


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_					(  snake_case					)  ->    List[Any]:  # picklable for multiprocessing
							return x.sum()




def        snake_case_					(  snake_case					)  ->    Union[str, Any]:  # picklable for multiprocessing
							return i + 1





@dataclass
class   __a      :
	__lowercase			:							int
	__lowercase			:							str





class   __a      (   __UpperCamelCase				):
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Tuple:




								'''simple docstring'''
								lowercase__:       Optional[int]        =       {}
								lowercase__:       Optional[int]        =       []
								lowercase__:       Union[str, Any]        =       1
								lowercase__:       List[str]        =       [1, 2]
								lowercase__:       Dict        =       {'a': 1, 'b': 2}
								lowercase__:       Optional[Any]        =       {'a': [1, 2], 'b': [3, 4]}
								lowercase__:       str        =       {'a': {'1': 1}, 'b': 2}
								lowercase__:       int        =       {'a': 1, 'b': 2, 'c': 3, 'd': 4}
								lowercase__:       Optional[Any]        =       {}
								lowercase__:       Optional[int]        =       []
								lowercase__:       Optional[int]        =       2
								lowercase__:       Optional[int]        =       [2, 3]
								lowercase__:       Optional[int]        =       {'a': 2, 'b': 3}
								lowercase__:       Any        =       {'a': [2, 3], 'b': [4, 5]}
								lowercase__:       List[str]        =       {'a': {'1': 2}, 'b': 3}
								lowercase__:       Optional[int]        =       {'a': 2, 'b': 3, 'c': 4, 'd': 5}
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A			)    ,			_A			)

								lowercase__:       Tuple        =       2
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(map_nested(_A    ,			_A    ,			num_proc=_A			)    ,			_A			)

								lowercase__:       Optional[int]        =       {'a': np.eye(2			), 'b': np.zeros(3			), 'c': np.ones(2			)}
								lowercase__:       Dict        =       {'a': 2, 'b': 0, 'c': 2}
								lowercase__:       List[str]        =       {
								    'a': np.eye(2			).astype(_A			),
								    'b': np.zeros(3			).astype(_A			),
								    'c': np.ones(2			).astype(_A			),
								}
								self.assertEqual(map_nested(_A    ,			_A    ,			map_numpy=_A			)    ,			_A			)
								self.assertEqual(
								    {k: v.tolist() for k, v in map_nested(_A    ,			_A    ,			map_numpy=_A			).items()}    ,			{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}    ,			)
								self.assertEqual(map_nested(_A    ,			_A    ,			map_numpy=_A    ,			num_proc=_A			)    ,			_A			)
								self.assertEqual(
								    {k: v.tolist() for k, v in map_nested(_A    ,			_A    ,			map_numpy=_A    ,			num_proc=_A			).items()}    ,			{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}    ,			)
								with self.assertRaises(_A			):  # can't pickle a local lambda
															map_nested(lambda lowerCAmelCase__			: x + 1    ,			_A    ,			num_proc=_A			)
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Union[str, Any]:




								'''simple docstring'''
								lowercase__:       Union[str, Any]        =       {'a': 1, 'b': 2}
								lowercase__:       Tuple        =       {'a': 3, 'b': 4}
								lowercase__:       List[Any]        =       {'a': 5, 'b': 6}
								lowercase__:       Dict        =       sorted([('a', (1, 3, 5)), ('b', (2, 4, 6))]			)
								self.assertEqual(sorted(zip_dict(_A    ,			_A    ,			_A			)			)    ,			_A			)
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    str:




								'''simple docstring'''





								class   __a      :
									__lowercase			:							Optional[int]       					=			"""bar"""





								lowercase__:       Optional[Any]        =       Foo()
								self.assertEqual(foo.my_attr    ,			'bar'			)
								with temporary_assignment(_A    ,			'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_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    Dict:





							with patch('datasets.utils.py_utils._single_map_nested'					) as mock_single_map_nested, patch(
							    'datasets.parallel.parallel.Pool'					) as mock_multiprocessing_pool:
														lowercase__:       int        =       {f'{i}': i for i in range(UpperCAmelCase_					)}
														lowercase__:       str        =       map_nested(lambda snake_case					: x + 10      ,							UpperCAmelCase_      ,							num_proc=UpperCAmelCase_      ,							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   __a      (   __UpperCamelCase				):
	@require_tf
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[int]:




								'''simple docstring'''
								import tensorflow as tf
								from tensorflow.keras import layers

								lowercase__:       Optional[Any]        =       layers.Dense(2			)

								def gen_random_output():
															lowercase__:       int        =       tf.random.uniform((1, 3)			)
															return model(_A			).numpy()

								with temp_seed(42    ,			set_tensorflow=_A			):
															lowercase__:       Tuple        =       gen_random_output()
								with temp_seed(42    ,			set_tensorflow=_A			):
															lowercase__:       Union[str, Any]        =       gen_random_output()
								lowercase__:       str        =       gen_random_output()

								np.testing.assert_equal(_A    ,			_A			)
								self.assertGreater(np.abs(outa - outa			).sum()    ,			0			)
	@require_torch
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




								'''simple docstring'''
								import torch

								def gen_random_output():
															lowercase__:       Optional[Any]        =       torch.nn.Linear(3    ,			2			)
															lowercase__:       Dict        =       torch.rand(1    ,			3			)
															return model(_A			).detach().numpy()

								with temp_seed(42    ,			set_pytorch=_A			):
															lowercase__:       Optional[int]        =       gen_random_output()
								with temp_seed(42    ,			set_pytorch=_A			):
															lowercase__:       Optional[int]        =       gen_random_output()
								lowercase__:       Dict        =       gen_random_output()

								np.testing.assert_equal(_A    ,			_A			)
								self.assertGreater(np.abs(outa - outa			).sum()    ,			0			)
	def 		SCREAMING_SNAKE_CASE__       (       self			) ->    Optional[Any]:




								'''simple docstring'''
								def gen_random_output():
															return np.random.rand(1    ,			3			)

								with temp_seed(42			):
															lowercase__:       Dict        =       gen_random_output()
								with temp_seed(42			):
															lowercase__:       str        =       gen_random_output()
								lowercase__:       Optional[Any]        =       gen_random_output()

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





@pytest.mark.parametrize('input_data'      ,							[{}]					)
def        snake_case_					(  snake_case					)  ->    Optional[Any]:
							lowercase__:       Any        =       NestedDataStructure(UpperCAmelCase_					).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_					(  snake_case      ,							snake_case					)  ->    Dict:
							lowercase__:       List[str]        =       NestedDataStructure(UpperCAmelCase_					).flatten()
							assert output == expected_output




def        snake_case_					(  )  ->    Any:
							lowercase__:       List[Any]        =       A(x=1      ,							y='foobar'					)
							lowercase__:       int        =       {'x': 1, 'y': 'foobar'}
							assert asdict(UpperCAmelCase_					) == expected_output

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

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




def        snake_case_					(  snake_case					)  ->    Tuple:
							return text.split()




def        snake_case_					(  snake_case					)  ->    List[Any]:
							yield (time.time(), content)
							time.sleep(2					)
							yield (time.time(), content)




def        snake_case_					(  )  ->    List[Any]:





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

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

							# check that we get items as fast as possible
							with Pool(2					) as pool:
														lowercase__:       Union[str, Any]        =       []
														for yield_time, content in iflatmap_unordered(
														    UpperCAmelCase_      ,							_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(UpperCAmelCase_					)
														assert out.count('a'					) == 2
														assert out.count('b'					) == 2
														assert len(UpperCAmelCase_					) == 4






def        snake_case_					(  snake_case					)  ->    list[int]:
       lowercase__:       Dict        =       [0 for i in range(len(snake_case					)					)]

       # initialize interval's left pointer and right pointer
       lowercase__      ,						lowercase__:       Union[str, Any]        =       0, 0

       for i in range(1      ,							len(snake_case					)					):
              # case when current index is inside the interval
              if i <= right_pointer:
                     lowercase__:       List[Any]        =       min(right_pointer - i + 1      ,							z_result[i - left_pointer]					)
                     lowercase__:       List[str]        =       min_edge

              while go_next(snake_case      ,							snake_case      ,							snake_case					):
                     z_result[i] += 1

              # if new index's result gives us more right interval,
              # we've to update left_pointer and right_pointer
              if i + z_result[i] - 1 > right_pointer:
                     lowercase__      ,						lowercase__:       List[Any]        =       i, i + z_result[i] - 1

       return z_result




def        snake_case_					(  snake_case      ,							snake_case      ,							snake_case					)  ->    bool:
       return i + z_result[i] < len(snake_case					) and s[z_result[i]] == s[i + z_result[i]]




def        snake_case_					(  snake_case      ,							snake_case					)  ->    int:
       lowercase__:       Tuple        =       0
       # concatenate 'pattern' and 'input_str' and call z_function
       # with concatenated string
       lowercase__:       Any        =       z_function(pattern + input_str					)

       for val in z_result:
              # if value is greater then length of the pattern string
              # that means this index is starting position of substring
              # which is equal to pattern string
              if val >= len(snake_case					):
                     answer += 1

       return answer


if __name__ == "__main__":
 import doctest

 doctest.testmod()


