import json
import os
import unittest

from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin, filter_roberta_detectors


@require_tokenizers
class 			lowerCamelCase_  (     UpperCAmelCase_		,			unittest.TestCase				):






    '''simple docstring'''






    a__			:		List[Any]      			=   MvpTokenizer
    a__			:		Union[str, Any]      			=   MvpTokenizerFast
    a__			:		Union[str, Any]      			=   True
    a__			:		Tuple      			=   filter_roberta_detectors







    def     UpperCamelCase__     (			self) ->			Optional[int]:
        super().setUp()
        __UpperCamelCase  :List[str]    						=	[
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''\u0120''',
            '''\u0120l''',
            '''\u0120n''',
            '''\u0120lo''',
            '''\u0120low''',
            '''er''',
            '''\u0120lowest''',
            '''\u0120newer''',
            '''\u0120wider''',
            '''<unk>''',
        ]
        __UpperCamelCase  :Tuple    						=	dict(zip(__lowercase				,				range(len(__lowercase))))
        __UpperCamelCase  :List[Any]    						=	['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
        __UpperCamelCase  :List[str]    						=	{'''unk_token''': '''<unk>'''}

        __UpperCamelCase  :int    						=	os.path.join(self.tmpdirname				,				VOCAB_FILES_NAMES['''vocab_file'''])
        __UpperCamelCase  :str    						=	os.path.join(self.tmpdirname				,				VOCAB_FILES_NAMES['''merges_file'''])
        with open(self.vocab_file				,				'''w'''				,				encoding='''utf-8''') as fp:
            fp.write(json.dumps(__lowercase) + '''\n''')
        with open(self.merges_file				,				'''w'''				,				encoding='''utf-8''') as fp:
            fp.write('''\n'''.join(__lowercase))







    def     UpperCamelCase__     (			self				,				**__lowercase) ->			Optional[Any]:
        kwargs.update(self.special_tokens_map)
        return self.tokenizer_class.from_pretrained(self.tmpdirname				,				**__lowercase)







    def     UpperCamelCase__     (			self				,				**__lowercase) ->			List[Any]:
        kwargs.update(self.special_tokens_map)
        return self.rust_tokenizer_class.from_pretrained(self.tmpdirname				,				**__lowercase)







    def     UpperCamelCase__     (			self				,				__lowercase) ->			Any:
        return "lower newer", "lower newer"







    @cached_property
    def     UpperCamelCase__     (			self) ->			Optional[Any]:
        return MvpTokenizer.from_pretrained('''RUCAIBox/mvp''')







    @cached_property
    def     UpperCamelCase__     (			self) ->			Union[str, Any]:
        return MvpTokenizerFast.from_pretrained('''RUCAIBox/mvp''')







    @require_torch
    def     UpperCamelCase__     (			self) ->			Union[str, Any]:
        __UpperCamelCase  :Tuple    						=	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        __UpperCamelCase  :Optional[int]    						=	[0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __UpperCamelCase  :Union[str, Any]    						=	tokenizer(__lowercase				,				max_length=len(__lowercase)				,				padding=__lowercase				,				return_tensors='''pt''')
            self.assertIsInstance(__lowercase				,				__lowercase)

            self.assertEqual((2, 9)				,				batch.input_ids.shape)
            self.assertEqual((2, 9)				,				batch.attention_mask.shape)
            __UpperCamelCase  :int    						=	batch.input_ids.tolist()[0]
            self.assertListEqual(__lowercase				,				__lowercase)
            # Test that special tokens are reset







    @require_torch
    def     UpperCamelCase__     (			self) ->			Dict:
        __UpperCamelCase  :Dict    						=	['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __UpperCamelCase  :Dict    						=	tokenizer(__lowercase				,				padding=__lowercase				,				return_tensors='''pt''')
            # check if input_ids are returned and no labels
            self.assertIn('''input_ids'''				,				__lowercase)
            self.assertIn('''attention_mask'''				,				__lowercase)
            self.assertNotIn('''labels'''				,				__lowercase)
            self.assertNotIn('''decoder_attention_mask'''				,				__lowercase)







    @require_torch
    def     UpperCamelCase__     (			self) ->			Tuple:
        __UpperCamelCase  :Dict    						=	[
            '''Summary of the text.''',
            '''Another summary.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __UpperCamelCase  :Any    						=	tokenizer(text_target=__lowercase				,				max_length=32				,				padding='''max_length'''				,				return_tensors='''pt''')
            self.assertEqual(32				,				targets['''input_ids'''].shape[1])







    @require_torch
    def     UpperCamelCase__     (			self) ->			List[Any]:
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __UpperCamelCase  :List[Any]    						=	tokenizer(
                ['''I am a small frog''' * 1_024, '''I am a small frog''']				,				padding=__lowercase				,				truncation=__lowercase				,				return_tensors='''pt''')
            self.assertIsInstance(__lowercase				,				__lowercase)
            self.assertEqual(batch.input_ids.shape				,				(2, 1_024))







    @require_torch
    def     UpperCamelCase__     (			self) ->			Tuple:
        __UpperCamelCase  :Optional[Any]    						=	['''A long paragraph for summarization.''']
        __UpperCamelCase  :int    						=	[
            '''Summary of the text.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
            __UpperCamelCase  :Optional[int]    						=	tokenizer(__lowercase				,				text_target=__lowercase				,				return_tensors='''pt''')
            __UpperCamelCase  :List[Any]    						=	inputs['''input_ids''']
            __UpperCamelCase  :Union[str, Any]    						=	inputs['''labels''']
            self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item())
            self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item())
            self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item())
            self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item())







    def     UpperCamelCase__     (			self) ->			Union[str, Any]:
        pass







    def     UpperCamelCase__     (			self) ->			Optional[Any]:
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
            with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""):
                __UpperCamelCase  :str    						=	self.rust_tokenizer_class.from_pretrained(__lowercase				,				**__lowercase)
                __UpperCamelCase  :str    						=	self.tokenizer_class.from_pretrained(__lowercase				,				**__lowercase)
                __UpperCamelCase  :List[str]    						=	'''A, <mask> AllenNLP sentence.'''
                __UpperCamelCase  :int    						=	tokenizer_r.encode_plus(__lowercase				,				add_special_tokens=__lowercase				,				return_token_type_ids=__lowercase)
                __UpperCamelCase  :Union[str, Any]    						=	tokenizer_p.encode_plus(__lowercase				,				add_special_tokens=__lowercase				,				return_token_type_ids=__lowercase)

                # token_type_ids should put 0 everywhere
                self.assertEqual(sum(tokens_r['''token_type_ids'''])				,				sum(tokens_p['''token_type_ids''']))

                # attention_mask should put 1 everywhere, so sum over length should be 1
                self.assertEqual(
                    sum(tokens_r['''attention_mask''']) / len(tokens_r['''attention_mask'''])				,				sum(tokens_p['''attention_mask''']) / len(tokens_p['''attention_mask'''])				,				)

                __UpperCamelCase  :Dict    						=	tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids'''])
                __UpperCamelCase  :List[Any]    						=	tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids'''])

                # Rust correctly handles the space before the mask while python doesnt
                self.assertSequenceEqual(tokens_p['''input_ids''']				,				[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2])
                self.assertSequenceEqual(tokens_r['''input_ids''']				,				[0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2])

                self.assertSequenceEqual(
                    __lowercase				,				['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])
                self.assertSequenceEqual(
                    __lowercase				,				['''<s>''', '''A''', ''',''', '''<mask>''', '''ĠAllen''', '''N''', '''LP''', '''Ġsentence''', '''.''', '''</s>'''])






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 lowerCamelCase						(     SCREAMING_SNAKE_CASE			):  # picklable for multiprocessing
    '''simple docstring'''







    return x.sum()



def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):  # picklable for multiprocessing
    '''simple docstring'''







    return i + 1


@dataclass
class 			lowerCamelCase_  :






    '''simple docstring'''






    a__			:		int
    a__			:		str


class 			lowerCamelCase_  (     UpperCAmelCase_				):






    '''simple docstring'''






    def     UpperCamelCase__     (			self) ->			int:
        __UpperCamelCase  :Dict    						=	{}
        __UpperCamelCase  :int    						=	[]
        __UpperCamelCase  :int    						=	1
        __UpperCamelCase  :int    						=	[1, 2]
        __UpperCamelCase  :Optional[Any]    						=	{'''a''': 1, '''b''': 2}
        __UpperCamelCase  :Dict    						=	{'''a''': [1, 2], '''b''': [3, 4]}
        __UpperCamelCase  :Optional[int]    						=	{'''a''': {'''1''': 1}, '''b''': 2}
        __UpperCamelCase  :Optional[Any]    						=	{'''a''': 1, '''b''': 2, '''c''': 3, '''d''': 4}
        __UpperCamelCase  :str    						=	{}
        __UpperCamelCase  :Any    						=	[]
        __UpperCamelCase  :Optional[Any]    						=	2
        __UpperCamelCase  :Optional[int]    						=	[2, 3]
        __UpperCamelCase  :List[Any]    						=	{'''a''': 2, '''b''': 3}
        __UpperCamelCase  :List[str]    						=	{'''a''': [2, 3], '''b''': [4, 5]}
        __UpperCamelCase  :int    						=	{'''a''': {'''1''': 2}, '''b''': 3}
        __UpperCamelCase  :Union[str, Any]    						=	{'''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)

        __UpperCamelCase  :Optional[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)

        __UpperCamelCase  :Dict    						=	{'''a''': np.eye(2), '''b''': np.zeros(3), '''c''': np.ones(2)}
        __UpperCamelCase  :Optional[Any]    						=	{'''a''': 2, '''b''': 0, '''c''': 2}
        __UpperCamelCase  :Optional[int]    						=	{
            '''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     UpperCamelCase__     (			self) ->			List[Any]:
        __UpperCamelCase  :List[str]    						=	{'''a''': 1, '''b''': 2}
        __UpperCamelCase  :int    						=	{'''a''': 3, '''b''': 4}
        __UpperCamelCase  :List[str]    						=	{'''a''': 5, '''b''': 6}
        __UpperCamelCase  :List[Any]    						=	sorted([('''a''', (1, 3, 5)), ('''b''', (2, 4, 6))])
        self.assertEqual(sorted(zip_dict(__lowercase				,				__lowercase				,				__lowercase))				,				__lowercase)







    def     UpperCamelCase__     (			self) ->			List[Any]:


        class 			lowerCamelCase_  :






            '''simple docstring'''






            a__			:		int      			=   """bar"""
        __UpperCamelCase  :List[str]    						=	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 lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    with patch('''datasets.utils.py_utils._single_map_nested'''			) as mock_single_map_nested, patch(
        '''datasets.parallel.parallel.Pool'''			) as mock_multiprocessing_pool:
        __UpperCamelCase  :Union[str, Any]    						=	{f"""{i}""": i for i in range(SCREAMING_SNAKE_CASE			)}
        __UpperCamelCase  :Dict    						=	map_nested(lambda SCREAMING_SNAKE_CASE			: x + 10						,    SCREAMING_SNAKE_CASE						,    num_proc=SCREAMING_SNAKE_CASE						,    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_  (     UpperCAmelCase_				):






    '''simple docstring'''






    @require_tf
    def     UpperCamelCase__     (			self) ->			Optional[int]:
        import tensorflow as tf
        from tensorflow.keras import layers

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

        def gen_random_output():
            __UpperCamelCase  :Optional[Any]    						=	tf.random.uniform((1, 3))
            return model(__lowercase).numpy()

        with temp_seed(42				,				set_tensorflow=__lowercase):
            __UpperCamelCase  :Tuple    						=	gen_random_output()
        with temp_seed(42				,				set_tensorflow=__lowercase):
            __UpperCamelCase  :int    						=	gen_random_output()
        __UpperCamelCase  :List[str]    						=	gen_random_output()

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







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

        def gen_random_output():
            __UpperCamelCase  :List[Any]    						=	torch.nn.Linear(3				,				2)
            __UpperCamelCase  :Optional[Any]    						=	torch.rand(1				,				3)
            return model(__lowercase).detach().numpy()

        with temp_seed(42				,				set_pytorch=__lowercase):
            __UpperCamelCase  :Union[str, Any]    						=	gen_random_output()
        with temp_seed(42				,				set_pytorch=__lowercase):
            __UpperCamelCase  :List[str]    						=	gen_random_output()
        __UpperCamelCase  :Dict    						=	gen_random_output()

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







    def     UpperCamelCase__     (			self) ->			str:
        def gen_random_output():
            return np.random.rand(1				,				3)

        with temp_seed(42):
            __UpperCamelCase  :List[Any]    						=	gen_random_output()
        with temp_seed(42):
            __UpperCamelCase  :Optional[Any]    						=	gen_random_output()
        __UpperCamelCase  :Optional[Any]    						=	gen_random_output()

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



@pytest.mark.parametrize('''input_data'''						,    [{}]			)
def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :List[str]    						=	NestedDataStructure(SCREAMING_SNAKE_CASE			).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 lowerCamelCase						(     SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    __UpperCamelCase  :Dict    						=	NestedDataStructure(SCREAMING_SNAKE_CASE			).flatten()
    assert output == expected_output



def lowerCamelCase						(     ):
    '''simple docstring'''







    __UpperCamelCase  :Union[str, Any]    						=	A(x=1						,    y='''foobar'''			)
    __UpperCamelCase  :Dict    						=	{'''x''': 1, '''y''': '''foobar'''}
    assert asdict(SCREAMING_SNAKE_CASE			) == expected_output

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

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



def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    return text.split()



def lowerCamelCase						(     SCREAMING_SNAKE_CASE			):
    '''simple docstring'''







    yield (time.time(), content)
    time.sleep(2			)
    yield (time.time(), content)



def lowerCamelCase						(     ):
    '''simple docstring'''







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

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

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





