




"""simple docstring"""






import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch

import multiprocess
import numpy as np
import pytest

from datasets.utils.py_utils import (
    NestedDataStructure,
    asdict,
    iflatmap_unordered,
    map_nested,
    temp_seed,
    temporary_assignment,
    zip_dict,
)

from .utils import require_tf, require_torch







def 	_snake_case     (							lowercase__						):  # picklable for multiprocessing
				return x.sum()







def 	_snake_case     (							lowercase__						):  # picklable for multiprocessing
				return i + 1






@dataclass
class lowerCAmelCase__      :






			'''simple docstring'''



			lowerCamelCase__ =     42
			lowerCamelCase__ =     42






class lowerCAmelCase__      (	lowercase		):






			'''simple docstring'''



			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       {}
							_lowerCamelCase	:     Tuple       =       []
							_lowerCamelCase	:     Tuple       =       1
							_lowerCamelCase	:     Union[str, Any]       =       [1, 2]
							_lowerCamelCase	:     str       =       {'a': 1, 'b': 2}
							_lowerCamelCase	:     Tuple       =       {'a': [1, 2], 'b': [3, 4]}
							_lowerCamelCase	:     Optional[int]       =       {'a': {'1': 1}, 'b': 2}
							_lowerCamelCase	:     Dict       =       {'a': 1, 'b': 2, 'c': 3, 'd': 4}
							_lowerCamelCase	:     Any       =       {}
							_lowerCamelCase	:     Tuple       =       []
							_lowerCamelCase	:     List[str]       =       2
							_lowerCamelCase	:     List[str]       =       [2, 3]
							_lowerCamelCase	:     Tuple       =       {'a': 2, 'b': 3}
							_lowerCamelCase	:     Union[str, Any]       =       {'a': [2, 3], 'b': [4, 5]}
							_lowerCamelCase	:     List[str]       =       {'a': {'1': 2}, 'b': 3}
							_lowerCamelCase	:     Optional[int]       =       {'a': 2, 'b': 3, 'c': 4, 'd': 5}
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    )    , lowercase    )

							_lowerCamelCase	:     Union[str, Any]       =       2
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(map_nested(lowercase    , lowercase    , num_proc=lowercase    )    , lowercase    )

							_lowerCamelCase	:     int       =       {'a': np.eye(2    ), 'b': np.zeros(3    ), 'c': np.ones(2    )}
							_lowerCamelCase	:     Optional[int]       =       {'a': 2, 'b': 0, 'c': 2}
							_lowerCamelCase	:     List[Any]       =       {
							    'a': np.eye(2    ).astype(lowercase    ),
							    'b': np.zeros(3    ).astype(lowercase    ),
							    'c': np.ones(2    ).astype(lowercase    ),
							}
							self.assertEqual(map_nested(lowercase    , lowercase    , map_numpy=lowercase    )    , lowercase    )
							self.assertEqual(
							    {k: v.tolist() for k, v in map_nested(lowercase    , lowercase    , map_numpy=lowercase    ).items()}    , {k: v.tolist() for k, v in expected_map_nested_sna_int.items()}    , )
							self.assertEqual(map_nested(lowercase    , lowercase    , map_numpy=lowercase    , num_proc=lowercase    )    , lowercase    )
							self.assertEqual(
							    {k: v.tolist() for k, v in map_nested(lowercase    , lowercase    , map_numpy=lowercase    , num_proc=lowercase    ).items()}    , {k: v.tolist() for k, v in expected_map_nested_sna_int.items()}    , )
							with self.assertRaises(lowercase    ):  # can't pickle a local lambda
											map_nested(lambda lowercase    : x + 1    , lowercase    , num_proc=lowercase    )
			def    A_       (    self    ):
							_lowerCamelCase	:     List[str]       =       {'a': 1, 'b': 2}
							_lowerCamelCase	:     List[str]       =       {'a': 3, 'b': 4}
							_lowerCamelCase	:     int       =       {'a': 5, 'b': 6}
							_lowerCamelCase	:     Union[str, Any]       =       sorted([('a', (1, 3, 5)), ('b', (2, 4, 6))]    )
							self.assertEqual(sorted(zip_dict(lowercase    , lowercase    , lowercase    )    )    , lowercase    )






			def    A_       (    self    ):






							class lowerCAmelCase__      :






										'''simple docstring'''



										lowerCamelCase__ =     """bar"""

							_lowerCamelCase	:     Optional[Any]       =       Foo()
							self.assertEqual(foo.my_attr    , 'bar'    )
							with temporary_assignment(lowercase    , 'my_attr'    , 'BAR'    ):
											self.assertEqual(foo.my_attr    , 'BAR'    )
							self.assertEqual(foo.my_attr    , 'bar'    )







@pytest.mark.parametrize(
    'iterable_length, num_proc, expected_num_proc'				,       [
        (1, None, 1),
        (1, 1, 1),
        (2, None, 1),
        (2, 1, 1),
        (2, 2, 1),
        (2, 3, 1),
        (3, 2, 1),
        (16, 16, 16),
        (16, 17, 16),
        (17, 16, 16),
    ]				,       )
def 	_snake_case     (							lowercase__				,       lowercase__				,       lowercase__						):
				with patch('datasets.utils.py_utils._single_map_nested'						) as mock_single_map_nested, patch(
				    'datasets.parallel.parallel.Pool'						) as mock_multiprocessing_pool:
								_lowerCamelCase	:     int       =       {f'''{i}''': i for i in range(lowercase__						)}
								_lowerCamelCase	:     List[str]       =       map_nested(lambda lowercase__						: x + 10				,       lowercase__				,       num_proc=lowercase__				,       parallel_min_length=16						)
								if expected_num_proc == 1:
												assert mock_single_map_nested.called
												assert not mock_multiprocessing_pool.called
								else:
												assert not mock_single_map_nested.called
												assert mock_multiprocessing_pool.called
												assert mock_multiprocessing_pool.call_args[0][0] == expected_num_proc






class lowerCAmelCase__      (	lowercase		):






			'''simple docstring'''



			@require_tf
			def    A_       (    self    ):
							import tensorflow as tf
							from tensorflow.keras import layers

							_lowerCamelCase	:     List[Any]       =       layers.Dense(2    )

							def gen_random_output():
											_lowerCamelCase	:     str       =       tf.random.uniform((1, 3)    )
											return model(lowercase    ).numpy()

							with temp_seed(42    , set_tensorflow=lowercase    ):
											_lowerCamelCase	:     List[str]       =       gen_random_output()
							with temp_seed(42    , set_tensorflow=lowercase    ):
											_lowerCamelCase	:     Optional[int]       =       gen_random_output()
							_lowerCamelCase	:     str       =       gen_random_output()

							np.testing.assert_equal(lowercase    , lowercase    )
							self.assertGreater(np.abs(outa - outa    ).sum()    , 0    )
			@require_torch
			def    A_       (    self    ):
							import torch

							def gen_random_output():
											_lowerCamelCase	:     Dict       =       torch.nn.Linear(3    , 2    )
											_lowerCamelCase	:     Tuple       =       torch.rand(1    , 3    )
											return model(lowercase    ).detach().numpy()

							with temp_seed(42    , set_pytorch=lowercase    ):
											_lowerCamelCase	:     Optional[int]       =       gen_random_output()
							with temp_seed(42    , set_pytorch=lowercase    ):
											_lowerCamelCase	:     List[str]       =       gen_random_output()
							_lowerCamelCase	:     List[Any]       =       gen_random_output()

							np.testing.assert_equal(lowercase    , lowercase    )
							self.assertGreater(np.abs(outa - outa    ).sum()    , 0    )






			def    A_       (    self    ):
							def gen_random_output():
											return np.random.rand(1    , 3    )

							with temp_seed(42    ):
											_lowerCamelCase	:     Union[str, Any]       =       gen_random_output()
							with temp_seed(42    ):
											_lowerCamelCase	:     Tuple       =       gen_random_output()
							_lowerCamelCase	:     Any       =       gen_random_output()

							np.testing.assert_equal(lowercase    , lowercase    )
							self.assertGreater(np.abs(outa - outa    ).sum()    , 0    )







@pytest.mark.parametrize('input_data'				,       [{}]						)
def 	_snake_case     (							lowercase__						):
				_lowerCamelCase	:     List[Any]       =       NestedDataStructure(lowercase__						).data
				assert output_data == input_data







@pytest.mark.parametrize(
    'data, expected_output'				,       [
        ({}, []),
        ([], []),
        ('foo', ['foo']),
        (['foo', 'bar'], ['foo', 'bar']),
        ([['foo', 'bar']], ['foo', 'bar']),
        ([[['foo'], ['bar']]], ['foo', 'bar']),
        ([[['foo'], 'bar']], ['foo', 'bar']),
        ({'a': 1, 'b': 2}, [1, 2]),
        ({'a': [1, 2], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[1, 2]], 'b': [[3, 4]]}, [1, 2, 3, 4]),
        ({'a': [[1, 2]], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [[[3], [4]]]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [[3, 4]]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [3, 4]}, [1, 2, 3, 4]),
        ({'a': [[[1], [2]]], 'b': [3, [4]]}, [1, 2, 3, 4]),
        ({'a': {'1': 1}, 'b': 2}, [1, 2]),
        ({'a': {'1': [1]}, 'b': 2}, [1, 2]),
        ({'a': {'1': [1]}, 'b': [2]}, [1, 2]),
    ]				,       )
def 	_snake_case     (							lowercase__				,       lowercase__						):
				_lowerCamelCase	:     Union[str, Any]       =       NestedDataStructure(lowercase__						).flatten()
				assert output == expected_output







def 	_snake_case     (							):
				_lowerCamelCase	:     List[str]       =       A(x=1				,       y='foobar'						)
				_lowerCamelCase	:     List[str]       =       {'x': 1, 'y': 'foobar'}
				assert asdict(lowercase__						) == expected_output

				_lowerCamelCase	:     Optional[Any]       =       {'a': {'b': A(x=10				,       y='foo'						)}, 'c': [A(x=20				,       y='bar'						)]}
				_lowerCamelCase	:     List[Any]       =       {'a': {'b': {'x': 10, 'y': 'foo'}}, 'c': [{'x': 20, 'y': 'bar'}]}
				assert asdict(lowercase__						) == expected_output

				with pytest.raises(lowercase__						):
								asdict([1, A(x=10				,       y='foo'						)]						)







def 	_snake_case     (							lowercase__						):
				return text.split()







def 	_snake_case     (							lowercase__						):
				yield (time.time(), content)
				time.sleep(2						)
				yield (time.time(), content)







def 	_snake_case     (							):
				with Pool(2						) as pool:
								_lowerCamelCase	:     str       =       list(iflatmap_unordered(lowercase__				,       _split_text				,       kwargs_iterable=[{'text': 'hello there'}] * 10						)						)
								assert out.count('hello'						) == 10
								assert out.count('there'						) == 10
								assert len(lowercase__						) == 20

				# check multiprocess from pathos (uses dill for pickling)
				with multiprocess.Pool(2						) as pool:
								_lowerCamelCase	:     Union[str, Any]       =       list(iflatmap_unordered(lowercase__				,       _split_text				,       kwargs_iterable=[{'text': 'hello there'}] * 10						)						)
								assert out.count('hello'						) == 10
								assert out.count('there'						) == 10
								assert len(lowercase__						) == 20

				# check that we get items as fast as possible
				with Pool(2						) as pool:
								_lowerCamelCase	:     int       =       []
								for yield_time, content in iflatmap_unordered(
								    lowercase__				,       _aseconds_generator_of_aitems_with_timing				,       kwargs_iterable=[{'content': 'a'}, {'content': 'b'}]						):
												assert yield_time < time.time() + 0.1, "we should each item directly after it was yielded"
												out.append(lowercase__						)
								assert out.count('a'						) == 2
								assert out.count('b'						) == 2
								assert len(lowercase__						) == 4





"""simple docstring"""






def 	_snake_case     (							lowercase__ = 1				,       lowercase__ = 1000						):
				_lowerCamelCase	:     Optional[int]       =       1
				_lowerCamelCase	:     List[Any]       =       0

				for divide_by_number in range(lowercase__				,       digit + 1						):
								_lowerCamelCase	:     list[int]       =       []
								_lowerCamelCase	:     Dict       =       numerator
								for _ in range(1				,       digit + 1						):
												if now_divide in has_been_divided:
																if longest_list_length < len(lowercase__						):
																				_lowerCamelCase	:     Any       =       len(lowercase__						)
																				_lowerCamelCase	:     Any       =       divide_by_number
												else:
																has_been_divided.append(lowercase__						)
																_lowerCamelCase	:     int       =       now_divide * 10 % divide_by_number

				return the_digit


# Tests
if __name__ == "__main__":
			import doctest

			doctest.testmod()