from ...configuration_utils import PretrainedConfig
from ...utils import is_detectrona_available, logging


__SCREAMING_SNAKE_CASE						:    Tuple     = logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE						:    List[str]     = {
    'layoutlmv2-base-uncased': 'https://huggingface.co/microsoft/layoutlmv2-base-uncased/resolve/main/config.json',
    'layoutlmv2-large-uncased': 'https://huggingface.co/microsoft/layoutlmv2-large-uncased/resolve/main/config.json',
    # See all LayoutLMv2 models at https://huggingface.co/models?filter=layoutlmv2
}

# soft dependency
if is_detectrona_available():
				import detectrona



class    lowercase_    (     _UpperCamelCase		):
							_lowerCamelCase						=		'layoutlmv2'



							def __init__(						self      ,				lowercase_=30_522      ,				lowercase_=768      ,				lowercase_=12      ,				lowercase_=12      ,				lowercase_=3_072      ,				lowercase_="gelu"      ,				lowercase_=0.1      ,				lowercase_=0.1      ,				lowercase_=512      ,				lowercase_=2      ,				lowercase_=0.02      ,				lowercase_=1e-12      ,				lowercase_=0      ,				lowercase_=1_024      ,				lowercase_=128      ,				lowercase_=32      ,				lowercase_=True      ,				lowercase_=256      ,				lowercase_=64      ,				lowercase_=True      ,				lowercase_=[7, 7, 256]      ,				lowercase_=128      ,				lowercase_=128      ,				lowercase_=True      ,				lowercase_=True      ,				lowercase_=False      ,				lowercase_=None      ,				**lowercase_      ,				):
													super().__init__(
													    vocab_size=a__      ,				hidden_size=a__      ,				num_hidden_layers=a__      ,				num_attention_heads=a__      ,				intermediate_size=a__      ,				hidden_act=a__      ,				hidden_dropout_prob=a__      ,				attention_probs_dropout_prob=a__      ,				max_position_embeddings=a__      ,				type_vocab_size=a__      ,				initializer_range=a__      ,				layer_norm_eps=a__      ,				pad_token_id=a__      ,				**a__      ,				)
													_snake_case						:     Union[str, Any]				=    max_ad_position_embeddings
													_snake_case						:     Optional[Any]				=    max_rel_pos
													_snake_case						:     List[str]				=    rel_pos_bins
													_snake_case						:     Union[str, Any]				=    fast_qkv
													_snake_case						:     List[str]				=    max_rel_ad_pos
													_snake_case						:     Optional[Any]				=    rel_ad_pos_bins
													_snake_case						:     Any				=    convert_sync_batchnorm
													_snake_case						:     Tuple				=    image_feature_pool_shape
													_snake_case						:     Dict				=    coordinate_size
													_snake_case						:     Dict				=    shape_size
													_snake_case						:     Optional[int]				=    has_relative_attention_bias
													_snake_case						:     Union[str, Any]				=    has_spatial_attention_bias
													_snake_case						:     Any				=    has_visual_segment_embedding
													_snake_case						:     str				=    (
													    detectrona_config_args if detectrona_config_args is not None else self.get_default_detectrona_config()
													)



							@classmethod
							def        UpperCamelCase       (						self				):
													return {
													    "MODEL.MASK_ON": True,
													    "MODEL.PIXEL_STD": [57.375, 57.120, 58.395],
													    "MODEL.BACKBONE.NAME": "build_resnet_fpn_backbone",
													    "MODEL.FPN.IN_FEATURES": ["res2", "res3", "res4", "res5"],
													    "MODEL.ANCHOR_GENERATOR.SIZES": [[32], [64], [128], [256], [512]],
													    "MODEL.RPN.IN_FEATURES": ["p2", "p3", "p4", "p5", "p6"],
													    "MODEL.RPN.PRE_NMS_TOPK_TRAIN": 2_000,
													    "MODEL.RPN.PRE_NMS_TOPK_TEST": 1_000,
													    "MODEL.RPN.POST_NMS_TOPK_TRAIN": 1_000,
													    "MODEL.POST_NMS_TOPK_TEST": 1_000,
													    "MODEL.ROI_HEADS.NAME": "StandardROIHeads",
													    "MODEL.ROI_HEADS.NUM_CLASSES": 5,
													    "MODEL.ROI_HEADS.IN_FEATURES": ["p2", "p3", "p4", "p5"],
													    "MODEL.ROI_BOX_HEAD.NAME": "FastRCNNConvFCHead",
													    "MODEL.ROI_BOX_HEAD.NUM_FC": 2,
													    "MODEL.ROI_BOX_HEAD.POOLER_RESOLUTION": 14,
													    "MODEL.ROI_MASK_HEAD.NAME": "MaskRCNNConvUpsampleHead",
													    "MODEL.ROI_MASK_HEAD.NUM_CONV": 4,
													    "MODEL.ROI_MASK_HEAD.POOLER_RESOLUTION": 7,
													    "MODEL.RESNETS.DEPTH": 101,
													    "MODEL.RESNETS.SIZES": [[32], [64], [128], [256], [512]],
													    "MODEL.RESNETS.ASPECT_RATIOS": [[0.5, 1.0, 2.0]],
													    "MODEL.RESNETS.OUT_FEATURES": ["res2", "res3", "res4", "res5"],
													    "MODEL.RESNETS.NUM_GROUPS": 32,
													    "MODEL.RESNETS.WIDTH_PER_GROUP": 8,
													    "MODEL.RESNETS.STRIDE_IN_1X1": False,
													}



							def        UpperCamelCase       (						self				):
													_snake_case						:     str				=    detectrona.config.get_cfg()
													for k, v in self.detectrona_config_args.items():
																			_snake_case						:     Dict				=    k.split("."				)
																			_snake_case						:     str				=    detectrona_config
																			for attribute in attributes[:-1]:
																									_snake_case						:     Tuple				=    getattr(a__      ,				a__				)
																			setattr(a__      ,				attributes[-1]      ,				a__				)

													return detectrona_config



"""simple docstring"""


import importlib
import inspect
from functools import wraps
from typing import TYPE_CHECKING, Optional, Union

from .download.streaming_download_manager import (
    xbasename,
    xdirname,
    xet_parse,
    xexists,
    xgetsize,
    xglob,
    xgzip_open,
    xisdir,
    xisfile,
    xjoin,
    xlistdir,
    xnumpy_load,
    xopen,
    xpandas_read_csv,
    xpandas_read_excel,
    xPath,
    xrelpath,
    xsio_loadmat,
    xsplit,
    xsplitext,
    xwalk,
    xxml_dom_minidom_parse,
)
from .utils.logging import get_logger
from .utils.patching import patch_submodule
from .utils.py_utils import get_imports


a_											=			get_logger(__name__)


if TYPE_CHECKING:
		from .builder import DatasetBuilder






def    a__       ( __lowercase   ,	__lowercase = None      )		->		Optional[Any]:
				_A         =	importlib.import_module(__lowercase      )

				# TODO(QL): always update the module to add subsequent new authentication
				if hasattr(__lowercase   ,	"_patched_for_streaming"      ) and module._patched_for_streaming:
								return

				def wrap_auth(__lowercase      ):
								@wraps(__lowercase      )
								def wrapper(*__lowercase   ,	**__lowercase      ):
												return function(*__lowercase   ,	use_auth_token=__lowercase   ,	**__lowercase      )

								_A         =	"wrap_auth"
								return wrapper

				# open files in a streaming fashion
				patch_submodule(__lowercase   ,	"open"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"os.listdir"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"os.walk"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"glob.glob"   ,	wrap_auth(__lowercase      )      ).start()
				# allow to navigate in remote zip files
				patch_submodule(__lowercase   ,	"os.path.join"   ,	__lowercase      ).start()
				patch_submodule(__lowercase   ,	"os.path.dirname"   ,	__lowercase      ).start()
				patch_submodule(__lowercase   ,	"os.path.basename"   ,	__lowercase      ).start()
				patch_submodule(__lowercase   ,	"os.path.relpath"   ,	__lowercase      ).start()
				patch_submodule(__lowercase   ,	"os.path.split"   ,	__lowercase      ).start()
				patch_submodule(__lowercase   ,	"os.path.splitext"   ,	__lowercase      ).start()
				# allow checks on paths
				patch_submodule(__lowercase   ,	"os.path.exists"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"os.path.isdir"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"os.path.isfile"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"os.path.getsize"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"pathlib.Path"   ,	__lowercase      ).start()
				# file readers
				patch_submodule(__lowercase   ,	"gzip.open"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"numpy.load"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"pandas.read_csv"   ,	wrap_auth(__lowercase      )   ,	attrs=["__version__"]      ).start()
				patch_submodule(__lowercase   ,	"pandas.read_excel"   ,	wrap_auth(__lowercase      )   ,	attrs=["__version__"]      ).start()
				patch_submodule(__lowercase   ,	"scipy.io.loadmat"   ,	wrap_auth(__lowercase      )   ,	attrs=["__version__"]      ).start()
				patch_submodule(__lowercase   ,	"xml.etree.ElementTree.parse"   ,	wrap_auth(__lowercase      )      ).start()
				patch_submodule(__lowercase   ,	"xml.dom.minidom.parse"   ,	wrap_auth(__lowercase      )      ).start()
				_A         =	True






def    a__       ( __lowercase      )		->		str:
				extend_module_for_streaming(builder.__module__   ,	use_auth_token=builder.use_auth_token      )
				# if needed, we also have to extend additional internal imports (like wmt14 -> wmt_utils)
				if not builder.__module__.startswith("datasets."      ):  # check that it's not a packaged builder like csv
								for imports in get_imports(inspect.getfile(builder.__class__      )      ):
												if imports[0] == "internal":
																_A         =	imports[1]
																_A         =	".".join(builder.__module__.split("."      )[:-1] + [internal_import_name]      )
																extend_module_for_streaming(__lowercase   ,	use_auth_token=builder.use_auth_token      )

    # builders can inherit from other builders that might use streaming functionality
    # (for example, ImageFolder and AudioFolder inherit from FolderBuilder which implements examples generation)
    # but these parents builders are not patched automatically as they are not instantiated, so we patch them here
				from .builder import DatasetBuilder

				_A         =	[
				    cls.__module__
				    for cls in type(__lowercase      ).__mro__[1:]  # make sure it's not the same module we've already patched
				    if issubclass(cls   ,	__lowercase      ) and cls.__module__ != DatasetBuilder.__module__
				]  # check it's not a standard builder from datasets.builder
				for module in parent_builder_modules:
								extend_module_for_streaming(__lowercase   ,	use_auth_token=builder.use_auth_token      )