






"""simple docstring"""

import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


lowercase__          = NewType("""DataClass""", Any)
lowercase__          = NewType("""DataClassType""", Any)

def 		__lowerCamelCase	(  __UpperCamelCase       )						->    Dict:

		"""simple docstring"""







		if isinstance(__UpperCamelCase      ,       __UpperCamelCase       ):
				return v
		if v.lower() in ("yes", "true", "t", "y", "1"):
				return True
		elif v.lower() in ("no", "false", "f", "n", "0"):
				return False
		else:
				raise ArgumentTypeError(
				    f'''Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive).'''       )

def 		__lowerCamelCase	(  __UpperCamelCase       )						->    Callable[[str], Any]:

		"""simple docstring"""







		lowerCAmelCase_   :							Optional[int]									=			{str(__UpperCamelCase       ): choice for choice in choices}
		return lambda __UpperCamelCase       : str_to_choice.get(__UpperCamelCase      ,       __UpperCamelCase       )

def 		__lowerCamelCase	(  *,
    __UpperCamelCase = None      ,       __UpperCamelCase = None      ,       __UpperCamelCase = dataclasses.MISSING      ,       __UpperCamelCase = dataclasses.MISSING      ,       __UpperCamelCase = None      ,       **__UpperCamelCase      ,       )						->    dataclasses.Field:

		"""simple docstring"""







		if metadata is None:
				# Important, don't use as default param in function signature because dict is mutable and shared across function calls
				lowerCAmelCase_   :							Any									=			{}
		if aliases is not None:
				lowerCAmelCase_   :							Union[str, Any]									=			aliases
		if help is not None:
				lowerCAmelCase_   :							int									=			help

		return dataclasses.field(metadata=__UpperCamelCase      ,       default=__UpperCamelCase      ,       default_factory=__UpperCamelCase      ,       **__UpperCamelCase       )



class 		__lowerCamelCase				( A__			):





		'''simple docstring'''






		a_	:				Iterable[DataClassType]





		def __init__(   self							:	Union[str, Any]						,			a_							:	Union[DataClassType, Iterable[DataClassType]]						,			**a_							:	Tuple	):
				# To make the default appear when using --help
				if "formatter_class" not in kwargs:
						lowerCAmelCase_   :							Dict									=			ArgumentDefaultsHelpFormatter
				super().__init__(**a_	)
				if dataclasses.is_dataclass(a_	):
						lowerCAmelCase_   :							Optional[int]									=			[dataclass_types]
				lowerCAmelCase_   :							str									=			list(a_	)
				for dtype in self.dataclass_types:
						self._add_dataclass_arguments(a_	)





		@staticmethod
		def    lowerCamelCase       (   a_							:	ArgumentParser						,			a_							:	dataclasses.Field	):
				lowerCAmelCase_   :							Union[str, Any]									=			f'''--{field.name}'''
				lowerCAmelCase_   :							Any									=			field.metadata.copy()
				# field.metadata is not used at all by Data Classes,
				# it is provided as a third-party extension mechanism.
				if isinstance(field.type						,			a_	):
						raise RuntimeError(
						    "Unresolved type detected, which should have been done with the help of "
						    "`typing.get_type_hints` method by default"	)

				lowerCAmelCase_   :							Any									=			kwargs.pop("aliases"						,			[]	)
				if isinstance(a_						,			a_	):
						lowerCAmelCase_   :							Union[str, Any]									=			[aliases]

				lowerCAmelCase_   :							Optional[int]									=			getattr(field.type						,			"__origin__"						,			field.type	)
				if origin_type is Union or (hasattr(a_						,			"UnionType"	) and isinstance(a_						,			types.UnionType	)):
						if str not in field.type.__args__ and (
						    len(field.type.__args__	) != 2 or type(a_	) not in field.type.__args__
						):
								raise ValueError(
								    "Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because"
								    " the argument parser only supports one type per argument."
								    f''' Problem encountered in field \'{field.name}\'.'''	)
						if type(a_	) not in field.type.__args__:
								# filter `str` in Union
								lowerCAmelCase_   :							List[str]									=			field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
								lowerCAmelCase_   :							Optional[int]									=			getattr(field.type						,			"__origin__"						,			field.type	)
						elif bool not in field.type.__args__:
								# filter `NoneType` in Union (except for `Union[bool, NoneType]`)
								lowerCAmelCase_   :							Dict									=			(
								    field.type.__args__[0] if isinstance(a_						,			field.type.__args__[1]	) else field.type.__args__[1]
								)
								lowerCAmelCase_   :							Tuple									=			getattr(field.type						,			"__origin__"						,			field.type	)

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
				lowerCAmelCase_   :							str									=			{}
				if origin_type is Literal or (isinstance(field.type						,			a_	) and issubclass(field.type						,			a_	)):
						if origin_type is Literal:
								lowerCAmelCase_   :							Any									=			field.type.__args__
						else:
								lowerCAmelCase_   :							Tuple									=			[x.value for x in field.type]

						lowerCAmelCase_   :							Dict									=			make_choice_type_function(kwargs["choices"]	)

						if field.default is not dataclasses.MISSING:
								lowerCAmelCase_   :							Union[str, Any]									=			field.default
						else:
								lowerCAmelCase_   :							Tuple									=			True
				elif field.type is bool or field.type == Optional[bool]:
						# Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
						# We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
						lowerCAmelCase_   :							Tuple									=			copy(a_	)

						# Hack because type=bool in argparse does not behave as we want.
						lowerCAmelCase_   :							List[Any]									=			string_to_bool
						if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
								# Default value is False if we have no default when of type bool.
								lowerCAmelCase_   :							Any									=			False if field.default is dataclasses.MISSING else field.default
								# This is the value that will get picked if we don't include --field_name in any way
								lowerCAmelCase_   :							Optional[Any]									=			default
								# This tells argparse we accept 0 or 1 value after --field_name
								lowerCAmelCase_   :							List[str]									=			"?"
								# This is the value that will get picked if we do --field_name (without value)
								lowerCAmelCase_   :							Optional[int]									=			True
				elif isclass(a_	) and issubclass(a_						,			a_	):
						lowerCAmelCase_   :							Union[str, Any]									=			field.type.__args__[0]
						lowerCAmelCase_   :							Tuple									=			"+"
						if field.default_factory is not dataclasses.MISSING:
								lowerCAmelCase_   :							Dict									=			field.default_factory()
						elif field.default is dataclasses.MISSING:
								lowerCAmelCase_   :							Union[str, Any]									=			True
				else:
						lowerCAmelCase_   :							str									=			field.type
						if field.default is not dataclasses.MISSING:
								lowerCAmelCase_   :							Tuple									=			field.default
						elif field.default_factory is not dataclasses.MISSING:
								lowerCAmelCase_   :							int									=			field.default_factory()
						else:
								lowerCAmelCase_   :							Optional[Any]									=			True
				parser.add_argument(a_						,			*a_						,			**a_	)

				# Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
				# Order is important for arguments with the same destination!
				# We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
				# here and we do not need those changes/additional keys.
				if field.default is True and (field.type is bool or field.type == Optional[bool]):
						lowerCAmelCase_   :							Any									=			False
						parser.add_argument(f'''--no_{field.name}'''						,			action="store_false"						,			dest=field.name						,			**a_	)





		def    lowerCamelCase       (   self							:	Dict						,			a_							:	DataClassType	):
				if hasattr(a_						,			"_argument_group_name"	):
						lowerCAmelCase_   :							Dict									=			self.add_argument_group(dtype._argument_group_name	)
				else:
						lowerCAmelCase_   :							int									=			self

				try:
						lowerCAmelCase_   :							Dict[str, type]									=			get_type_hints(a_	)
				except NameError:
						raise RuntimeError(
						    f'''Type resolution failed for {dtype}. Try declaring the class in global scope or '''
						    "removing line of `from __future__ import annotations` which opts in Postponed "
						    "Evaluation of Annotations (PEP 563)"	)
				except TypeError as ex:
						# Remove this block when we drop Python 3.9 support
						if sys.version_info[:2] < (3, 10) and "unsupported operand type(s) for |" in str(a_	):
								lowerCAmelCase_   :							Any									=			".".join(map(a_						,			sys.version_info[:3]	)	)
								raise RuntimeError(
								    f'''Type resolution failed for {dtype} on Python {python_version}. Try removing '''
								    "line of `from __future__ import annotations` which opts in union types as "
								    "`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To "
								    "support Python versions that lower than 3.10, you need to use "
								    "`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of "
								    "`X | None`."	) from ex
						raise

				for field in dataclasses.fields(a_	):
						if not field.init:
								continue
						lowerCAmelCase_   :							List[str]									=			type_hints[field.name]
						self._parse_dataclass_field(a_						,			a_	)





		def    lowerCamelCase       (   self							:	List[str]						,			a_							:	List[str]=None						,			a_							:	int=False						,			a_							:	Union[str, Any]=True						,			a_							:	List[Any]=None						,			a_							:	List[str]=None						,			):

				if args_file_flag or args_filename or (look_for_args_file and len(sys.argv	)):
						lowerCAmelCase_   :							Optional[int]									=			[]

						if args_filename:
								args_files.append(Path(a_	)	)
						elif look_for_args_file and len(sys.argv	):
								args_files.append(Path(sys.argv[0]	).with_suffix(".args"	)	)

						# args files specified via command line flag should overwrite default args files so we add them last
						if args_file_flag:
								# Create special parser just to extract the args_file_flag values
								lowerCAmelCase_   :							Dict									=			ArgumentParser()
								args_file_parser.add_argument(a_						,			type=a_						,			action="append"	)

								# Use only remaining args for further parsing (remove the args_file_flag)
								lowerCAmelCase_				,	lowerCAmelCase_   :							Optional[Any]									=			args_file_parser.parse_known_args(args=a_	)
								lowerCAmelCase_   :							List[Any]									=			vars(a_	).get(args_file_flag.lstrip("-"	)						,			a_	)

								if cmd_args_file_paths:
										args_files.extend([Path(a_	) for p in cmd_args_file_paths]	)

						lowerCAmelCase_   :							List[str]									=			[]
						for args_file in args_files:
								if args_file.exists():
										file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
						lowerCAmelCase_   :							Dict									=			file_args + args if args is not None else file_args + sys.argv[1:]
				lowerCAmelCase_				,	lowerCAmelCase_   :							Tuple									=			self.parse_known_args(args=a_	)
				lowerCAmelCase_   :							List[str]									=			[]
				for dtype in self.dataclass_types:
						lowerCAmelCase_   :							int									=			{f.name for f in dataclasses.fields(a_	) if f.init}
						lowerCAmelCase_   :							Union[str, Any]									=			{k: v for k, v in vars(a_	).items() if k in keys}
						for k in keys:
								delattr(a_						,			a_	)
						lowerCAmelCase_   :							int									=			dtype(**a_	)
						outputs.append(a_	)
				if len(namespace.__dict__	) > 0:
						# additional namespace.
						outputs.append(a_	)
				if return_remaining_strings:
						return (*outputs, remaining_args)
				else:
						if remaining_args:
								raise ValueError(f'''Some specified arguments are not used by the HfArgumentParser: {remaining_args}'''	)

						return (*outputs,)





		def    lowerCamelCase       (   self							:	List[str]						,			a_							:	Dict[str, Any]						,			a_							:	bool = False	):
				lowerCAmelCase_   :							List[str]									=			set(args.keys()	)
				lowerCAmelCase_   :							int									=			[]
				for dtype in self.dataclass_types:
						lowerCAmelCase_   :							List[Any]									=			{f.name for f in dataclasses.fields(a_	) if f.init}
						lowerCAmelCase_   :							Tuple									=			{k: v for k, v in args.items() if k in keys}
						unused_keys.difference_update(inputs.keys()	)
						lowerCAmelCase_   :							Any									=			dtype(**a_	)
						outputs.append(a_	)
				if not allow_extra_keys and unused_keys:
						raise ValueError(f'''Some keys are not used by the HfArgumentParser: {sorted(a_	)}'''	)
				return tuple(a_	)





		def    lowerCamelCase       (   self							:	Any						,			a_							:	str						,			a_							:	bool = False	):
				with open(Path(a_	)						,			encoding="utf-8"	) as open_json_file:
						lowerCAmelCase_   :							Union[str, Any]									=			json.loads(open_json_file.read()	)
				lowerCAmelCase_   :							Optional[Any]									=			self.parse_dict(a_						,			allow_extra_keys=a_	)
				return tuple(a_	)





		def    lowerCamelCase       (   self							:	Optional[int]						,			a_							:	str						,			a_							:	bool = False	):
				lowerCAmelCase_   :							Union[str, Any]									=			self.parse_dict(yaml.safe_load(Path(a_	).read_text()	)						,			allow_extra_keys=a_	)
				return tuple(a_	)








"""simple docstring"""

import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding


class 		__lowerCamelCase				( A__			):





		'''simple docstring'''






		a_	:				str            =							["""image_processor""", """tokenizer"""]
		a_	:				List[str]            =							"""ViTImageProcessor"""
		a_	:				List[str]            =							("""CLIPTokenizer""", """CLIPTokenizerFast""")





		def __init__(   self							:	List[str]						,			a_							:	str=None						,			a_							:	Dict=None						,			**a_							:	List[Any]	):
				lowerCAmelCase_   :							int									=			None
				if "feature_extractor" in kwargs:
						warnings.warn(
						    "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
						    " instead."						,			a_						,			)
						lowerCAmelCase_   :							Union[str, Any]									=			kwargs.pop("feature_extractor"	)

				lowerCAmelCase_   :							Dict									=			image_processor if image_processor is not None else feature_extractor
				if image_processor is None:
						raise ValueError("You need to specify an `image_processor`."	)
				if tokenizer is None:
						raise ValueError("You need to specify a `tokenizer`."	)

				super().__init__(a_						,			a_	)





		def __call__(   self							:	Union[str, Any]						,			a_							:	Any=None						,			a_							:	Dict=None						,			a_							:	List[str]=None						,			a_							:	str=None						,			**a_							:	Any	):
				if text is None and visual_prompt is None and images is None:
						raise ValueError("You have to specify either text, visual prompt or images."	)

				if text is not None and visual_prompt is not None:
						raise ValueError("You have to specify exactly one type of prompt. Either text or visual prompt."	)

				if text is not None:
						lowerCAmelCase_   :							Optional[Any]									=			self.tokenizer(a_						,			return_tensors=a_						,			**a_	)

				if visual_prompt is not None:
						lowerCAmelCase_   :							Optional[Any]									=			self.image_processor(a_						,			return_tensors=a_						,			**a_	)

				if images is not None:
						lowerCAmelCase_   :							List[str]									=			self.image_processor(a_						,			return_tensors=a_						,			**a_	)

				if visual_prompt is not None and images is not None:
						lowerCAmelCase_   :							Union[str, Any]									=			{
						    "pixel_values": image_features.pixel_values,
						    "conditional_pixel_values": prompt_features.pixel_values,
						}
						return encoding
				elif text is not None and images is not None:
						lowerCAmelCase_   :							Optional[int]									=			image_features.pixel_values
						return encoding
				elif text is not None:
						return encoding
				elif visual_prompt is not None:
						lowerCAmelCase_   :							Dict									=			{
						    "conditional_pixel_values": prompt_features.pixel_values,
						}
						return encoding
				else:
						return BatchEncoding(data=dict(**a_	)						,			tensor_type=a_	)





		def    lowerCamelCase       (   self							:	Optional[int]						,			*a_							:	Optional[Any]						,			**a_							:	List[str]	):
				return self.tokenizer.batch_decode(*a_						,			**a_	)





		def    lowerCamelCase       (   self							:	Optional[Any]						,			*a_							:	Tuple						,			**a_							:	Tuple	):
				return self.tokenizer.decode(*a_						,			**a_	)





		@property
		def    lowerCamelCase       (   self							:	List[Any]	):
				warnings.warn(
				    "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."						,			a_						,			)
				return self.image_processor_class





		@property
		def    lowerCamelCase       (   self							:	Dict	):
				warnings.warn(
				    "`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."						,			a_						,			)
				return self.image_processor
