






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


UpperCamelCase								=		"http://www.mocksite.com/file1.txt"
UpperCamelCase								=		"\"text\": [\"foo\", \"foo\"]"
UpperCamelCase								=		"6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"

class 				lowerCAmelCase_	:
				_UpperCamelCase					:       int							       = 200
				_UpperCamelCase					:       Tuple							       = {"Content-Length": "100"}
				_UpperCamelCase					:       int							       = {}


				def 						__a					(					self ,						**_lowerCAmelCase      ):
											return [bytes(_lowerCAmelCase ,						'utf-8'      )]






def    __magic_name__    (	*SCREAMING_SNAKE_CASE     ,     **SCREAMING_SNAKE_CASE				)     ->    Tuple:
							return MockResponse()






@pytest.mark.parametrize('urls_type'     ,     [str, list, dict]				)
def    __magic_name__    (	SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)     ->    Optional[Any]:
							import requests

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

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






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






def    __magic_name__    (	SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)     ->    int:
							assert path.endswith('.jsonl'				)
							for num_items, line in enumerate(SCREAMING_SNAKE_CASE     ,     start=1				):
														_lowercase							:   List[str] 							=   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    __magic_name__    (	SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)     ->    Any:
							_lowercase							:   str 							=   request.getfixturevalue(SCREAMING_SNAKE_CASE				)
							_lowercase							:   Tuple 							=   DownloadManager()
							for num_jsonl, (path, file) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE				)     ,     start=1				):
														_test_jsonl(SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)
							assert num_jsonl == 2






@pytest.mark.parametrize('archive_nested_jsonl'     ,     ['tar_nested_jsonl_path', 'zip_nested_jsonl_path']				)
def    __magic_name__    (	SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)     ->    Optional[Any]:
							_lowercase							:   Optional[int] 							=   request.getfixturevalue(SCREAMING_SNAKE_CASE				)
							_lowercase							:   Optional[Any] 							=   DownloadManager()
							for num_tar, (path, file) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE				)     ,     start=1				):
														for num_jsonl, (subpath, subfile) in enumerate(dl_manager.iter_archive(SCREAMING_SNAKE_CASE				)     ,     start=1				):
																					_test_jsonl(SCREAMING_SNAKE_CASE     ,     SCREAMING_SNAKE_CASE				)
							assert num_tar == 1
							assert num_jsonl == 2






def    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    Optional[int]:
							_lowercase							:   Dict 							=   DownloadManager()
							for num_file, file in enumerate(dl_manager.iter_files(SCREAMING_SNAKE_CASE				)     ,     start=1				):
														assert os.path.basename(SCREAMING_SNAKE_CASE				) == ("test.txt" if num_file == 1 else "train.txt")
							assert num_file == 2









"""simple docstring"""






import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case				:  str =       logging.get_logger(__name__)

__snake_case				:  Union[str, Any] =       {
    'microsoft/git-base': 'https://huggingface.co/microsoft/git-base/resolve/main/config.json',
}



class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      'git_vision_model'

	def __init__(	self:						Optional[int]			,     _SCREAMING_SNAKE_CASE:						List[Any]=768			,     _SCREAMING_SNAKE_CASE:						Optional[Any]=3072			,     _SCREAMING_SNAKE_CASE:						str=12			,     _SCREAMING_SNAKE_CASE:						Any=12			,     _SCREAMING_SNAKE_CASE:						Dict=3			,     _SCREAMING_SNAKE_CASE:						List[Any]=224			,     _SCREAMING_SNAKE_CASE:						List[str]=16			,     _SCREAMING_SNAKE_CASE:						str="quick_gelu"			,     _SCREAMING_SNAKE_CASE:						Any=1e-5			,     _SCREAMING_SNAKE_CASE:						List[str]=0.0			,     _SCREAMING_SNAKE_CASE:						Dict=0.02			,     **_SCREAMING_SNAKE_CASE:						str			,     )							->			Optional[Any]:

				"""simple docstring"""

				super().__init__(**_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase :    Union[str, Any]				=			hidden_size
				__lowerCAmelCase :    List[str]				=			intermediate_size
				__lowerCAmelCase :    List[str]				=			num_hidden_layers
				__lowerCAmelCase :    Tuple				=			num_attention_heads
				__lowerCAmelCase :    List[Any]				=			num_channels
				__lowerCAmelCase :    Dict				=			patch_size
				__lowerCAmelCase :    Optional[int]				=			image_size
				__lowerCAmelCase :    Optional[Any]				=			initializer_range
				__lowerCAmelCase :    str				=			attention_dropout
				__lowerCAmelCase :    Optional[Any]				=			layer_norm_eps
				__lowerCAmelCase :    Tuple				=			hidden_act







	@classmethod
	def 				_SCREAMING_SNAKE_CASE  (	cls:						Dict			,     _SCREAMING_SNAKE_CASE:						Union[str, os.PathLike]			,     **_SCREAMING_SNAKE_CASE:						Dict)							->			"PretrainedConfig":

				"""simple docstring"""

				cls._set_token_in_kwargs(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase		,      __lowerCAmelCase :    List[Any]				=			cls.get_config_dict(_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)

				# get the vision config dict if we are loading from GITConfig
				if config_dict.get("model_type") == "git":
							__lowerCAmelCase :    str				=			config_dict["vision_config"]

				if "model_type" in config_dict and hasattr(cls			,     "model_type") and config_dict["model_type"] != cls.model_type:
							logger.warning(
							    F"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
							    F"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""")

				return cls.from_dict(_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)






class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      'git'

	def __init__(	self:						Union[str, Any]			,     _SCREAMING_SNAKE_CASE:						Tuple=None			,     _SCREAMING_SNAKE_CASE:						Dict=3_0522			,     _SCREAMING_SNAKE_CASE:						Any=768			,     _SCREAMING_SNAKE_CASE:						str=6			,     _SCREAMING_SNAKE_CASE:						int=12			,     _SCREAMING_SNAKE_CASE:						Dict=3072			,     _SCREAMING_SNAKE_CASE:						Optional[Any]="gelu"			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=0.1			,     _SCREAMING_SNAKE_CASE:						Any=0.1			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=1024			,     _SCREAMING_SNAKE_CASE:						str=0.02			,     _SCREAMING_SNAKE_CASE:						Tuple=1e-12			,     _SCREAMING_SNAKE_CASE:						List[str]=0			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]="absolute"			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=True			,     _SCREAMING_SNAKE_CASE:						Tuple=False			,     _SCREAMING_SNAKE_CASE:						Dict=101			,     _SCREAMING_SNAKE_CASE:						Tuple=102			,     _SCREAMING_SNAKE_CASE:						Any=None			,     **_SCREAMING_SNAKE_CASE:						List[Any]			,     )							->			List[Any]:

				"""simple docstring"""

				super().__init__(bos_token_id=_SCREAMING_SNAKE_CASE			,     eos_token_id=_SCREAMING_SNAKE_CASE			,     pad_token_id=_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE)

				if vision_config is None:
							__lowerCAmelCase :    int				=			{}
							logger.info("vision_config is None. initializing the GitVisionConfig with default values.")

				__lowerCAmelCase :    List[str]				=			GitVisionConfig(**_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase :    List[Any]				=			vocab_size
				__lowerCAmelCase :    int				=			hidden_size
				__lowerCAmelCase :    Dict				=			num_hidden_layers
				__lowerCAmelCase :    Tuple				=			num_attention_heads
				__lowerCAmelCase :    Union[str, Any]				=			hidden_act
				__lowerCAmelCase :    Dict				=			intermediate_size
				__lowerCAmelCase :    List[str]				=			hidden_dropout_prob
				__lowerCAmelCase :    Union[str, Any]				=			attention_probs_dropout_prob
				__lowerCAmelCase :    Union[str, Any]				=			max_position_embeddings
				__lowerCAmelCase :    Optional[int]				=			initializer_range
				__lowerCAmelCase :    str				=			layer_norm_eps
				__lowerCAmelCase :    Optional[Any]				=			position_embedding_type
				__lowerCAmelCase :    str				=			use_cache
				__lowerCAmelCase :    str				=			tie_word_embeddings
				__lowerCAmelCase :    Optional[int]				=			num_image_with_embedding

				__lowerCAmelCase :    Optional[Any]				=			bos_token_id
				__lowerCAmelCase :    Any				=			eos_token_id







	def 				_SCREAMING_SNAKE_CASE  (	self:						Dict)							->			List[str]:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[int]				=			copy.deepcopy(self.__dict__)
				__lowerCAmelCase :    List[Any]				=			self.vision_config.to_dict()
				__lowerCAmelCase :    Tuple				=			self.__class__.model_type
				return output