



'''simple docstring'''







import os
import tempfile
from pathlib import Path
from unittest import TestCase

import pyarrow as pa
import pytest

from datasets.arrow_dataset import Dataset
from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
from datasets.info import DatasetInfo
from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo

from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




class 				__lowerCAmelCase(							lowerCAmelCase__      ):






			def 				_lowercase	(   self  :							Tuple      ,       SCREAMING_SNAKE_CASE  :							Union[str, Any]      ,       SCREAMING_SNAKE_CASE  :							List[Any]=False	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:int										=      (
					    filename_skip_take['filename'],
					    filename_skip_take['skip'] if 'skip' in filename_skip_take else None,
					    filename_skip_take['take'] if 'take' in filename_skip_take else None,
					)
					open(os.path.join(SCREAMING_SNAKE_CASE	)      ,       'wb'	).close()
					SCREAMING_SNAKE_CASE_						:int										=      pa.Table.from_pydict({'filename': [Path(SCREAMING_SNAKE_CASE	).name] * 100}	)
					if take == -1:
							SCREAMING_SNAKE_CASE_						:Optional[Any]										=      len(SCREAMING_SNAKE_CASE	) - skip
					if skip is not None and take is not None:
							SCREAMING_SNAKE_CASE_						:List[str]										=      pa_table.slice(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)
					return pa_table




class 				__lowerCAmelCase(							lowerCAmelCase__      ):






			def 				_lowercase	(   self  :							List[str]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      'my_name'
					SCREAMING_SNAKE_CASE_						:int										=      SplitInfo(name='train'      ,       num_examples=100	)
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      SplitInfo(name='test'      ,       num_examples=100	)
					SCREAMING_SNAKE_CASE_						:Any										=      [train_info, test_info]
					SCREAMING_SNAKE_CASE_						:int										=      SplitDict()
					split_dict.add(SCREAMING_SNAKE_CASE	)
					split_dict.add(SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:Optional[int]										=      DatasetInfo(splits=SCREAMING_SNAKE_CASE	)

					with tempfile.TemporaryDirectory() as tmp_dir:
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      ReaderTest(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)

							SCREAMING_SNAKE_CASE_						:Dict										=      'test[:33%]'
							SCREAMING_SNAKE_CASE_						:List[str]										=      Dataset(**reader.read(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)	)
							self.assertEqual(dset['filename'][0]      ,       f'{name}-test'	)
							self.assertEqual(dset.num_rows      ,       33	)
							self.assertEqual(dset.num_columns      ,       1	)

							SCREAMING_SNAKE_CASE_						:List[Any]										=      ['train', 'test[:33%]']
							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      [Split.TRAIN, ReadInstruction.from_spec('test[:33%]'	)]
							for instructions in [instructionsa, instructionsa]:
									SCREAMING_SNAKE_CASE_						:Optional[Any]										=      [reader.read(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	) for instr in instructions]
									SCREAMING_SNAKE_CASE_						,		SCREAMING_SNAKE_CASE_						:int										=      (Dataset(**SCREAMING_SNAKE_CASE	) for dataset_kwargs in datasets_kwargs)
									self.assertEqual(train_dset['filename'][0]      ,       f'{name}-train'	)
									self.assertEqual(train_dset.num_rows      ,       100	)
									self.assertEqual(train_dset.num_columns      ,       1	)
									self.assertIsInstance(train_dset.split      ,       SCREAMING_SNAKE_CASE	)
									self.assertEqual(str(train_dset.split	)      ,       'train'	)
									self.assertEqual(test_dset['filename'][0]      ,       f'{name}-test'	)
									self.assertEqual(test_dset.num_rows      ,       33	)
									self.assertEqual(test_dset.num_columns      ,       1	)
									self.assertIsInstance(test_dset.split      ,       SCREAMING_SNAKE_CASE	)
									self.assertEqual(str(test_dset.split	)      ,       'test[:33%]'	)
									del train_dset, test_dset






			def 				_lowercase	(   self  :							int	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      'my_name'
					SCREAMING_SNAKE_CASE_						:Optional[int]										=      SplitInfo(name='train'      ,       num_examples=1_000      ,       shard_lengths=[100] * 10	)
					SCREAMING_SNAKE_CASE_						:List[str]										=      [train_info]
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      SplitDict()
					split_dict.add(SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      DatasetInfo(splits=SCREAMING_SNAKE_CASE	)

					with tempfile.TemporaryDirectory() as tmp_dir:
							SCREAMING_SNAKE_CASE_						:int										=      ReaderTest(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)

							SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      'train[:33%]'
							SCREAMING_SNAKE_CASE_						:str										=      Dataset(**reader.read(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)	)
							self.assertEqual(dset['filename'][0]      ,       f'{name}-train-00000-of-00010'	)
							self.assertEqual(dset['filename'][-1]      ,       f'{name}-train-00003-of-00010'	)
							self.assertEqual(dset.num_rows      ,       330	)
							self.assertEqual(dset.num_columns      ,       1	)






			def 				_lowercase	(   self  :							int	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Tuple										=      SplitInfo(name='train'      ,       num_examples=100	)
					SCREAMING_SNAKE_CASE_						:List[Any]										=      SplitInfo(name='test'      ,       num_examples=100	)
					SCREAMING_SNAKE_CASE_						:Tuple										=      SplitDict()
					split_dict.add(SCREAMING_SNAKE_CASE	)
					split_dict.add(SCREAMING_SNAKE_CASE	)
					SCREAMING_SNAKE_CASE_						:str										=      DatasetInfo(splits=SCREAMING_SNAKE_CASE	)

					with tempfile.TemporaryDirectory() as tmp_dir:
							SCREAMING_SNAKE_CASE_						:Dict										=      ReaderTest(SCREAMING_SNAKE_CASE      ,       SCREAMING_SNAKE_CASE	)

							SCREAMING_SNAKE_CASE_						:Tuple										=      [
							    {'filename': os.path.join(SCREAMING_SNAKE_CASE      ,       'train'	)},
							    {'filename': os.path.join(SCREAMING_SNAKE_CASE      ,       'test'	), 'skip': 10, 'take': 10},
							]
							SCREAMING_SNAKE_CASE_						:Tuple										=      Dataset(**reader.read_files(SCREAMING_SNAKE_CASE      ,       original_instructions='train+test[10:20]'	)	)
							self.assertEqual(dset.num_rows      ,       110	)
							self.assertEqual(dset.num_columns      ,       1	)
							del dset







@pytest.mark.parametrize('in_memory' ,		[False, True]     )
def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      arrow_file
		with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
				SCREAMING_SNAKE_CASE_						:List[str]										=      ArrowReader.read_table(SCREAMING_SNAKE_CASE ,		in_memory=SCREAMING_SNAKE_CASE     )
		assert table.shape == dataset.data.shape
		assert set(table.column_names     ) == set(dataset.data.column_names     )
		assert dict(table.to_pydict()     ) == dict(dataset.data.to_pydict()     )  # to_pydict returns OrderedDict







@pytest.mark.parametrize('in_memory' ,		[False, True]     )
def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:int										=      arrow_file
		SCREAMING_SNAKE_CASE_						:int										=      ArrowReader('' ,		SCREAMING_SNAKE_CASE     )
		with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
				SCREAMING_SNAKE_CASE_						:int										=      reader.read_files([{'filename': filename}] ,		in_memory=SCREAMING_SNAKE_CASE     )
		assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
		SCREAMING_SNAKE_CASE_						:List[str]										=      dataset_kwargs['arrow_table']
		assert table.shape == dataset.data.shape
		assert set(table.column_names     ) == set(dataset.data.column_names     )
		assert dict(table.to_pydict()     ) == dict(dataset.data.to_pydict()     )  # to_pydict returns OrderedDict







def  SCREAMING_SNAKE_CASE__ (				):
		assert ReadInstruction('train' ,		to=10 ,		unit='abs'     ).to_spec() == "train[:10]"
		assert ReadInstruction('train' ,		from_=-80 ,		to=10 ,		unit='%'     ).to_spec() == "train[-80%:10%]"

		SCREAMING_SNAKE_CASE_						:List[str]										=      'train+test'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == spec_train_test

		SCREAMING_SNAKE_CASE_						:List[Any]										=      'train[2:10]'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == spec_train_abs

		SCREAMING_SNAKE_CASE_						:int										=      'train[15%:-20%]'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == spec_train_pct

		SCREAMING_SNAKE_CASE_						:List[str]										=      'train[:10%](closest)'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == "train[:10%]"

		SCREAMING_SNAKE_CASE_						:Dict										=      'train[:10%](pct1_dropremainder)'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == spec_train_pct_rounding

		SCREAMING_SNAKE_CASE_						:int										=      'train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)'
		assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE     ).to_spec() == spec_train_test_pct_rounding







def  SCREAMING_SNAKE_CASE__ (				):
		SCREAMING_SNAKE_CASE_						:Tuple										=      'dummy'
		SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      [SplitInfo(name='train' ,		num_examples=100     )]
		SCREAMING_SNAKE_CASE_						:Optional[Any]										=      'train[:33%]'
		SCREAMING_SNAKE_CASE_						:Any										=      'arrow'
		SCREAMING_SNAKE_CASE_						:Optional[Any]										=      'prefix'

		SCREAMING_SNAKE_CASE_						:Optional[Any]										=      make_file_instructions(SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     )
		assert isinstance(SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     )
		assert file_instructions.num_examples == 33
		assert file_instructions.file_instructions == [
		    {"filename": os.path.join(SCREAMING_SNAKE_CASE ,		F'{name}-train.arrow'     ), "skip": 0, "take": 33}
		]

		SCREAMING_SNAKE_CASE_						:List[str]										=      [SplitInfo(name='train' ,		num_examples=100 ,		shard_lengths=[10] * 10     )]
		SCREAMING_SNAKE_CASE_						:Any										=      make_file_instructions(SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     )
		assert isinstance(SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     )
		assert file_instructions.num_examples == 33
		assert file_instructions.file_instructions == [
		    {"filename": os.path.join(SCREAMING_SNAKE_CASE ,		F'{name}-train-00000-of-00010.arrow'     ), "skip": 0, "take": -1},
		    {"filename": os.path.join(SCREAMING_SNAKE_CASE ,		F'{name}-train-00001-of-00010.arrow'     ), "skip": 0, "take": -1},
		    {"filename": os.path.join(SCREAMING_SNAKE_CASE ,		F'{name}-train-00002-of-00010.arrow'     ), "skip": 0, "take": -1},
		    {"filename": os.path.join(SCREAMING_SNAKE_CASE ,		F'{name}-train-00003-of-00010.arrow'     ), "skip": 0, "take": 3},
		]







@pytest.mark.parametrize('name, expected_exception' ,		[(None, TypeError), ('', ValueError)]     )
def  SCREAMING_SNAKE_CASE__ (				SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     ):
		SCREAMING_SNAKE_CASE_						:Any										=      [SplitInfo(name='train' ,		num_examples=100     )]
		SCREAMING_SNAKE_CASE_						:int										=      'train'
		SCREAMING_SNAKE_CASE_						:Dict										=      'arrow'
		SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      'prefix_path'
		with pytest.raises(SCREAMING_SNAKE_CASE     ):
				SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      make_file_instructions(SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE ,		SCREAMING_SNAKE_CASE     )








"""simple docstring"""





UpperCamelCase					=     float("""inf""")







class 						_a  :





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_)			->   List[str]:




          '''simple docstring'''




          lowercase__:							Optional[Any]         =     [0] * n
          lowercase__:							Dict         =     [0] * n
          lowercase__:							List[Any]         =     [0] * n
          lowercase__:							str         =     [[] for _ in range(UpperCAmelCase_)]





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_=0)			->   Optional[int]:




          '''simple docstring'''




          self.adj[a].append([b, len(self.adj[b]), c, 0])
          self.adj[b].append([a, len(self.adj[a]) - 1, rcap, 0])





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_)			->   Union[str, Any]:




          '''simple docstring'''




          if vertex == sink or not flow:
                 return flow

          for i in range(self.ptr[vertex]					, len(self.adj[vertex])):
                 lowercase__:							Optional[Any]         =     self.adj[vertex][i]
                 if self.lvl[e[0]] == self.lvl[vertex] + 1:
                        lowercase__:							Optional[int]         =     self.depth_first_search(e[0]					, UpperCAmelCase_					, min(UpperCAmelCase_					, e[2] - e[3]))
                        if p:
                               self.adj[vertex][i][3] += p
                               self.adj[e[0]][e[1]][3] -= p
                               return p
                 lowercase__:							int         =     self.ptr[vertex] + 1
          return 0





   def __lowercase							(       self					, UpperCAmelCase_					, UpperCAmelCase_)			->   str:




          '''simple docstring'''




          lowercase__    ,      lowercase__:							Union[str, Any]         =     0, source
          for l in range(31):  # noqa: E741  l = 30 maybe faster for random data
                 while True:
                        lowercase__    ,      lowercase__:							Union[str, Any]         =     [0] * len(self.q), [0] * len(self.q)
                        lowercase__    ,      lowercase__    ,      lowercase__:							str         =     0, 1, 1
                        while qi < qe and not self.lvl[sink]:
                               lowercase__:							Tuple         =     self.q[qi]
                               qi += 1
                               for e in self.adj[v]:
                                      if not self.lvl[e[0]] and (e[2] - e[3]) >> (30 - l):
                                             lowercase__:							Optional[int]         =     e[0]
                                             qe += 1
                                             lowercase__:							str         =     self.lvl[v] + 1

                        lowercase__:							List[str]         =     self.depth_first_search(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_)
                        while p:
                               flow += p
                               lowercase__:							Any         =     self.depth_first_search(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_)

                        if not self.lvl[sink]:
                               break

          return flow
UpperCamelCase					=     Dinic(10)
UpperCamelCase					=     0
UpperCamelCase					=     9
for vertex in range(1, 5):
  graph.add_edge(source, vertex, 1)
for vertex in range(5, 9):
  graph.add_edge(vertex, sink, 1)
for vertex in range(1, 5):
  graph.add_edge(vertex, vertex + 4, 1)

# Now we can know that is the maximum flow(source -> sink)
print(graph.max_flow(source, sink))






