


# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import ast
import difflib
from collections.abc import Mapping
from typing import Any, Callable, Dict

class     __snake_case							(      _UpperCAmelCase):
					pass







def 							UpperCamelCase_  (				__snake_case			:						str	,			__snake_case			:						Dict[str, Callable]	,			__snake_case			:						Tuple=None	,			__snake_case			:						int=False     )->      Optional[int]:




						'''simple docstring'''
						try:
												__magic_name__ 		=			ast.parse(__snake_case     )
						except SyntaxError as e:
												print('The code generated by the agent is not valid.\n'	,			__snake_case     )
												return
						if state is None:
												__magic_name__ 		=			{}
						__magic_name__ 		=			None
						for idx, node in enumerate(expression.body     ):
												try:
																		__magic_name__ 		=			evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     )
												except InterpretorError as e:
																		__magic_name__ 		=			F'''Evaluation of the code stopped at line {idx} before the end because of the following error'''
																		if chat_mode:
																								msg += (
																								    F'''. Copy paste the following error message and send it back to the agent:\nI get an error: \'{e}\''''
																								)
																		else:
																								msg += F''':\n{e}'''
																		print(__snake_case     )
																		break
												if line_result is not None:
																		__magic_name__ 		=			line_result

						return result
def 							UpperCamelCase_  (				__snake_case			:						ast.AST	,			__snake_case			:						Dict[str, Any]	,			__snake_case			:						Dict[str, Callable]     )->      List[str]:




						'''simple docstring'''
						if isinstance(__snake_case	,			ast.Assign     ):
												# Assignement -> we evaluate the assignement which should update the state
												# We return the variable assigned as it may be used to determine the final result.
												return evaluate_assign(__snake_case	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.Call     ):
												# Function call -> we return the value of the function call
												return evaluate_call(__snake_case	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.Constant     ):
												# Constant -> just return the value
												return expression.value
						elif isinstance(__snake_case	,			ast.Dict     ):
												# Dict -> evaluate all keys and values
												__magic_name__ 		=			[evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     ) for k in expression.keys]
												__magic_name__ 		=			[evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     ) for v in expression.values]
												return dict(zip(__snake_case	,			__snake_case     )     )
						elif isinstance(__snake_case	,			ast.Expr     ):
												# Expression -> evaluate the content
												return evaluate_ast(expression.value	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.For     ):
												# For loop -> execute the loop
												return evaluate_for(__snake_case	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.FormattedValue     ):
												# Formatted value (part of f-string) -> evaluate the content and return
												return evaluate_ast(expression.value	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.If     ):
												# If -> execute the right branch
												return evaluate_if(__snake_case	,			__snake_case	,			__snake_case     )
						elif hasattr(__snake_case	,			'Index'     ) and isinstance(__snake_case	,			ast.Index     ):
												return evaluate_ast(expression.value	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.JoinedStr     ):
												return "".join([str(evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     )     ) for v in expression.values]     )
						elif isinstance(__snake_case	,			ast.List     ):
												# List -> evaluate all elements
												return [evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     ) for elt in expression.elts]
						elif isinstance(__snake_case	,			ast.Name     ):
												# Name -> pick up the value in the state
												return evaluate_name(__snake_case	,			__snake_case	,			__snake_case     )
						elif isinstance(__snake_case	,			ast.Subscript     ):
												# Subscript -> return the value of the indexing
												return evaluate_subscript(__snake_case	,			__snake_case	,			__snake_case     )
						else:
												# For now we refuse anything else. Let's add things as we need them.
												raise InterpretorError(F'''{expression.__class__.__name__} is not supported.'''     )
def 							UpperCamelCase_  (				__snake_case			:						List[str]	,			__snake_case			:						List[Any]	,			__snake_case			:						Any     )->      List[str]:




						'''simple docstring'''
						__magic_name__ 		=			assign.targets
						__magic_name__ 		=			evaluate_ast(assign.value	,			__snake_case	,			__snake_case     )

						if len(__snake_case     ) == 1:
												__magic_name__ 		=			result
						else:
												if len(__snake_case     ) != len(__snake_case     ):
																		raise InterpretorError(F'''Expected {len(__snake_case     )} values but got {len(__snake_case     )}.'''     )
												for var_name, r in zip(__snake_case	,			__snake_case     ):
																		__magic_name__ 		=			r
						return result
def 							UpperCamelCase_  (				__snake_case			:						int	,			__snake_case			:						Union[str, Any]	,			__snake_case			:						int     )->      Tuple:




						'''simple docstring'''
						if not isinstance(call.func	,			ast.Name     ):
												raise InterpretorError(
												    F'''It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func} of '''
												    F'''type {type(call.func     )}.'''     )
						__magic_name__ 		=			call.func.id
						if func_name not in tools:
												raise InterpretorError(
												    F'''It is not permitted to evaluate other functions than the provided tools (tried to execute {call.func.id}).'''     )

						__magic_name__ 		=			tools[func_name]
						# Todo deal with args
						__magic_name__ 		=			[evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     ) for arg in call.args]
						__magic_name__ 		=			{keyword.arg: evaluate_ast(keyword.value	,			__snake_case	,			__snake_case     ) for keyword in call.keywords}
						return func(*__snake_case	,			**__snake_case     )
def 							UpperCamelCase_  (				__snake_case			:						Optional[int]	,			__snake_case			:						Optional[Any]	,			__snake_case			:						str     )->      List[Any]:




						'''simple docstring'''
						__magic_name__ 		=			evaluate_ast(subscript.slice	,			__snake_case	,			__snake_case     )
						__magic_name__ 		=			evaluate_ast(subscript.value	,			__snake_case	,			__snake_case     )
						if isinstance(__snake_case	,			(list, tuple)     ):
												return value[int(__snake_case     )]
						if index in value:
												return value[index]
						if isinstance(__snake_case	,			__snake_case     ) and isinstance(__snake_case	,			__snake_case     ):
												__magic_name__ 		=			difflib.get_close_matches(__snake_case	,			list(value.keys()     )     )
												if len(__snake_case     ) > 0:
																		return value[close_matches[0]]

						raise InterpretorError(F'''Could not index {value} with \'{index}\'.'''     )
def 							UpperCamelCase_  (				__snake_case			:						List[str]	,			__snake_case			:						Tuple	,			__snake_case			:						Optional[Any]     )->      Any:




						'''simple docstring'''
						if name.id in state:
												return state[name.id]
						__magic_name__ 		=			difflib.get_close_matches(name.id	,			list(state.keys()     )     )
						if len(__snake_case     ) > 0:
												return state[close_matches[0]]
						raise InterpretorError(F'''The variable `{name.id}` is not defined.'''     )
def 							UpperCamelCase_  (				__snake_case			:						Dict	,			__snake_case			:						Union[str, Any]	,			__snake_case			:						Any     )->      Optional[Any]:




						'''simple docstring'''
						if len(condition.ops     ) > 1:
												raise InterpretorError('Cannot evaluate conditions with multiple operators'     )

						__magic_name__ 		=			evaluate_ast(condition.left	,			__snake_case	,			__snake_case     )
						__magic_name__ 		=			condition.ops[0]
						__magic_name__ 		=			evaluate_ast(condition.comparators[0]	,			__snake_case	,			__snake_case     )

						if isinstance(__snake_case	,			ast.Eq     ):
												return left == right
						elif isinstance(__snake_case	,			ast.NotEq     ):
												return left != right
						elif isinstance(__snake_case	,			ast.Lt     ):
												return left < right
						elif isinstance(__snake_case	,			ast.LtE     ):
												return left <= right
						elif isinstance(__snake_case	,			ast.Gt     ):
												return left > right
						elif isinstance(__snake_case	,			ast.GtE     ):
												return left >= right
						elif isinstance(__snake_case	,			ast.Is     ):
												return left is right
						elif isinstance(__snake_case	,			ast.IsNot     ):
												return left is not right
						elif isinstance(__snake_case	,			ast.In     ):
												return left in right
						elif isinstance(__snake_case	,			ast.NotIn     ):
												return left not in right
						else:
												raise InterpretorError(F'''Operator not supported: {comparator}'''     )
def 							UpperCamelCase_  (				__snake_case			:						Any	,			__snake_case			:						Optional[Any]	,			__snake_case			:						str     )->      Any:




						'''simple docstring'''
						__magic_name__ 		=			None
						if evaluate_condition(if_statement.test	,			__snake_case	,			__snake_case     ):
												for line in if_statement.body:
																		__magic_name__ 		=			evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     )
																		if line_result is not None:
																								__magic_name__ 		=			line_result
						else:
												for line in if_statement.orelse:
																		__magic_name__ 		=			evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     )
																		if line_result is not None:
																								__magic_name__ 		=			line_result
						return result




def 							UpperCamelCase_  (				__snake_case			:						Any	,			__snake_case			:						Any	,			__snake_case			:						List[Any]     )->      List[Any]:




						'''simple docstring'''
						__magic_name__ 		=			None
						__magic_name__ 		=			evaluate_ast(for_loop.iter	,			__snake_case	,			__snake_case     )
						for counter in iterator:
												__magic_name__ 		=			counter
												for expression in for_loop.body:
																		__magic_name__ 		=			evaluate_ast(__snake_case	,			__snake_case	,			__snake_case     )
																		if line_result is not None:
																								__magic_name__ 		=			line_result
						return result





import warnings

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

class     __snake_case							(      _UpperCAmelCase):
					SCREAMING_SNAKE_CASE_		:					Union[str, Any] 				= ["image_processor", "tokenizer"]
					SCREAMING_SNAKE_CASE_		:					Tuple 				= "AutoImageProcessor"
					SCREAMING_SNAKE_CASE_		:					Dict 				= "AutoTokenizer"
					def __init__(	self					:	List[str]  ,			_lowerCAmelCase					:	str=None  ,			_lowerCAmelCase					:	Dict=None  ,			**_lowerCAmelCase					:	List[str]     )       ->				Optional[int]:



											'''simple docstring'''





											__magic_name__ 		=			None
											if "feature_extractor" in kwargs:
																	warnings.warn(
																	    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
																	    ' instead.'  ,			_lowerCAmelCase  ,			)
																	__magic_name__ 		=			kwargs.pop('feature_extractor'     )

											__magic_name__ 		=			image_processor if image_processor is not None else feature_extractor
											if image_processor is None:
																	raise ValueError('You have to specify an image_processor.'     )
											if tokenizer is None:
																	raise ValueError('You have to specify a tokenizer.'     )

											super().__init__(_lowerCAmelCase  ,			_lowerCAmelCase     )
											__magic_name__ 		=			self.image_processor
					def __call__(	self					:	str  ,			_lowerCAmelCase					:	Any=None  ,			_lowerCAmelCase					:	int=None  ,			_lowerCAmelCase					:	List[str]=None  ,			**_lowerCAmelCase					:	int     )       ->				int:



											'''simple docstring'''





											if text is None and images is None:
																	raise ValueError('You have to specify either text or images. Both cannot be none.'     )

											if text is not None:
																	__magic_name__ 		=			self.tokenizer(_lowerCAmelCase  ,			return_tensors=_lowerCAmelCase  ,			**_lowerCAmelCase     )

											if images is not None:
																	__magic_name__ 		=			self.image_processor(_lowerCAmelCase  ,			return_tensors=_lowerCAmelCase  ,			**_lowerCAmelCase     )

											if text is not None and images is not None:
																	__magic_name__ 		=			image_features.pixel_values
																	return encoding
											elif text is not None:
																	return encoding
											else:
																	return BatchEncoding(data=dict(**_lowerCAmelCase     )  ,			tensor_type=_lowerCAmelCase     )
					def   a (	self					:	Optional[int]  ,			*_lowerCAmelCase					:	Optional[int]  ,			**_lowerCAmelCase					:	Optional[Any]     )       ->				Optional[int]:



											'''simple docstring'''





											return self.tokenizer.batch_decode(*_lowerCAmelCase  ,			**_lowerCAmelCase     )
					def   a (	self					:	Union[str, Any]  ,			*_lowerCAmelCase					:	str  ,			**_lowerCAmelCase					:	Tuple     )       ->				int:



											'''simple docstring'''





											return self.tokenizer.decode(*_lowerCAmelCase  ,			**_lowerCAmelCase     )
					@property
					def   a (	self					:	List[Any]     )       ->				Tuple:



											'''simple docstring'''





											__magic_name__ 		=			self.tokenizer.model_input_names
											__magic_name__ 		=			self.image_processor.model_input_names
											return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names     )     )
					@property
					def   a (	self					:	Optional[Any]     )       ->				Dict:



											'''simple docstring'''





											warnings.warn(
											    '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'  ,			_lowerCAmelCase  ,			)
											return self.image_processor_class







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



											'''simple docstring'''





											warnings.warn(
											    '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'  ,			_lowerCAmelCase  ,			)
											return self.image_processor

