






import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile

from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version


lowerCamelCase : Any						   =       get_logger(__name__)

class 		lowerCAmelCase     :

					'''simple docstring'''

					_A						:			Tuple									=      'dummy_data'
					_A						:			Dict									=      'datasets'
					_A						:			int									=      False



					def __init__(  self				:	List[str]		,     __a				:	str		,     __a				:	str		,     __a				:	Union[Version, str]		,     __a				:	Optional[str] = None		,     __a				:	bool = False		,     __a				:	bool = True		,     __a				:	Optional[List[Callable]] = None		,     )			->  Any:


												"""simple docstring"""

												__lowercase      :							List[Any]				=     0
												__lowercase      :							str				=     dataset_name
												__lowercase      :							Optional[Any]				=     cache_dir
												__lowercase      :							Union[str, Any]				=     use_local_dummy_data
												__lowercase      :							Tuple				=     config
												# download_callbacks take a single url as input
												__lowercase      :							List[Any]				=     download_callbacks or []
												# if False, it doesn't load existing files and it returns the paths of the dummy files relative
												# to the dummy_data zip file root
												__lowercase      :							List[Any]				=     load_existing_dummy_data

												# TODO(PVP, QL) might need to make this more general
												__lowercase      :							str				=     str(__a							)
												# to be downloaded
												__lowercase      :							int				=     None
												__lowercase      :							str				=     None



					@property
					def       lowerCAmelCase				(  self				:	Any							)			->  Union[str, Any]:


												"""simple docstring"""

												if self._dummy_file is None:
																			__lowercase      :							Union[str, Any]				=     self.download_dummy_data()
												return self._dummy_file



					@property
					def       lowerCAmelCase				(  self				:	Tuple							)			->  Dict:


												"""simple docstring"""

												if self.config is not None:
																			# structure is dummy / config_name / version_name
																			return os.path.join("""dummy"""		,     self.config.name		,     self.version_name							)
												# structure is dummy / version_name
												return os.path.join("""dummy"""		,     self.version_name							)



					@property
					def       lowerCAmelCase				(  self				:	List[str]							)			->  Tuple:


												"""simple docstring"""

												return os.path.join(self.dummy_data_folder		,     """dummy_data.zip"""							)



					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  Optional[Any]:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     (
												    self.local_path_to_dummy_data if self.use_local_dummy_data is True else self.github_path_to_dummy_data
												)

												__lowercase      :							int				=     cached_path(
												    __a		,     cache_dir=self.cache_dir		,     extract_compressed_file=__a		,     force_extract=__a							)

												return os.path.join(__a		,     self.dummy_file_name							)



					@property
					def       lowerCAmelCase				(  self				:	int							)			->  str:


												"""simple docstring"""

												return os.path.join(self.datasets_scripts_dir		,     self.dataset_name		,     self.dummy_zip_file							)



					@property
					def       lowerCAmelCase				(  self				:	Any							)			->  Any:


												"""simple docstring"""

												if self._bucket_url is None:
																			__lowercase      :							Optional[int]				=     hf_github_url(self.dataset_name		,     self.dummy_zip_file.replace(os.sep		,     """/"""							)							)
												return self._bucket_url



					@property
					def       lowerCAmelCase				(  self				:	int							)			->  Any:


												"""simple docstring"""

												if os.path.isdir(self.dummy_file							):
																			return self.dummy_file
												# else cut off path to file -> example `xsum`.
												return "/".join(self.dummy_file.replace(os.sep		,     """/"""							).split("""/"""							)[:-1]							)



					def       lowerCAmelCase				(  self				:	Union[str, Any]		,     __a				:	Dict		,     *__a				:	Any							)			->  int:


												"""simple docstring"""

												if self.load_existing_dummy_data:
																			# dummy data is downloaded and tested
																			__lowercase      :							Dict				=     self.dummy_file
												else:
																			# dummy data cannot be downloaded and only the path to dummy file is returned
																			__lowercase      :							str				=     self.dummy_file_name

												# special case when data_url is a dict
												if isinstance(__a		,     __a							):
																			return self.create_dummy_data_dict(__a		,     __a							)
												elif isinstance(__a		,     (list, tuple)							):
																			return self.create_dummy_data_list(__a		,     __a							)
												else:
																			return self.create_dummy_data_single(__a		,     __a							)



					def       lowerCAmelCase				(  self				:	Any		,     __a				:	str		,     *__a				:	Any							)			->  Optional[Any]:


												"""simple docstring"""

												return self.download_and_extract(__a							)



					def       lowerCAmelCase				(  self				:	Tuple		,     __a				:	Union[str, Any]		,     __a				:	Optional[Any]							)			->  Union[str, Any]:


												"""simple docstring"""

												return self.download_and_extract(__a							)



					def       lowerCAmelCase				(  self				:	Dict		,     __a				:	Union[str, Any]		,     *__a				:	Optional[int]		,     **__a				:	Any							)			->  Optional[int]:


												"""simple docstring"""

												return path



					def       lowerCAmelCase				(  self				:	int							)			->  Optional[Any]:


												"""simple docstring"""

												return {}



					def       lowerCAmelCase				(  self				:	str		,     __a				:	Optional[int]		,     __a				:	List[Any]							)			->  Union[str, Any]:


												"""simple docstring"""

												__lowercase      :							int				=     {}
												for key, single_urls in data_url.items():
																			for download_callback in self.download_callbacks:
																										if isinstance(__a		,     __a							):
																																	for single_url in single_urls:
																																								download_callback(__a							)
																										else:
																																	__lowercase      :							Tuple				=     single_urls
																																	download_callback(__a							)
																										# we force the name of each key to be the last file / folder name of the url path
																										# if the url has arguments, we need to encode them with urllib.parse.quote_plus
																			if isinstance(__a		,     __a							):
																										__lowercase      :							Optional[int]				=     [os.path.join(__a		,     urllib.parse.quote_plus(Path(__a							).name							)							) for x in single_urls]
																			else:
																										__lowercase      :							List[Any]				=     single_urls
																										__lowercase      :							Any				=     os.path.join(__a		,     urllib.parse.quote_plus(Path(__a							).name							)							)
																			__lowercase      :							Any				=     value

												# make sure that values are unique
												if all(isinstance(__a		,     __a							) for i in dummy_data_dict.values()							) and len(set(dummy_data_dict.values()							)							) < len(
												    dummy_data_dict.values()							):
																			# append key to value to make its name unique
																			__lowercase      :							Optional[Any]				=     {key: value + key for key, value in dummy_data_dict.items()}

												return dummy_data_dict



					def       lowerCAmelCase				(  self				:	Optional[Any]		,     __a				:	Any		,     __a				:	Union[str, Any]							)			->  str:


												"""simple docstring"""

												__lowercase      :							Union[str, Any]				=     []
												# trick: if there are many shards named like `data.txt-000001-of-00300`, only use the first one
												__lowercase      :							str				=     all(bool(re.findall("""[0-9]{3,}-of-[0-9]{3,}"""		,     __a							)							) for url in data_url							)
												__lowercase      :							Union[str, Any]				=     all(
												    url.startswith("""https://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed"""							) for url in data_url							)
												if data_url and (is_tf_records or is_pubmed_records):
																			__lowercase      :							Optional[int]				=     [data_url[0]] * len(__a							)
												for single_url in data_url:
																			for download_callback in self.download_callbacks:
																										download_callback(__a							)
																			# we force the name of each key to be the last file / folder name of the url path
																			# if the url has arguments, we need to encode them with urllib.parse.quote_plus
																			__lowercase      :							str				=     os.path.join(__a		,     urllib.parse.quote_plus(single_url.split("""/"""							)[-1]							)							)
																			dummy_data_list.append(__a							)
												return dummy_data_list



					def       lowerCAmelCase				(  self				:	str		,     __a				:	Union[str, Any]		,     __a				:	List[Any]							)			->  Optional[Any]:


												"""simple docstring"""

												for download_callback in self.download_callbacks:
																			download_callback(__a							)
												# we force the name of each key to be the last file / folder name of the url path
												# if the url has arguments, we need to encode them with urllib.parse.quote_plus
												__lowercase      :							Optional[int]				=     os.path.join(__a		,     urllib.parse.quote_plus(data_url.split("""/"""							)[-1]							)							)
												if os.path.exists(__a							) or not self.load_existing_dummy_data:
																			return value
												else:
																			# Backward compatibility, maybe deprecate at one point.
																			# For many datasets with single url calls to dl_manager.download_and_extract,
																			# the dummy_data.zip file is actually the zipped downloaded file
																			# while now we expected the dummy_data.zip file to be a directory containing
																			# the downloaded file.
																			return path_to_dummy_data



					def       lowerCAmelCase				(  self				:	int							)			->  List[Any]:


												"""simple docstring"""

												pass



					def       lowerCAmelCase				(  self				:	Union[str, Any]							)			->  Optional[Any]:


												"""simple docstring"""

												pass



					def       lowerCAmelCase				(  self				:	int		,     __a				:	Tuple							)			->  Any:


												"""simple docstring"""

												def _iter_archive_members(__a				:	Union[str, Any]							):
																			# this preserves the order of the members inside the ZIP archive
																			__lowercase      :							List[Any]				=     Path(self.dummy_file							).parent
																			__lowercase      :							Optional[Any]				=     path.relative_to(__a							)
																			with ZipFile(self.local_path_to_dummy_data							) as zip_file:
																										__lowercase      :							List[str]				=     zip_file.namelist()
																			for member in members:
																										if member.startswith(relative_path.as_posix()							):
																																	yield dummy_parent_path.joinpath(__a							)

												__lowercase      :							int				=     Path(__a							)
												__lowercase      :							List[str]				=     _iter_archive_members(__a							) if self.use_local_dummy_data else path.rglob("""*"""							)
												for file_path in file_paths:
																			if file_path.is_file() and not file_path.name.startswith((""".""", """__""")							):
																										yield file_path.relative_to(__a							).as_posix(), file_path.open("""rb"""							)



					def       lowerCAmelCase				(  self				:	Optional[int]		,     __a				:	Union[str, Any]							)			->  Optional[int]:


												"""simple docstring"""

												if not isinstance(__a		,     __a							):
																			__lowercase      :							List[str]				=     [paths]
												for path in paths:
																			if os.path.isfile(__a							):
																										if os.path.basename(__a							).startswith((""".""", """__""")							):
																																	return
																										yield path
																			else:
																										for dirpath, dirnames, filenames in os.walk(__a							):
																																	if os.path.basename(__a							).startswith((""".""", """__""")							):
																																								continue
																																	dirnames.sort()
																																	for filename in sorted(__a							):
																																								if filename.startswith((""".""", """__""")							):
																																															continue
																																								yield os.path.join(__a		,     __a							)







from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging


if TYPE_CHECKING:
	from ...processing_utils import ProcessorMixin
	from ...utils import TensorType


lowerCamelCase : Optional[int]						   =       logging.get_logger(__name__)

lowerCamelCase : Tuple						   =       {
    '''microsoft/layoutlmv3-base''': '''https://huggingface.co/microsoft/layoutlmv3-base/resolve/main/config.json''',
}

class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					_A						:			int									=      '''layoutlmv3'''



					def __init__(  self				:	Dict		,     __a				:	List[str]=50265		,     __a				:	str=768		,     __a				:	List[Any]=12		,     __a				:	List[Any]=12		,     __a				:	List[str]=3072		,     __a				:	Optional[Any]="gelu"		,     __a				:	Optional[int]=0.1		,     __a				:	List[Any]=0.1		,     __a				:	Tuple=512		,     __a				:	int=2		,     __a				:	Any=0.02		,     __a				:	Union[str, Any]=1E-5		,     __a				:	List[str]=1		,     __a				:	List[Any]=0		,     __a				:	int=2		,     __a				:	str=1024		,     __a				:	str=128		,     __a				:	List[Any]=128		,     __a				:	Tuple=True		,     __a				:	Optional[int]=32		,     __a				:	Any=128		,     __a				:	List[Any]=64		,     __a				:	Tuple=256		,     __a				:	str=True		,     __a				:	int=True		,     __a				:	Optional[Any]=True		,     __a				:	Any=224		,     __a				:	str=3		,     __a				:	List[str]=16		,     __a				:	Union[str, Any]=None		,     **__a				:	List[Any]		,     )			->  List[str]:


												"""simple docstring"""

												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		,     bos_token_id=__a		,     eos_token_id=__a		,     **__a		,     )
												__lowercase      :							int				=     max_ad_position_embeddings
												__lowercase      :							Any				=     coordinate_size
												__lowercase      :							Optional[Any]				=     shape_size
												__lowercase      :							str				=     has_relative_attention_bias
												__lowercase      :							int				=     rel_pos_bins
												__lowercase      :							Union[str, Any]				=     max_rel_pos
												__lowercase      :							str				=     has_spatial_attention_bias
												__lowercase      :							str				=     rel_ad_pos_bins
												__lowercase      :							List[Any]				=     max_rel_ad_pos
												__lowercase      :							Tuple				=     text_embed
												__lowercase      :							int				=     visual_embed
												__lowercase      :							Tuple				=     input_size
												__lowercase      :							Dict				=     num_channels
												__lowercase      :							str				=     patch_size
												__lowercase      :							Optional[int]				=     classifier_dropout







class 		lowerCAmelCase     ( __a			):

					'''simple docstring'''

					_A						:			str									=      version.parse('''1.12'''			)



					@property
					def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  Mapping[str, Mapping[int, str]]:


												"""simple docstring"""

												if self.task in ["question-answering", "sequence-classification"]:
																			return OrderedDict(
																			    [
																			        ("""input_ids""", {0: """batch""", 1: """sequence"""}),
																			        ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
																			        ("""bbox""", {0: """batch""", 1: """sequence"""}),
																			        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
																			    ]							)
												else:
																			return OrderedDict(
																			    [
																			        ("""input_ids""", {0: """batch""", 1: """sequence"""}),
																			        ("""bbox""", {0: """batch""", 1: """sequence"""}),
																			        ("""attention_mask""", {0: """batch""", 1: """sequence"""}),
																			        ("""pixel_values""", {0: """batch""", 1: """num_channels"""}),
																			    ]							)



					@property
					def       lowerCAmelCase				(  self				:	Union[str, Any]							)			->  float:


												"""simple docstring"""

												return 1E-5



					@property
					def       lowerCAmelCase				(  self				:	str							)			->  int:


												"""simple docstring"""

												return 12



					def       lowerCAmelCase				(  self				:	List[Any]		,     __a				:	"ProcessorMixin"		,     __a				:	int = -1		,     __a				:	int = -1		,     __a				:	bool = False		,     __a				:	Optional["TensorType"] = None		,     __a				:	int = 3		,     __a				:	int = 40		,     __a				:	int = 40		,     )			->  Mapping[str, Any]:


												"""simple docstring"""

												setattr(processor.image_processor		,     """apply_ocr"""		,     __a							)

												# If dynamic axis (-1) we forward with a fixed dimension of 2 samples to avoid optimizations made by ONNX
												__lowercase      :							Tuple				=     compute_effective_axis_dimension(
												    __a		,     fixed_dimension=OnnxConfig.default_fixed_batch		,     num_token_to_add=0							)
												# If dynamic axis (-1) we forward with a fixed dimension of 8 tokens to avoid optimizations made by ONNX
												__lowercase      :							Tuple				=     processor.tokenizer.num_special_tokens_to_add(__a							)
												__lowercase      :							Tuple				=     compute_effective_axis_dimension(
												    __a		,     fixed_dimension=OnnxConfig.default_fixed_sequence		,     num_token_to_add=__a							)
												# Generate dummy inputs according to compute batch and sequence
												__lowercase      :							Union[str, Any]				=     [[""" """.join([processor.tokenizer.unk_token]							) * seq_length]] * batch_size

												# Generate dummy bounding boxes
												__lowercase      :							Tuple				=     [[[48, 84, 73, 128]]] * batch_size

												# If dynamic axis (-1) we forward with a fixed dimension of 2 samples to avoid optimizations made by ONNX
												# batch_size = compute_effective_axis_dimension(batch_size, fixed_dimension=OnnxConfig.default_fixed_batch)
												__lowercase      :							Tuple				=     self._generate_dummy_images(__a		,     __a		,     __a		,     __a							)

												__lowercase      :							int				=     dict(
												    processor(
												        __a		,     text=__a		,     boxes=__a		,     return_tensors=__a		,     )							)

												return inputs