



"""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


_lowerCAmelCase       :str	=   NewType('DataClass', Any)
_lowerCAmelCase       :Union[str, Any]	=   NewType('DataClassType', Any)





def 					lowerCamelCase_		(UpperCamelCase__						:						Union[str, Any]				):
    if isinstance(A__	,			A__				):
        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__						:						int				):
    _UpperCAmelCase				:    Optional[Any]											=       {str(A__				): choice for choice in choices}
    return lambda UpperCamelCase__				: str_to_choice.get(A__	,			A__				)





def 					lowerCamelCase_		(*,
    UpperCamelCase__						:						Tuple = None	,			UpperCamelCase__						:						Union[str, Any] = None	,			UpperCamelCase__						:						Dict = dataclasses.MISSING	,			UpperCamelCase__						:						List[str] = dataclasses.MISSING	,			UpperCamelCase__						:						Optional[int] = None	,			**UpperCamelCase__						:						Dict	,			):
    if metadata is None:
        # Important, don't use as default param in function signature because dict is mutable and shared across function calls
        _UpperCAmelCase				:    int											=       {}
    if aliases is not None:
        _UpperCAmelCase				:    List[str]											=       aliases
    if help is not None:
        _UpperCAmelCase				:    Optional[int]											=       help

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


class 				_UpperCAmelCase				(					__A ):





     '''simple docstring'''



     a__   							=4_2





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





     @staticmethod
     def 					__lowerCAmelCase      (   A			,      A						)				->   Tuple:
         _UpperCAmelCase				:    Any											=       f'--{field.name}'
         _UpperCAmelCase				:    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			,      lowerCAmelCase_						):
             raise RuntimeError(
                 '''Unresolved type detected, which should have been done with the help of '''
                 '''`typing.get_type_hints` method by default'''						)

         _UpperCAmelCase				:    Optional[Any]											=       kwargs.pop('''aliases'''			,      []						)
         if isinstance(lowerCAmelCase_			,      lowerCAmelCase_						):
             _UpperCAmelCase				:    Any											=       [aliases]

         _UpperCAmelCase				:    Tuple											=       getattr(field.type			,      '''__origin__'''			,      field.type						)
         if origin_type is Union or (hasattr(lowerCAmelCase_			,      '''UnionType'''						) and isinstance(lowerCAmelCase_			,      types.UnionType						)):
             if str not in field.type.__args__ and (
                 len(field.type.__args__						) != 2 or type(lowerCAmelCase_						) 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(lowerCAmelCase_						) not in field.type.__args__:
                 # filter `str` in Union
                 _UpperCAmelCase				:    Optional[Any]											=       field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
                 _UpperCAmelCase				:    int											=       getattr(field.type			,      '''__origin__'''			,      field.type						)
             elif bool not in field.type.__args__:
                 # filter `NoneType` in Union (except for `Union[bool, NoneType]`)
                 _UpperCAmelCase				:    Any											=       (
                     field.type.__args__[0] if isinstance(lowerCAmelCase_			,      field.type.__args__[1]						) else field.type.__args__[1]
                 )
                 _UpperCAmelCase				:    Optional[Any]											=       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)
         _UpperCAmelCase				:    List[Any]											=       {}
         if origin_type is Literal or (isinstance(field.type			,      lowerCAmelCase_						) and issubclass(field.type			,      lowerCAmelCase_						)):
             if origin_type is Literal:
                 _UpperCAmelCase				:    str											=       field.type.__args__
             else:
                 _UpperCAmelCase				:    List[Any]											=       [x.value for x in field.type]

             _UpperCAmelCase				:    Optional[int]											=       make_choice_type_function(kwargs['''choices''']						)

             if field.default is not dataclasses.MISSING:
                 _UpperCAmelCase				:    Dict											=       field.default
             else:
                 _UpperCAmelCase				:    str											=       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
             _UpperCAmelCase				:    Any											=       copy(lowerCAmelCase_						)

             # Hack because type=bool in argparse does not behave as we want.
             _UpperCAmelCase				:    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.
                 _UpperCAmelCase				:    Optional[int]											=       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
                 _UpperCAmelCase				:    int											=       default
                 # This tells argparse we accept 0 or 1 value after --field_name
                 _UpperCAmelCase				:    Union[str, Any]											=       "?"
                 # This is the value that will get picked if we do --field_name (without value)
                 _UpperCAmelCase				:    List[Any]											=       True
         elif isclass(lowerCAmelCase_						) and issubclass(lowerCAmelCase_			,      lowerCAmelCase_						):
             _UpperCAmelCase				:    List[str]											=       field.type.__args__[0]
             _UpperCAmelCase				:    int											=       "+"
             if field.default_factory is not dataclasses.MISSING:
                 _UpperCAmelCase				:    Union[str, Any]											=       field.default_factory()
             elif field.default is dataclasses.MISSING:
                 _UpperCAmelCase				:    List[Any]											=       True
         else:
             _UpperCAmelCase				:    Tuple											=       field.type
             if field.default is not dataclasses.MISSING:
                 _UpperCAmelCase				:    Any											=       field.default
             elif field.default_factory is not dataclasses.MISSING:
                 _UpperCAmelCase				:    str											=       field.default_factory()
             else:
                 _UpperCAmelCase				:    Union[str, Any]											=       True
         parser.add_argument(lowerCAmelCase_			,      *lowerCAmelCase_			,      **lowerCAmelCase_						)

         # 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]):
             _UpperCAmelCase				:    Union[str, Any]											=       False
             parser.add_argument(f'--no_{field.name}'			,      action='''store_false'''			,      dest=field.name			,      **lowerCAmelCase_						)





     def 					__lowerCAmelCase      (   self			,      A						)				->   int:
         if hasattr(lowerCAmelCase_			,      '''_argument_group_name'''						):
             _UpperCAmelCase				:    Union[str, Any]											=       self.add_argument_group(dtype._argument_group_name						)
         else:
             _UpperCAmelCase				:    Tuple											=       self

         try:
             _UpperCAmelCase				:    Dict[str, type]											=       get_type_hints(lowerCAmelCase_						)
         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, 1_0) and "unsupported operand type(s) for |" in str(lowerCAmelCase_						):
                 _UpperCAmelCase				:    Union[str, Any]											=       ".".join(map(lowerCAmelCase_			,      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(lowerCAmelCase_						):
             if not field.init:
                 continue
             _UpperCAmelCase				:    Optional[Any]											=       type_hints[field.name]
             self._parse_dataclass_field(lowerCAmelCase_			,      lowerCAmelCase_						)





     def 					__lowerCAmelCase      (   self			,      A=None			,      A=False			,      A=True			,      A=None			,      A=None			,      )				->   Tuple[DataClass, ...]:

         if args_file_flag or args_filename or (look_for_args_file and len(sys.argv						)):
             _UpperCAmelCase				:    Dict											=       []

             if args_filename:
                 args_files.append(Path(lowerCAmelCase_						)						)
             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
                 _UpperCAmelCase				:    int											=       ArgumentParser()
                 args_file_parser.add_argument(lowerCAmelCase_			,      type=lowerCAmelCase_			,      action='''append'''						)

                 # Use only remaining args for further parsing (remove the args_file_flag)
                 _UpperCAmelCase				:    Tuple											=       args_file_parser.parse_known_args(args=lowerCAmelCase_						)
                 _UpperCAmelCase				:    Tuple											=       vars(lowerCAmelCase_						).get(args_file_flag.lstrip('''-'''						)			,      lowerCAmelCase_						)

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

             _UpperCAmelCase				:    Dict											=       []
             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
             _UpperCAmelCase				:    Union[str, Any]											=       file_args + args if args is not None else file_args + sys.argv[1:]
         _UpperCAmelCase				:    Any											=       self.parse_known_args(args=lowerCAmelCase_						)
         _UpperCAmelCase				:    Union[str, Any]											=       []
         for dtype in self.dataclass_types:
             _UpperCAmelCase				:    Union[str, Any]											=       {f.name for f in dataclasses.fields(lowerCAmelCase_						) if f.init}
             _UpperCAmelCase				:    Optional[int]											=       {k: v for k, v in vars(lowerCAmelCase_						).items() if k in keys}
             for k in keys:
                 delattr(lowerCAmelCase_			,      lowerCAmelCase_						)
             _UpperCAmelCase				:    Tuple											=       dtype(**lowerCAmelCase_						)
             outputs.append(lowerCAmelCase_						)
         if len(namespace.__dict__						) > 0:
             # additional namespace.
             outputs.append(lowerCAmelCase_						)
         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			,      A			,      A = False						)				->   Tuple[DataClass, ...]:
         _UpperCAmelCase				:    Dict											=       set(args.keys()						)
         _UpperCAmelCase				:    Dict											=       []
         for dtype in self.dataclass_types:
             _UpperCAmelCase				:    Dict											=       {f.name for f in dataclasses.fields(lowerCAmelCase_						) if f.init}
             _UpperCAmelCase				:    Dict											=       {k: v for k, v in args.items() if k in keys}
             unused_keys.difference_update(inputs.keys()						)
             _UpperCAmelCase				:    List[str]											=       dtype(**lowerCAmelCase_						)
             outputs.append(lowerCAmelCase_						)
         if not allow_extra_keys and unused_keys:
             raise ValueError(f'Some keys are not used by the HfArgumentParser: {sorted(lowerCAmelCase_						)}'						)
         return tuple(lowerCAmelCase_						)





     def 					__lowerCAmelCase      (   self			,      A			,      A = False						)				->   Tuple[DataClass, ...]:
         with open(Path(lowerCAmelCase_						)			,      encoding='''utf-8'''						) as open_json_file:
             _UpperCAmelCase				:    List[Any]											=       json.loads(open_json_file.read()						)
         _UpperCAmelCase				:    Any											=       self.parse_dict(lowerCAmelCase_			,      allow_extra_keys=lowerCAmelCase_						)
         return tuple(lowerCAmelCase_						)





     def 					__lowerCAmelCase      (   self			,      A			,      A = False						)				->   Tuple[DataClass, ...]:
         _UpperCAmelCase				:    Optional[int]											=       self.parse_dict(yaml.safe_load(Path(lowerCAmelCase_						).read_text()						)			,      allow_extra_keys=lowerCAmelCase_						)
         return tuple(lowerCAmelCase_						)










"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
			from ... import PreTrainedTokenizerBase, TensorType

lowerCamelCase_							      = logging.get_logger(__name__)







class      UpperCamelCase_			(__A	):
	__magic_name__       =							'''vision-encoder-decoder'''
	__magic_name__       =							True





	def __init__( self   :					Union[str, Any]      ,      **lowerCAmelCase_   :					List[Any]		)		->     Union[str, Any]:
				super().__init__(**lowerCAmelCase_		)
				if "encoder" not in kwargs or "decoder" not in kwargs:
							raise ValueError(
							    f"""A configuraton of type {self.model_type} cannot be instantiated because """
							    f"""not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}"""		)

				UpperCAmelCase_	:					str     	=   kwargs.pop("encoder"		)
				UpperCAmelCase_	:					Dict     	=   encoder_config.pop("model_type"		)
				UpperCAmelCase_	:					List[Any]     	=   kwargs.pop("decoder"		)
				UpperCAmelCase_	:					Dict     	=   decoder_config.pop("model_type"		)

				UpperCAmelCase_	:					Union[str, Any]     	=   AutoConfig.for_model(lowerCAmelCase_      ,      **lowerCAmelCase_		)
				UpperCAmelCase_	:					List[str]     	=   AutoConfig.for_model(lowerCAmelCase_      ,      **lowerCAmelCase_		)
				UpperCAmelCase_	:					Tuple     	=   True





	@classmethod
	def 	_SCREAMING_SNAKE_CASE ( cls   :					List[str]      ,      lowerCAmelCase_   :					PretrainedConfig      ,      lowerCAmelCase_   :					PretrainedConfig      ,      **lowerCAmelCase_   :					Dict		)		->     PretrainedConfig:
				logger.info("Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
				UpperCAmelCase_	:					Tuple     	=   True
				UpperCAmelCase_	:					str     	=   True

				return cls(encoder=encoder_config.to_dict()      ,      decoder=decoder_config.to_dict()      ,      **lowerCAmelCase_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Optional[int]		)		->     List[Any]:
				UpperCAmelCase_	:					Union[str, Any]     	=   copy.deepcopy(self.__dict__		)
				UpperCAmelCase_	:					List[str]     	=   self.encoder.to_dict()
				UpperCAmelCase_	:					List[Any]     	=   self.decoder.to_dict()
				UpperCAmelCase_	:					Any     	=   self.__class__.model_type
				return output







class      UpperCamelCase_			(__A	):
	__magic_name__       =							version.parse('''1.11'''	)





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					Union[str, Any]		)		->     Mapping[str, Mapping[int, str]]:
				return OrderedDict(
				    [
				        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
				    ]		)





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     float:
				return 1e-4





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					Any		)		->     Mapping[str, Mapping[int, str]]:
				return OrderedDict({"last_hidden_state": {0: "batch", 1: "encoder_sequence"}}		)







class      UpperCamelCase_			(__A	):





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					Dict		)		->     Mapping[str, Mapping[int, str]]:
				UpperCAmelCase_	:					List[Any]     	=   OrderedDict()
				UpperCAmelCase_	:					int     	=   {0: "batch", 1: "past_decoder_sequence + sequence"}
				UpperCAmelCase_	:					Dict     	=   {0: "batch", 1: "past_decoder_sequence + sequence"}
				UpperCAmelCase_	:					Union[str, Any]     	=   {0: "batch", 1: "encoder_sequence"}

				return common_inputs





	def 	_SCREAMING_SNAKE_CASE ( self   :					List[Any]      ,      lowerCAmelCase_   :					"PreTrainedTokenizerBase"      ,      lowerCAmelCase_   :					int = -1      ,      lowerCAmelCase_   :					int = -1      ,      lowerCAmelCase_   :					bool = False      ,      lowerCAmelCase_   :					Optional["TensorType"] = None      ,      )		->     Mapping[str, Any]:
				import torch

				UpperCAmelCase_	:					Optional[int]     	=   OrderedDict()

				UpperCAmelCase_	:					Any     	=   super().generate_dummy_inputs(
				    lowerCAmelCase_      ,      batch_size=lowerCAmelCase_      ,      seq_length=lowerCAmelCase_      ,      is_pair=lowerCAmelCase_      ,      framework=lowerCAmelCase_		)

				UpperCAmelCase_	,      UpperCAmelCase_	:					Optional[Any]     	=   dummy_input["input_ids"].shape
				UpperCAmelCase_	:					List[str]     	=   (batch, encoder_sequence, self._config.encoder_hidden_size)
				UpperCAmelCase_	:					List[str]     	=   dummy_input.pop("input_ids"		)
				UpperCAmelCase_	:					List[str]     	=   dummy_input.pop("attention_mask"		)
				UpperCAmelCase_	:					List[Any]     	=   torch.zeros(lowerCAmelCase_		)

				return common_inputs







class      UpperCamelCase_			(__A	):





	@property
	def 	_SCREAMING_SNAKE_CASE ( self   :					List[str]		)		->     None:
				pass





	def 	_SCREAMING_SNAKE_CASE ( self   :					Any      ,      lowerCAmelCase_   :					PretrainedConfig		)		->     OnnxConfig:
				return VisionEncoderDecoderEncoderOnnxConfig(lowerCAmelCase_		)





	def 	_SCREAMING_SNAKE_CASE ( self   :					Union[str, Any]      ,      lowerCAmelCase_   :					PretrainedConfig      ,      lowerCAmelCase_   :					PretrainedConfig      ,      lowerCAmelCase_   :					str = "default"		)		->     OnnxConfig:
				UpperCAmelCase_	:					Optional[int]     	=   encoder_config.hidden_size
				return VisionEncoderDecoderDecoderOnnxConfig(lowerCAmelCase_      ,      lowerCAmelCase_		)



