmelCase						(    ):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				__lowercase 			=							Features({'''labels''': ClassLabel(names=['''neg''', '''pos''']							)}							)
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							,			features=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write({'''labels''': 0}							)
								writer.write({'''labels''': 1}							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				assert writer._schema == features.arrow_schema
				assert writer._schema.metadata == features.arrow_schema.metadata
				__lowercase 			=							pa.BufferReader(output.getvalue()							)
				__lowercase 			=							pa.ipc.open_stream(SCREAMING_SNAKE_CASE__							)
				__lowercase 			=							f.read_all()
				__lowercase 			=							pa_table.schema
				assert pa_table.num_rows == 2
				assert schema == features.arrow_schema
				assert schema.metadata == features.arrow_schema.metadata
				assert features == Features.from_arrow_schema(SCREAMING_SNAKE_CASE__							)





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 1, 10]							)
def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				with ArrowWriter(
				    stream=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							,			hash_salt='''split_name'''							,			check_duplicates=SCREAMING_SNAKE_CASE__							,			) as writer:
								with pytest.raises(SCREAMING_SNAKE_CASE__							):
												writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,			key=[1, 2]							)
												__lowercase 			=							writer.finalize()





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 2, 10]							)
def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				with ArrowWriter(
				    stream=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							,			hash_salt='''split_name'''							,			check_duplicates=SCREAMING_SNAKE_CASE__							,			) as writer:
								with pytest.raises(SCREAMING_SNAKE_CASE__							):
												writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,			key=10							)
												writer.write({'''col_1''': '''bar''', '''col_2''': 2}							,			key=10							)
												__lowercase 			=							writer.finalize()





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 2, 10]							)
def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				with ArrowWriter(
				    stream=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							,			hash_salt='''split_name'''							,			check_duplicates=SCREAMING_SNAKE_CASE__							,			) as writer:
								writer.write({'''col_1''': '''foo''', '''col_2''': 1}							,			key=1							)
								writer.write({'''col_1''': '''bar''', '''col_2''': 2}							,			key=2							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				_check_output(output.getvalue()							,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 1, 10]							)
@pytest.mark.parametrize(
    '''fields'''							,			[None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				__lowercase 			=							pa.schema(SCREAMING_SNAKE_CASE__							) if fields else None
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							,			schema=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}							)
								writer.write_batch({'''col_1''': [], '''col_2''': []}							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				if not fields:
								__lowercase 			=							{"""col_1""": pa.string(), """col_2""": pa.intaa()}
				assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__							,			metadata=writer._schema.metadata							)
				_check_output(output.getvalue()							,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 1, 10]							)
@pytest.mark.parametrize(
    '''fields'''							,			[None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				__lowercase 			=							pa.schema(SCREAMING_SNAKE_CASE__							) if fields else None
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							,			schema=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write_table(pa.Table.from_pydict({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}							)							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				if not fields:
								__lowercase 			=							{"""col_1""": pa.string(), """col_2""": pa.intaa()}
				assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__							,			metadata=writer._schema.metadata							)
				_check_output(output.getvalue()							,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





@pytest.mark.parametrize('''writer_batch_size'''							,			[None, 1, 10]							)
@pytest.mark.parametrize(
    '''fields'''							,			[None, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}, {'''col_1''': pa.string(), '''col_2''': pa.intaa()}]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				__lowercase 			=							pa.schema(SCREAMING_SNAKE_CASE__							) if fields else None
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							,			schema=SCREAMING_SNAKE_CASE__							,			writer_batch_size=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write_row(pa.Table.from_pydict({'''col_1''': ['''foo'''], '''col_2''': [1]}							)							)
								writer.write_row(pa.Table.from_pydict({'''col_1''': ['''bar'''], '''col_2''': [2]}							)							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				if not fields:
								__lowercase 			=							{"""col_1""": pa.string(), """col_2""": pa.intaa()}
				assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__							,			metadata=writer._schema.metadata							)
				_check_output(output.getvalue()							,			expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)





def 				UpperCAmelCase						(    ):







				"""simple docstring"""



				with tempfile.TemporaryDirectory() as tmp_dir:
								__lowercase 			=							{"""col_1""": pa.string(), """col_2""": pa.intaa()}
								__lowercase 			=							os.path.join(SCREAMING_SNAKE_CASE__							,			'''test.arrow'''							)
								with ArrowWriter(path=SCREAMING_SNAKE_CASE__							,			schema=pa.schema(SCREAMING_SNAKE_CASE__							)							) as writer:
												writer.write_batch({'''col_1''': ['''foo''', '''bar'''], '''col_2''': [1, 2]}							)
												__lowercase 			=							writer.finalize()
								assert num_examples == 2
								assert num_bytes > 0
								assert writer._schema == pa.schema(SCREAMING_SNAKE_CASE__							,			metadata=writer._schema.metadata							)
								_check_output(SCREAMING_SNAKE_CASE__							,			1							)





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				if pa.types.is_list(SCREAMING_SNAKE_CASE__							):
								return get_base_dtype(arr_type.value_type							)
				else:
								return arr_type





def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				if isinstance(lst[0]							,			SCREAMING_SNAKE_CASE__							):
								change_first_primitive_element_in_list(lst[0]							,			SCREAMING_SNAKE_CASE__							)
				else:
								__lowercase 			=							value





@pytest.mark.parametrize('''optimized_int_type, expected_dtype'''							,			[(None, pa.intaa()), (Value('''int32'''							), pa.intaa())]							)
@pytest.mark.parametrize('''sequence'''							,			[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.array(TypedSequence(SCREAMING_SNAKE_CASE__							,			optimized_int_type=SCREAMING_SNAKE_CASE__							)							)
				assert get_base_dtype(arr.type							) == expected_dtype





@pytest.mark.parametrize(
    '''col, expected_dtype'''							,			[
        ('''attention_mask''', pa.inta()),
        ('''special_tokens_mask''', pa.inta()),
        ('''token_type_ids''', pa.inta()),
        ('''input_ids''', pa.intaa()),
        ('''other''', pa.intaa()),
    ]							,			)
@pytest.mark.parametrize('''sequence'''							,			[[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							pa.array(OptimizedTypedSequence(SCREAMING_SNAKE_CASE__							,			col=SCREAMING_SNAKE_CASE__							)							)
				assert get_base_dtype(arr.type							) == expected_dtype

				# not in range
				if col != "other":
								# avoids errors due to in-place modifications
								__lowercase 			=							copy.deepcopy(SCREAMING_SNAKE_CASE__							)
								__lowercase 			=							np.iinfo(expected_dtype.to_pandas_dtype()							).max + 1
								change_first_primitive_element_in_list(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__							)
								__lowercase 			=							pa.array(OptimizedTypedSequence(SCREAMING_SNAKE_CASE__							,			col=SCREAMING_SNAKE_CASE__							)							)
								assert get_base_dtype(arr.type							) == pa.intaa()





@pytest.mark.parametrize('''raise_exception'''							,			[False, True]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				__lowercase 			=							str(tmp_path / '''dataset-train.arrow'''							)
				try:
								with ArrowWriter(path=SCREAMING_SNAKE_CASE__							) as writer:
												if raise_exception:
																raise pa.lib.ArrowInvalid()
												else:
																writer.stream.close()
				except pa.lib.ArrowInvalid:
								pass
				finally:
								assert writer.stream.closed





def 				UpperCAmelCase						(    lowercase							):







				"""simple docstring"""



				__lowercase 			=							"""mock://dataset-train.arrow"""
				with ArrowWriter(path=SCREAMING_SNAKE_CASE__							,			storage_options=mockfs.storage_options							) as writer:
								assert isinstance(writer._fs							,			type(SCREAMING_SNAKE_CASE__							)							)
								assert writer._fs.storage_options == mockfs.storage_options
								writer.write({'''col_1''': '''foo''', '''col_2''': 1}							)
								writer.write({'''col_1''': '''bar''', '''col_2''': 2}							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				assert mockfs.exists(SCREAMING_SNAKE_CASE__							)





def 				UpperCAmelCase						(    ):







				"""simple docstring"""



				__lowercase 			=							pa.BufferOutputStream()
				with ParquetWriter(stream=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write({'''col_1''': '''foo''', '''col_2''': 1}							)
								writer.write({'''col_1''': '''bar''', '''col_2''': 2}							)
								__lowercase 			=							writer.finalize()
				assert num_examples == 2
				assert num_bytes > 0
				__lowercase 			=							pa.BufferReader(output.getvalue()							)
				__lowercase 			=							pq.read_table(SCREAMING_SNAKE_CASE__							)
				assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}





@require_pil
@pytest.mark.parametrize('''embed_local_files'''							,			[False, True]							)
def 				UpperCAmelCase						(    lowercase							,			lowercase							):







				"""simple docstring"""



				import PIL.Image

				__lowercase 			=							str(tmp_path / '''test_image_rgb.jpg'''							)
				PIL.Image.fromarray(np.zeros((5, 5)							,			dtype=np.uinta							)							).save(SCREAMING_SNAKE_CASE__							,			format='''png'''							)
				__lowercase 			=							pa.BufferOutputStream()
				with ParquetWriter(
				    stream=SCREAMING_SNAKE_CASE__							,			features=Features({'''image''': Image()}							)							,			embed_local_files=SCREAMING_SNAKE_CASE__							) as writer:
								writer.write({'''image''': image_path}							)
								writer.finalize()
				__lowercase 			=							pa.BufferReader(output.getvalue()							)
				__lowercase 			=							pq.read_table(SCREAMING_SNAKE_CASE__							)
				__lowercase 			=							pa_table.to_pydict()
				if embed_local_files:
								assert isinstance(out['''image'''][0]['''path''']							,			SCREAMING_SNAKE_CASE__							)
								with open(SCREAMING_SNAKE_CASE__							,			'''rb'''							) as f:
												assert out["image"][0]["bytes"] == f.read()
				else:
								assert out["image"][0]["path"] == image_path
								assert out["image"][0]["bytes"] is None





def 				UpperCAmelCase						(    ):







				"""simple docstring"""



				__lowercase 			=							pa.schema([pa.field('''col_1'''							,			pa.string()							,			nullable=SCREAMING_SNAKE_CASE__							)]							)
				__lowercase 			=							pa.BufferOutputStream()
				with ArrowWriter(stream=SCREAMING_SNAKE_CASE__							) as writer:
								writer._build_writer(inferred_schema=SCREAMING_SNAKE_CASE__							)
								assert writer._schema == pa.schema([pa.field('''col_1'''							,			pa.string()							)]							)

import os

import numpy
import onnx







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       lowercase							:     int       	=      a.name
       lowercase							:     Any       	=      b.name

       lowercase							:     Optional[Any]       	=      """"""
       lowercase							:     Dict       	=      """"""

       lowercase							:     int       	=      a == b

       lowercase							:     int       	=      name_a
       lowercase							:     List[str]       	=      name_b

       return res







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

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







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    Union[str, Any]:
       for n in graph_proto.node:
              _node_replace_input_with(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				) ->    List[Any]:
       lowercase							:     Any       	=      list(model.graph.initializer				)
       lowercase							:     Dict       	=      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							:     Union[str, Any]       	=      inits[i].name
              lowercase							:     Dict       	=      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					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)







def 						_snake_case(  SCREAMING_SNAKE_CASE__				) ->    List[str]:
       lowercase							:     Union[str, Any]       	=      os.path.dirname(SCREAMING_SNAKE_CASE__				)
       lowercase							:     Dict       	=      os.path.basename(SCREAMING_SNAKE_CASE__				)

       lowercase							:     str       	=      onnx.load(os.path.join(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)				)

       lowercase							:     List[str]       	=      list(model.graph.initializer				)

       lowercase							:     Tuple       	=      set()
       lowercase							:     int       	=      {}
       lowercase							:     Optional[Any]       	=      []

       lowercase							:     Dict       	=      0

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

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

                            lowercase							:     int       	=      inits[j].data_type
                            lowercase							:     Optional[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: """					,	SCREAMING_SNAKE_CASE__				)
                            total_reduced_size += mem_size

                            lowercase							:     Tuple       	=      inits[i].name
                            lowercase							:     int       	=      inits[j].name

                            if name_i in dup_map:
                                   dup_map[name_i].append(SCREAMING_SNAKE_CASE__				)
                            else:
                                   lowercase							:     List[str]       	=      [name_j]
                            ind_to_replace.append((j, i)				)

       print("""total reduced size: """					,	total_reduced_size / 1_024 / 1_024 / 1_024					,	"""GB"""				)

       lowercase							:     str       	=      sorted(SCREAMING_SNAKE_CASE__				)
       _remove_dup_initializers_from_model(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       lowercase							:     Optional[Any]       	=      """optimized_""" + model_file_name
       lowercase							:     Dict       	=      os.path.join(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)
       onnx.save(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__				)

       return new_model
