


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     (  A )		->					Union[str, Any]:  # picklable for multiprocessing
							return x.sum()


def       _snake_case     (  A )		->					str:  # picklable for multiprocessing
							return i + 1




@dataclass
class 	a__       :





							'''simple docstring'''






							lowercase__    :     int
							lowercase__    :     str




class 	a__       (							a__						):





							'''simple docstring'''






							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Optional[int]:
														lowerCAmelCase__      =			{}
														lowerCAmelCase__      =			[]
														lowerCAmelCase__      =			1
														lowerCAmelCase__      =			[1, 2]
														lowerCAmelCase__      =			{'''a''': 1, '''b''': 2}
														lowerCAmelCase__      =			{'''a''': [1, 2], '''b''': [3, 4]}
														lowerCAmelCase__      =			{'''a''': {'''1''': 1}, '''b''': 2}
														lowerCAmelCase__      =			{'''a''': 1, '''b''': 2, '''c''': 3, '''d''': 4}
														lowerCAmelCase__      =			{}
														lowerCAmelCase__      =			[]
														lowerCAmelCase__      =			2
														lowerCAmelCase__      =			[2, 3]
														lowerCAmelCase__      =			{'''a''': 2, '''b''': 3}
														lowerCAmelCase__      =			{'''a''': [2, 3], '''b''': [4, 5]}
														lowerCAmelCase__      =			{'''a''': {'''1''': 2}, '''b''': 3}
														lowerCAmelCase__      =			{'''a''': 2, '''b''': 3, '''c''': 4, '''d''': 5}
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_     )      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			2
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )

														lowerCAmelCase__      =			{'''a''': np.eye(2     ), '''b''': np.zeros(3     ), '''c''': np.ones(2     )}
														lowerCAmelCase__      =			{'''a''': 2, '''b''': 0, '''c''': 2}
														lowerCAmelCase__      =			{
														    '''a''': np.eye(2     ).astype(lowerCamelCase_     ),
														    '''b''': np.zeros(3     ).astype(lowerCamelCase_     ),
														    '''c''': np.ones(2     ).astype(lowerCamelCase_     ),
														}
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					map_numpy=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(
														    {k: v.tolist() for k, v in map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					map_numpy=lowerCamelCase_     ).items()}      ,					{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}      ,					)
														self.assertEqual(map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					map_numpy=lowerCamelCase_      ,					num_proc=lowerCamelCase_     )      ,					lowerCamelCase_     )
														self.assertEqual(
														    {k: v.tolist() for k, v in map_nested(lowerCamelCase_      ,					lowerCamelCase_      ,					map_numpy=lowerCamelCase_      ,					num_proc=lowerCamelCase_     ).items()}      ,					{k: v.tolist() for k, v in expected_map_nested_sna_int.items()}      ,					)
														with self.assertRaises(lowerCamelCase_     ):  # can't pickle a local lambda
																					map_nested(lambda lowerCamelCase_     : x + 1      ,					lowerCamelCase_      ,					num_proc=lowerCamelCase_     )







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Any:
														lowerCAmelCase__      =			{'''a''': 1, '''b''': 2}
														lowerCAmelCase__      =			{'''a''': 3, '''b''': 4}
														lowerCAmelCase__      =			{'''a''': 5, '''b''': 6}
														lowerCAmelCase__      =			sorted([('''a''', (1, 3, 5)), ('''b''', (2, 4, 6))]     )
														self.assertEqual(sorted(zip_dict(lowerCamelCase_      ,					lowerCamelCase_      ,					lowerCamelCase_     )     )      ,					lowerCamelCase_     )







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




														class 	a__       :





																					'''simple docstring'''






																					lowercase__    :     Optional[int]					=   "bar"

														lowerCAmelCase__      =			Foo()
														self.assertEqual(foo.my_attr      ,					'''bar'''     )
														with temporary_assignment(lowerCamelCase_      ,					'''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     (  A				,					A				,					A )		->					Any:
							with patch('''datasets.utils.py_utils._single_map_nested''' ) as mock_single_map_nested, patch(
							    '''datasets.parallel.parallel.Pool''' ) as mock_multiprocessing_pool:
														lowerCAmelCase__      =			{F"""{i}""": i for i in range(A )}
														lowerCAmelCase__      =			map_nested(lambda A : x + 10				,					A				,					num_proc=A				,					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__       (							a__						):





							'''simple docstring'''






							@require_tf
							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							int:
														import tensorflow as tf
														from tensorflow.keras import layers

														lowerCAmelCase__      =			layers.Dense(2     )

														def gen_random_output():
																					lowerCAmelCase__      =			tf.random.uniform((1, 3)     )
																					return model(lowerCamelCase_     ).numpy()

														with temp_seed(42      ,					set_tensorflow=lowerCamelCase_     ):
																					lowerCAmelCase__      =			gen_random_output()
														with temp_seed(42      ,					set_tensorflow=lowerCamelCase_     ):
																					lowerCAmelCase__      =			gen_random_output()
														lowerCAmelCase__      =			gen_random_output()

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







							@require_torch
							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							List[str]:
														import torch

														def gen_random_output():
																					lowerCAmelCase__      =			torch.nn.Linear(3      ,					2     )
																					lowerCAmelCase__      =			torch.rand(1      ,					3     )
																					return model(lowerCamelCase_     ).detach().numpy()

														with temp_seed(42      ,					set_pytorch=lowerCamelCase_     ):
																					lowerCAmelCase__      =			gen_random_output()
														with temp_seed(42      ,					set_pytorch=lowerCamelCase_     ):
																					lowerCAmelCase__      =			gen_random_output()
														lowerCAmelCase__      =			gen_random_output()

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







							def 						__SCREAMING_SNAKE_CASE							(	self     ) ->							Optional[int]:
														def gen_random_output():
																					return np.random.rand(1      ,					3     )

														with temp_seed(42     ):
																					lowerCAmelCase__      =			gen_random_output()
														with temp_seed(42     ):
																					lowerCAmelCase__      =			gen_random_output()
														lowerCAmelCase__      =			gen_random_output()

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


@pytest.mark.parametrize('''input_data'''				,					[{}] )
def       _snake_case     (  A )		->					str:
							lowerCAmelCase__      =			NestedDataStructure(A ).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     (  A				,					A )		->					List[str]:
							lowerCAmelCase__      =			NestedDataStructure(A ).flatten()
							assert output == expected_output


def       _snake_case     (  )		->					Any:
							lowerCAmelCase__      =			A(x=1				,					y='''foobar''' )
							lowerCAmelCase__      =			{'''x''': 1, '''y''': '''foobar'''}
							assert asdict(A ) == expected_output

							lowerCAmelCase__      =			{'''a''': {'''b''': A(x=10				,					y='''foo''' )}, '''c''': [A(x=20				,					y='''bar''' )]}
							lowerCAmelCase__      =			{'''a''': {'''b''': {'''x''': 10, '''y''': '''foo'''}}, '''c''': [{'''x''': 20, '''y''': '''bar'''}]}
							assert asdict(A ) == expected_output

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


def       _snake_case     (  A )		->					Tuple:
							return text.split()


def       _snake_case     (  A )		->					Tuple:
							yield (time.time(), content)
							time.sleep(2 )
							yield (time.time(), content)






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

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

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



'''simple docstring'''






import jax.numpy as jnp

from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig


__UpperCAmelCase					       =							logging.get_logger(__name__)

__UpperCAmelCase					       =							'''T5Config'''


def       _snake_case     (  A				,					A				,					A )		->					jnp.ndarray:
							lowerCAmelCase__      =			jnp.zeros_like(A )
							lowerCAmelCase__      =			shifted_input_ids.at[:, 1:].set(input_ids[:, :-1] )
							lowerCAmelCase__      =			shifted_input_ids.at[:, 0].set(A )

							lowerCAmelCase__      =			jnp.where(shifted_input_ids == -100				,					A				,					A )
							return shifted_input_ids




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     int					=   "mt5"
							lowercase__    :     Dict					=   MTaConfig




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     int					=   "mt5"
							lowercase__    :     Any					=   MTaConfig




class 	a__       (							a__						):





							'''simple docstring'''






							lowercase__    :     Union[str, Any]					=   "mt5"
							lowercase__    :     Tuple					=   MTaConfig