


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 : Tuple 			=				"http://www.mocksite.com/file1.txt"
__UpperCAmelCase : Tuple 			=				"\"text\": [\"foo\", \"foo\"]"
__UpperCAmelCase : Optional[Any] 			=				"6d8ce9aa78a471c7477201efbeabd3bb01ac2e7d100a6dc024ba1608361f90a8"



class    UpperCAmelCase_	:
       '''simple docstring'''
       __UpperCamelCase      :     str							=					200
       __UpperCamelCase      :     Optional[int]							=					{"Content-Length": "100"}
       __UpperCamelCase      :     Dict							=					{}






       def  _lowercase   (     self ,					**__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return [bytes(__SCREAMING_SNAKE_CASE ,					'''utf-8'''						)]




def      a	(							*SCREAMING_SNAKE_CASE_      :		Any							,			**SCREAMING_SNAKE_CASE_      :		Optional[Any]       ):






       """simple docstring"""





       return MockResponse()


@pytest.mark.parametrize('''urls_type'''							,			[str, list, dict]       )
def      a	(							SCREAMING_SNAKE_CASE_      :		Optional[Any]							,			SCREAMING_SNAKE_CASE_      :		Union[str, Any]							,			SCREAMING_SNAKE_CASE_      :		Union[str, Any]       ):






       """simple docstring"""





       import requests

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

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


@pytest.mark.parametrize('''paths_type'''							,			[str, list, dict]       )
def      a	(							SCREAMING_SNAKE_CASE_      :		Any							,			SCREAMING_SNAKE_CASE_      :		str							,			SCREAMING_SNAKE_CASE_      :		Dict       ):






       """simple docstring"""





       UpperCamelCase    :	Any   	=		str(SCREAMING_SNAKE_CASE_       )
       if issubclass(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       ):
              UpperCamelCase    :	List[Any]   	=		filename
       elif issubclass(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       ):
              UpperCamelCase    :	Optional[Any]   	=		[filename]
       elif issubclass(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       ):
              UpperCamelCase    :	Union[str, Any]   	=		{'''train''': filename}
       UpperCamelCase    :	Union[str, Any]   	=		'''dummy'''
       UpperCamelCase    :	int   	=		xz_file.parent
       UpperCamelCase    :	Optional[Any]   	=		'''extracted'''
       UpperCamelCase    :	Dict   	=		DownloadConfig(
           cache_dir=SCREAMING_SNAKE_CASE_							,			use_etag=SCREAMING_SNAKE_CASE_							,			)
       UpperCamelCase    :	Optional[Any]   	=		DownloadManager(dataset_name=SCREAMING_SNAKE_CASE_							,			download_config=SCREAMING_SNAKE_CASE_       )
       UpperCamelCase    :	Dict   	=		dl_manager.extract(SCREAMING_SNAKE_CASE_       )
       UpperCamelCase    :	List[Any]   	=		paths
       for extracted_paths in [extracted_paths]:
              if isinstance(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       ):
                     UpperCamelCase    :	Tuple   	=		[extracted_paths]
                     UpperCamelCase    :	Any   	=		[paths]
              elif isinstance(SCREAMING_SNAKE_CASE_							,			SCREAMING_SNAKE_CASE_       ):
                     assert "train" in extracted_paths.keys()
                     UpperCamelCase    :	Tuple   	=		extracted_paths.values()
                     UpperCamelCase    :	List[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]
                     UpperCamelCase    :	Any   	=		Path(SCREAMING_SNAKE_CASE_       )
                     UpperCamelCase    :	List[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()
                     UpperCamelCase    :	Optional[int]   	=		extracted_path.read_text()
                     UpperCamelCase    :	int   	=		text_file.read_text()
                     assert extracted_file_content == expected_file_content


def      a	(							SCREAMING_SNAKE_CASE_      :		Union[str, Any]							,			SCREAMING_SNAKE_CASE_      :		str       ):






       """simple docstring"""





       assert path.endswith('''.jsonl'''       )
       for num_items, line in enumerate(SCREAMING_SNAKE_CASE_							,			start=1       ):
              UpperCamelCase    :	Optional[int]   	=		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      a	(							SCREAMING_SNAKE_CASE_      :		Tuple							,			SCREAMING_SNAKE_CASE_      :		Tuple       ):






       """simple docstring"""





       UpperCamelCase    :	Any   	=		request.getfixturevalue(SCREAMING_SNAKE_CASE_       )
       UpperCamelCase    :	int   	=		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      a	(							SCREAMING_SNAKE_CASE_      :		List[Any]							,			SCREAMING_SNAKE_CASE_      :		Tuple       ):






       """simple docstring"""





       UpperCamelCase    :	Any   	=		request.getfixturevalue(SCREAMING_SNAKE_CASE_       )
       UpperCamelCase    :	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      a	(							SCREAMING_SNAKE_CASE_      :		Optional[int]       ):






       """simple docstring"""





       UpperCamelCase    :	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





import copy
from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


__UpperCAmelCase : Optional[Any] 			=				logging.get_logger(__name__)

__UpperCAmelCase : List[str] 			=				{
    "microsoft/conditional-detr-resnet-50": (
        "https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"
    ),
}



class    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     Optional[int]							=					"conditional_detr"
       __UpperCamelCase      :     Optional[Any]							=					["past_key_values"]
       __UpperCamelCase      :     Union[str, Any]							=					{
           "hidden_size": "d_model",
           "num_attention_heads": "encoder_attention_heads",
       }






       def __init__(     self ,					__SCREAMING_SNAKE_CASE=True ,					__SCREAMING_SNAKE_CASE=None ,					__SCREAMING_SNAKE_CASE=3 ,					__SCREAMING_SNAKE_CASE=300 ,					__SCREAMING_SNAKE_CASE=6 ,					__SCREAMING_SNAKE_CASE=2_048 ,					__SCREAMING_SNAKE_CASE=8 ,					__SCREAMING_SNAKE_CASE=6 ,					__SCREAMING_SNAKE_CASE=2_048 ,					__SCREAMING_SNAKE_CASE=8 ,					__SCREAMING_SNAKE_CASE=0.0 ,					__SCREAMING_SNAKE_CASE=0.0 ,					__SCREAMING_SNAKE_CASE=True ,					__SCREAMING_SNAKE_CASE="relu" ,					__SCREAMING_SNAKE_CASE=256 ,					__SCREAMING_SNAKE_CASE=0.1 ,					__SCREAMING_SNAKE_CASE=0.0 ,					__SCREAMING_SNAKE_CASE=0.0 ,					__SCREAMING_SNAKE_CASE=0.02 ,					__SCREAMING_SNAKE_CASE=1.0 ,					__SCREAMING_SNAKE_CASE=False ,					__SCREAMING_SNAKE_CASE="sine" ,					__SCREAMING_SNAKE_CASE="resnet50" ,					__SCREAMING_SNAKE_CASE=True ,					__SCREAMING_SNAKE_CASE=False ,					__SCREAMING_SNAKE_CASE=2 ,					__SCREAMING_SNAKE_CASE=5 ,					__SCREAMING_SNAKE_CASE=2 ,					__SCREAMING_SNAKE_CASE=1 ,					__SCREAMING_SNAKE_CASE=1 ,					__SCREAMING_SNAKE_CASE=2 ,					__SCREAMING_SNAKE_CASE=5 ,					__SCREAMING_SNAKE_CASE=2 ,					__SCREAMING_SNAKE_CASE=0.25 ,					**__SCREAMING_SNAKE_CASE ,					):




              """simple docstring"""




              if backbone_config is not None and use_timm_backbone:
                     raise ValueError('''You can\'t specify both `backbone_config` and `use_timm_backbone`.'''						)

              if not use_timm_backbone:
                     if backbone_config is None:
                            logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''						)
                            UpperCamelCase    :	str   	=		CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']						)
                     elif isinstance(__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE						):
                            UpperCamelCase    :	Tuple   	=		backbone_config.get('''model_type'''						)
                            UpperCamelCase    :	Optional[Any]   	=		CONFIG_MAPPING[backbone_model_type]
                            UpperCamelCase    :	Any   	=		config_class.from_dict(__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	List[str]   	=		use_timm_backbone
              UpperCamelCase    :	int   	=		backbone_config
              UpperCamelCase    :	Any   	=		num_channels
              UpperCamelCase    :	Optional[Any]   	=		num_queries
              UpperCamelCase    :	Tuple   	=		d_model
              UpperCamelCase    :	Optional[Any]   	=		encoder_ffn_dim
              UpperCamelCase    :	Optional[int]   	=		encoder_layers
              UpperCamelCase    :	Union[str, Any]   	=		encoder_attention_heads
              UpperCamelCase    :	Optional[Any]   	=		decoder_ffn_dim
              UpperCamelCase    :	Optional[int]   	=		decoder_layers
              UpperCamelCase    :	Optional[Any]   	=		decoder_attention_heads
              UpperCamelCase    :	Any   	=		dropout
              UpperCamelCase    :	List[Any]   	=		attention_dropout
              UpperCamelCase    :	List[Any]   	=		activation_dropout
              UpperCamelCase    :	List[str]   	=		activation_function
              UpperCamelCase    :	Optional[int]   	=		init_std
              UpperCamelCase    :	Optional[Any]   	=		init_xavier_std
              UpperCamelCase    :	Union[str, Any]   	=		encoder_layerdrop
              UpperCamelCase    :	Optional[Any]   	=		decoder_layerdrop
              UpperCamelCase    :	Tuple   	=		encoder_layers
              UpperCamelCase    :	Optional[Any]   	=		auxiliary_loss
              UpperCamelCase    :	Union[str, Any]   	=		position_embedding_type
              UpperCamelCase    :	Optional[int]   	=		backbone
              UpperCamelCase    :	Dict   	=		use_pretrained_backbone
              UpperCamelCase    :	Tuple   	=		dilation
              # Hungarian matcher
              UpperCamelCase    :	Union[str, Any]   	=		class_cost
              UpperCamelCase    :	List[Any]   	=		bbox_cost
              UpperCamelCase    :	Optional[Any]   	=		giou_cost
              # Loss coefficients
              UpperCamelCase    :	Optional[Any]   	=		mask_loss_coefficient
              UpperCamelCase    :	Optional[int]   	=		dice_loss_coefficient
              UpperCamelCase    :	Optional[Any]   	=		cls_loss_coefficient
              UpperCamelCase    :	Optional[int]   	=		bbox_loss_coefficient
              UpperCamelCase    :	Optional[int]   	=		giou_loss_coefficient
              UpperCamelCase    :	Optional[int]   	=		focal_alpha
              super().__init__(is_encoder_decoder=__SCREAMING_SNAKE_CASE ,					**__SCREAMING_SNAKE_CASE						)






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return self.encoder_attention_heads






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return self.d_model






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Union[str, Any]   	=		copy.deepcopy(self.__dict__						)
              if self.backbone_config is not None:
                     UpperCamelCase    :	List[Any]   	=		self.backbone_config.to_dict()
              UpperCamelCase    :	List[Any]   	=		self.__class__.model_type
              return output




class    UpperCAmelCase_	(							_a):
       '''simple docstring'''
       __UpperCamelCase      :     Dict							=					version.parse("1.11")






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return OrderedDict(
                  [
                      ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
                      ('''pixel_mask''', {0: '''batch'''}),
                  ]						)






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return 1e-5






       @property
       def  _lowercase   (     self						):




              """simple docstring"""




              return 12

