


import json
import os
from pathlib import Path

import pytest

from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename


snake_case							:	Tuple					      =				'''http://www.mocksite.com/file1.txt'''
snake_case							:	Optional[Any]					      =				'''"text": ["foo", "foo"]'''
snake_case							:	List[str]					      =				'''6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8'''







class 	snake_case_       :
					UpperCAmelCase__ :   Union[str, Any]   				=      2_0_0
					UpperCAmelCase__ :   str   				=      {'''Content-Length''': '''100'''}
					UpperCAmelCase__ :   Any   				=      {}
					def 			lowerCamelCase__(				self       :Optional[int]      ,**__snake_case       :List[Any]				) ->   Optional[Any]:
												return [bytes(__snake_case      ,'utf-8'				)]






def 							__lowercase       (			*__lowerCAmelCase							:    Tuple ,   **__lowerCAmelCase							:    Any       ):
							return MockResponse()






@pytest.mark.parametrize('urls_type' ,   [str, list, dict]       )
def 							__lowercase       (			__lowerCAmelCase							:    List[str] ,   __lowerCAmelCase							:    Any ,   __lowerCAmelCase							:    List[Any]       ):
							import requests

							monkeypatch.setattr(__lowerCAmelCase ,   'request' ,   __lowerCAmelCase       )

							a__					=					URL
							if issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					url
							elif issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					[url]
							elif issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					{'train': url}
							a__					=					'dummy'
							a__					=					'downloads'
							a__					=					tmp_path
							a__					=					DownloadConfig(
							    cache_dir=os.path.join(__lowerCAmelCase ,   __lowerCAmelCase       ) ,   use_etag=__lowerCAmelCase ,   )
							a__					=					DownloadManager(dataset_name=__lowerCAmelCase ,   download_config=__lowerCAmelCase       )
							a__					=					dl_manager.download(__lowerCAmelCase       )
							a__					=					urls
							for downloaded_paths in [downloaded_paths]:
														if isinstance(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					a__					=					[downloaded_paths]
																					a__					=					[urls]
														elif isinstance(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					assert "train" in downloaded_paths.keys()
																					a__					=					downloaded_paths.values()
																					a__					=					urls.values()
														assert downloaded_paths
														for downloaded_path, input_url in zip(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					assert downloaded_path == dl_manager.downloaded_paths[input_url]
																					a__					=					Path(__lowerCAmelCase       )
																					a__					=					downloaded_path.parts
																					assert parts[-1] == HASH
																					assert parts[-2] == cache_subdir
																					assert downloaded_path.exists()
																					a__					=					downloaded_path.read_text()
																					assert content == CONTENT
																					a__					=					downloaded_path.with_suffix('.json'       )
																					assert metadata_downloaded_path.exists()
																					a__					=					json.loads(metadata_downloaded_path.read_text()       )
																					assert metadata_content == {"url": URL, "etag": None}






@pytest.mark.parametrize('paths_type' ,   [str, list, dict]       )
def 							__lowercase       (			__lowerCAmelCase							:    Dict ,   __lowerCAmelCase							:    str ,   __lowerCAmelCase							:    Dict       ):
							a__					=					str(__lowerCAmelCase       )
							if issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					filename
							elif issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					[filename]
							elif issubclass(__lowerCAmelCase ,   __lowerCAmelCase       ):
														a__					=					{'train': filename}
							a__					=					'dummy'
							a__					=					xz_file.parent
							a__					=					'extracted'
							a__					=					DownloadConfig(
							    cache_dir=__lowerCAmelCase ,   use_etag=__lowerCAmelCase ,   )
							a__					=					DownloadManager(dataset_name=__lowerCAmelCase ,   download_config=__lowerCAmelCase       )
							a__					=					dl_manager.extract(__lowerCAmelCase       )
							a__					=					paths
							for extracted_paths in [extracted_paths]:
														if isinstance(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					a__					=					[extracted_paths]
																					a__					=					[paths]
														elif isinstance(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					assert "train" in extracted_paths.keys()
																					a__					=					extracted_paths.values()
																					a__					=					paths.values()
														assert extracted_paths
														for extracted_path, input_path in zip(__lowerCAmelCase ,   __lowerCAmelCase       ):
																					assert extracted_path == dl_manager.extracted_paths[input_path]
																					a__					=					Path(__lowerCAmelCase       )
																					a__					=					extracted_path.parts
																					assert parts[-1] == hash_url_to_filename(__lowerCAmelCase ,   etag=__lowerCAmelCase       )
																					assert parts[-2] == extracted_subdir
																					assert extracted_path.exists()
																					a__					=					extracted_path.read_text()
																					a__					=					text_file.read_text()
																					assert extracted_file_content == expected_file_content






def 							__lowercase       (			__lowerCAmelCase							:    Dict ,   __lowerCAmelCase							:    List[Any]       ):
							assert path.endswith('.jsonl'       )
							for num_items, line in enumerate(__lowerCAmelCase ,   start=1       ):
														a__					=					json.loads(line.decode('utf-8'       )       )
														assert item.keys() == {"col_1", "col_2", "col_3"}
							assert num_items == 4






@pytest.mark.parametrize('archive_jsonl' ,   ['tar_jsonl_path', 'zip_jsonl_path']       )
def 							__lowercase       (			__lowerCAmelCase							:    str ,   __lowerCAmelCase							:    List[str]       ):
							a__					=					request.getfixturevalue(__lowerCAmelCase       )
							a__					=					DownloadManager()
							for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(__lowerCAmelCase       ) ,   start=1       ):
														_test_jsonl(__lowerCAmelCase ,   __lowerCAmelCase       )
							assert num_jsonl == 2






@pytest.mark.parametrize('archive_nested_jsonl' ,   ['tar_nested_jsonl_path', 'zip_nested_jsonl_path']       )
def 							__lowercase       (			__lowerCAmelCase							:    List[str] ,   __lowerCAmelCase							:    Tuple       ):
							a__					=					request.getfixturevalue(__lowerCAmelCase       )
							a__					=					DownloadManager()
							for num_tar, (path, file) in enumerate(dl_manager.iter_archive(__lowerCAmelCase       ) ,   start=1       ):
														for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(__lowerCAmelCase       ) ,   start=1       ):
																					_test_jsonl(__lowerCAmelCase ,   __lowerCAmelCase       )
							assert num_tar == 1
							assert num_jsonl == 2






def 							__lowercase       (			__lowerCAmelCase							:    Any       ):
							a__					=					DownloadManager()
							for num_file, file in enumerate(dl_manager.iter_files(__lowerCAmelCase       ) ,   start=1       ):
														assert os.path.basename(__lowerCAmelCase       ) == ("test.txt" if num_file == 1 else "train.txt")
							assert num_file == 2








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 	snake_case_       (lowerCamelCase_     ,						unittest.TestCase				):
					UpperCAmelCase__ :   int   				=      MvpTokenizer
					UpperCAmelCase__ :   List[Any]   				=      MvpTokenizerFast
					UpperCAmelCase__ :   Optional[int]   				=      True
					UpperCAmelCase__ :   Tuple   				=      filter_roberta_detectors
					def 			lowerCamelCase__(				self       :Optional[Any]				) ->   Union[str, Any]:
												super().setUp()
												a__					=					[
												    'l',
												    'o',
												    'w',
												    'e',
												    'r',
												    's',
												    't',
												    'i',
												    'd',
												    'n',
												    '\u0120',
												    '\u0120l',
												    '\u0120n',
												    '\u0120lo',
												    '\u0120low',
												    'er',
												    '\u0120lowest',
												    '\u0120newer',
												    '\u0120wider',
												    '<unk>',
												]
												a__					=					dict(zip(__snake_case      ,range(len(__snake_case				)				)				)				)
												a__					=					['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
												a__					=					{'unk_token': '<unk>'}

												a__					=					os.path.join(self.tmpdirname      ,VOCAB_FILES_NAMES['vocab_file']				)
												a__					=					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(__snake_case				) + '\n'				)
												with open(self.merges_file      ,'w'      ,encoding='utf-8'				) as fp:
																			fp.write('\n'.join(__snake_case				)				)
					def 			lowerCamelCase__(				self       :Optional[Any]      ,**__snake_case       :Tuple				) ->   int:
												kwargs.update(self.special_tokens_map				)
												return self.tokenizer_class.from_pretrained(self.tmpdirname      ,**__snake_case				)
					def 			lowerCamelCase__(				self       :Optional[Any]      ,**__snake_case       :Dict				) ->   Dict:
												kwargs.update(self.special_tokens_map				)
												return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,**__snake_case				)
					def 			lowerCamelCase__(				self       :Any      ,__snake_case       :Union[str, Any]				) ->   List[Any]:
												return "lower newer", "lower newer"
					@cached_property
					def 			lowerCamelCase__(				self       :Tuple				) ->   Optional[int]:
												return MvpTokenizer.from_pretrained('RUCAIBox/mvp'				)
					@cached_property
					def 			lowerCamelCase__(				self       :Optional[int]				) ->   str:
												return MvpTokenizerFast.from_pretrained('RUCAIBox/mvp'				)
					@require_torch
					def 			lowerCamelCase__(				self       :Optional[int]				) ->   str:
												a__					=					['A long paragraph for summarization.', 'Another paragraph for summarization.']
												a__					=					[0, 2_50, 2_51, 1_78_18, 13, 3_91_86, 19_38, 4, 2]

												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			a__					=					tokenizer(__snake_case      ,max_length=len(__snake_case				)      ,padding=__snake_case      ,return_tensors='pt'				)
																			self.assertIsInstance(__snake_case      ,__snake_case				)

																			self.assertEqual((2, 9)      ,batch.input_ids.shape				)
																			self.assertEqual((2, 9)      ,batch.attention_mask.shape				)
																			a__					=					batch.input_ids.tolist()[0]
																			self.assertListEqual(__snake_case      ,__snake_case				)
																			# Test that special tokens are reset
					@require_torch
					def 			lowerCamelCase__(				self       :Union[str, Any]				) ->   List[Any]:
												a__					=					['A long paragraph for summarization.', 'Another paragraph for summarization.']
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			a__					=					tokenizer(__snake_case      ,padding=__snake_case      ,return_tensors='pt'				)
																			# check if input_ids are returned and no labels
																			self.assertIn('input_ids'      ,__snake_case				)
																			self.assertIn('attention_mask'      ,__snake_case				)
																			self.assertNotIn('labels'      ,__snake_case				)
																			self.assertNotIn('decoder_attention_mask'      ,__snake_case				)
					@require_torch
					def 			lowerCamelCase__(				self       :Any				) ->   int:
												a__					=					[
												    'Summary of the text.',
												    'Another summary.',
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			a__					=					tokenizer(text_target=__snake_case      ,max_length=32      ,padding='max_length'      ,return_tensors='pt'				)
																			self.assertEqual(32      ,targets['input_ids'].shape[1]				)
					@require_torch
					def 			lowerCamelCase__(				self       :int				) ->   Union[str, Any]:
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			a__					=					tokenizer(
																			    ['I am a small frog' * 10_24, 'I am a small frog']      ,padding=__snake_case      ,truncation=__snake_case      ,return_tensors='pt'				)
																			self.assertIsInstance(__snake_case      ,__snake_case				)
																			self.assertEqual(batch.input_ids.shape      ,(2, 10_24)				)
					@require_torch
					def 			lowerCamelCase__(				self       :List[Any]				) ->   Any:
												a__					=					['A long paragraph for summarization.']
												a__					=					[
												    'Summary of the text.',
												]
												for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																			a__					=					tokenizer(__snake_case      ,text_target=__snake_case      ,return_tensors='pt'				)
																			a__					=					inputs['input_ids']
																			a__					=					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 			lowerCamelCase__(				self       :Union[str, Any]				) ->   Tuple:
												pass



					def 			lowerCamelCase__(				self       :Tuple				) ->   Optional[Any]:
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'				):
																										a__					=					self.rust_tokenizer_class.from_pretrained(__snake_case      ,**__snake_case				)
																										a__					=					self.tokenizer_class.from_pretrained(__snake_case      ,**__snake_case				)
																										a__					=					'A, <mask> AllenNLP sentence.'
																										a__					=					tokenizer_r.encode_plus(__snake_case      ,add_special_tokens=__snake_case      ,return_token_type_ids=__snake_case				)
																										a__					=					tokenizer_p.encode_plus(__snake_case      ,add_special_tokens=__snake_case      ,return_token_type_ids=__snake_case				)

																										# 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']				)      ,)

																										a__					=					tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']				)
																										a__					=					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, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)
																										self.assertSequenceEqual(tokens_r['input_ids']      ,[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)

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




