





from abc import ABC, abstractmethod
from typing import List, Optional

class   lowerCAmelCase				(   __UpperCamelCase     ):
 def __init__( self    : Any      )     ->      str:
     # test for the above condition
     self.test()
 def 	A_      ( self    : Optional[int]      )     ->      str:
     lowerCamelCase__       : Tuple   					=						0
     lowerCamelCase__       : Tuple   					=						False
     while not completed:
         if counter == 1:
             self.reset()
         lowerCamelCase__       : Optional[int]   					=						self.advance()
         if not self.does_advance(UpperCAmelCase      ):
             raise Exception(
                 'Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true.'      )

         lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : Union[str, Any]   					=						self.update(UpperCAmelCase      )
         counter += 1

         if counter > 10000:
             raise Exception('update() does not fulfill the constraint.'      )

     if self.remaining() != 0:
         raise Exception('Custom Constraint is not defined correctly.'      )
 @abstractmethod
 def 	A_      ( self    : Union[str, Any]      )     ->      int:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )
 @abstractmethod
 def 	A_      ( self    : List[str]     ,	UpperCAmelCase    : int      )     ->      Optional[int]:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )
 @abstractmethod
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : int      )     ->      List[str]:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )
 @abstractmethod
 def 	A_      ( self    : Optional[Any]      )     ->      List[str]:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )
 @abstractmethod
 def 	A_      ( self    : Optional[int]      )     ->      List[str]:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )







 @abstractmethod
 def 	A_      ( self    : List[Any]     ,	UpperCAmelCase    : List[str]=False      )     ->      int:
     raise NotImplementedError(
         F"""{self.__class__} is an abstract class. Only classes inheriting this class can be called."""      )


class   lowerCAmelCase				(   __UpperCamelCase     ):
 def __init__( self    : Optional[int]     ,	UpperCAmelCase    : List[int]      )     ->      Optional[int]:
     super(UpperCAmelCase     ,	self      ).__init__()

     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ) or len(UpperCAmelCase      ) == 0:
         raise ValueError(F"""`token_ids` has to be a non-empty list, but is {token_ids}."""      )
     if any((not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ) or token_id < 0) for token_id in token_ids      ):
         raise ValueError(F"""Each list in `token_ids` has to be a list of positive integers, but is {token_ids}."""      )

     lowerCamelCase__       : Optional[int]   					=						token_ids

     lowerCamelCase__       : List[str]   					=						len(self.token_ids      )
     lowerCamelCase__       : Optional[Any]   					=						-1  # the index of the currently fulfilled step
     lowerCamelCase__       : List[str]   					=						False
 def 	A_      ( self    : Union[str, Any]      )     ->      Union[str, Any]:
     if self.completed:
         return None
     return self.token_ids[self.fulfilled_idx + 1]
 def 	A_      ( self    : Union[str, Any]     ,	UpperCAmelCase    : int      )     ->      List[Any]:
     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(F"""`token_id` has to be an `int`, but is {token_id} of type {type(UpperCAmelCase      )}"""      )

     if self.completed:
         return False

     return token_id == self.token_ids[self.fulfilled_idx + 1]
 def 	A_      ( self    : List[Any]     ,	UpperCAmelCase    : int      )     ->      Union[str, Any]:
     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(F"""`token_id` has to be an `int`, but is {token_id} of type {type(UpperCAmelCase      )}"""      )

     lowerCamelCase__       : List[Any]   					=						False
     lowerCamelCase__       : List[Any]   					=						False
     lowerCamelCase__       : Dict   					=						False

     if self.does_advance(UpperCAmelCase      ):
         self.fulfilled_idx += 1
         lowerCamelCase__       : List[str]   					=						True
         if self.fulfilled_idx == (self.seqlen - 1):
             lowerCamelCase__       : List[Any]   					=						True
         lowerCamelCase__       : Optional[int]   					=						completed
     else:
         # failed to make progress.
         lowerCamelCase__       : Union[str, Any]   					=						True
         self.reset()
     return stepped, completed, reset
 def 	A_      ( self    : Dict      )     ->      List[Any]:
     lowerCamelCase__       : str   					=						False
     lowerCamelCase__       : Dict   					=						0
 def 	A_      ( self    : Optional[Any]      )     ->      Tuple:
     return self.seqlen - (self.fulfilled_idx + 1)







 def 	A_      ( self    : int     ,	UpperCAmelCase    : List[Any]=False      )     ->      Dict:
     lowerCamelCase__       : int   					=						PhrasalConstraint(self.token_ids      )

     if stateful:
         lowerCamelCase__       : int   					=						self.seqlen
         lowerCamelCase__       : Union[str, Any]   					=						self.fulfilled_idx
         lowerCamelCase__       : str   					=						self.completed

     return new_constraint


class   lowerCAmelCase				:
 def __init__( self    : Union[str, Any]     ,	UpperCAmelCase    : List[List[int]]     ,	UpperCAmelCase    : List[str]=True      )     ->      Union[str, Any]:
     lowerCamelCase__       : Tuple   					=						max([len(UpperCAmelCase      ) for one in nested_token_ids]      )

     lowerCamelCase__       : Tuple   					=						{}
     for token_ids in nested_token_ids:
         lowerCamelCase__       : Any   					=						root
         for tidx, token_id in enumerate(UpperCAmelCase      ):
             if token_id not in level:
                 lowerCamelCase__       : Optional[Any]   					=						{}

             lowerCamelCase__       : Dict   					=						level[token_id]

     if no_subsets and self.has_subsets(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(
             'Each list in `nested_token_ids` can\'t be a complete subset of another list, but is'
             F""" {nested_token_ids}."""      )

     lowerCamelCase__       : Union[str, Any]   					=						root
 def 	A_      ( self    : Any     ,	UpperCAmelCase    : str      )     ->      Optional[int]:
     lowerCamelCase__       : str   					=						self.trie

     for current_token in current_seq:
         lowerCamelCase__       : Optional[Any]   					=						start[current_token]

     lowerCamelCase__       : Dict   					=						list(start.keys()      )

     return next_tokens
 def 	A_      ( self    : List[Any]     ,	UpperCAmelCase    : Union[str, Any]      )     ->      List[str]:
     lowerCamelCase__       : Optional[Any]   					=						self.next_tokens(UpperCAmelCase      )

     return len(UpperCAmelCase      ) == 0
 def 	A_      ( self    : Union[str, Any]     ,	UpperCAmelCase    : Tuple      )     ->      Dict:
     lowerCamelCase__       : str   					=						list(root.values()      )
     if len(UpperCAmelCase      ) == 0:
         return 1
     else:
         return sum([self.count_leaves(UpperCAmelCase      ) for nn in next_nodes]      )







 def 	A_      ( self    : Optional[int]     ,	UpperCAmelCase    : Union[str, Any]     ,	UpperCAmelCase    : Tuple      )     ->      Dict:
     lowerCamelCase__       : Optional[int]   					=						self.count_leaves(UpperCAmelCase      )
     return len(UpperCAmelCase      ) != leaf_count


class   lowerCAmelCase				(   __UpperCamelCase     ):
 def __init__( self    : Any     ,	UpperCAmelCase    : List[List[int]]      )     ->      str:
     super(UpperCAmelCase     ,	self      ).__init__()

     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ) or len(UpperCAmelCase      ) == 0:
         raise ValueError(F"""`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}."""      )
     if any(not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ) for token_ids in nested_token_ids      ):
         raise ValueError(F"""`nested_token_ids` has to be a list of lists, but is {nested_token_ids}."""      )
     if any(
         any((not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ) or token_id < 0) for token_id in token_ids      )
         for token_ids in nested_token_ids      ):
         raise ValueError(
             F"""Each list in `nested_token_ids` has to be a list of positive integers, but is {nested_token_ids}."""      )

     lowerCamelCase__       : List[str]   					=						DisjunctiveTrie(UpperCAmelCase      )
     lowerCamelCase__       : Union[str, Any]   					=						nested_token_ids

     lowerCamelCase__       : Optional[int]   					=						self.trie.max_height
     lowerCamelCase__       : Dict   					=						[]
     lowerCamelCase__       : int   					=						False
 def 	A_      ( self    : List[Any]      )     ->      List[str]:
     lowerCamelCase__       : Optional[Any]   					=						self.trie.next_tokens(self.current_seq      )

     if len(UpperCAmelCase      ) == 0:
         return None
     else:
         return token_list
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : int      )     ->      List[str]:
     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(F"""`token_id` is supposed to be type `int`, but is {token_id} of type {type(UpperCAmelCase      )}"""      )

     lowerCamelCase__       : Any   					=						self.trie.next_tokens(self.current_seq      )

     return token_id in next_tokens
 def 	A_      ( self    : Optional[int]     ,	UpperCAmelCase    : int      )     ->      Tuple:
     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(F"""`token_id` is supposed to be type `int`, but is {token_id} of type {type(UpperCAmelCase      )}"""      )

     lowerCamelCase__       : int   					=						False
     lowerCamelCase__       : str   					=						False
     lowerCamelCase__       : str   					=						False

     if self.does_advance(UpperCAmelCase      ):
         self.current_seq.append(UpperCAmelCase      )
         lowerCamelCase__       : List[Any]   					=						True
     else:
         lowerCamelCase__       : str   					=						True
         self.reset()

     lowerCamelCase__       : Dict   					=						self.trie.reached_leaf(self.current_seq      )
     lowerCamelCase__       : List[str]   					=						completed

     return stepped, completed, reset
 def 	A_      ( self    : Dict      )     ->      List[str]:
     lowerCamelCase__       : List[Any]   					=						False
     lowerCamelCase__       : Union[str, Any]   					=						[]
 def 	A_      ( self    : int      )     ->      Union[str, Any]:
     if self.completed:
         # since this can be completed without reaching max height
         return 0
     else:
         return self.seqlen - len(self.current_seq      )







 def 	A_      ( self    : Any     ,	UpperCAmelCase    : Optional[int]=False      )     ->      Optional[Any]:
     lowerCamelCase__       : Dict   					=						DisjunctiveConstraint(self.token_ids      )

     if stateful:
         lowerCamelCase__       : Optional[int]   					=						self.seqlen
         lowerCamelCase__       : Any   					=						self.current_seq
         lowerCamelCase__       : int   					=						self.completed

     return new_constraint


class   lowerCAmelCase				:
 def __init__( self    : Tuple     ,	UpperCAmelCase    : List[Constraint]      )     ->      str:
     lowerCamelCase__       : str   					=						constraints

     # max # of steps required to fulfill a given constraint
     lowerCamelCase__       : Dict   					=						max([c.seqlen for c in constraints]      )
     lowerCamelCase__       : str   					=						len(UpperCAmelCase      )
     lowerCamelCase__       : Union[str, Any]   					=						False

     self.init_state()
 def 	A_      ( self    : List[str]      )     ->      List[str]:
     lowerCamelCase__       : int   					=						[]
     lowerCamelCase__       : Optional[int]   					=						None
     lowerCamelCase__       : Optional[Any]   					=						[constraint.copy(stateful=UpperCAmelCase      ) for constraint in self.constraints]
 def 	A_      ( self    : List[Any]      )     ->      Union[str, Any]:
     lowerCamelCase__       : Union[str, Any]   					=						0
     if self.inprogress_constraint:
         # extra points for having a constraint mid-fulfilled
         add += self.max_seqlen - self.inprogress_constraint.remaining()

     return (len(self.complete_constraints      ) * self.max_seqlen) + add
 def 	A_      ( self    : Optional[Any]      )     ->      Union[str, Any]:
     lowerCamelCase__       : Optional[Any]   					=						[]
     if self.inprogress_constraint is None:
         for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
             lowerCamelCase__       : Union[str, Any]   					=						constraint.advance()
             if isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
                 token_list.append(UpperCAmelCase      )
             elif isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
                 token_list.extend(UpperCAmelCase      )
     else:
         lowerCamelCase__       : Union[str, Any]   					=						self.inprogress_constraint.advance()
         if isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
             token_list.append(UpperCAmelCase      )
         elif isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
             token_list.extend(UpperCAmelCase      )

     if len(UpperCAmelCase      ) == 0:
         return None
     else:
         return token_list
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : Optional[List[int]]      )     ->      Dict:
     self.init_state()

     if token_ids is not None:
         for token in token_ids:
             # completes or steps **one** constraint
             lowerCamelCase__					,				lowerCamelCase__       : Tuple   					=						self.add(UpperCAmelCase      )

             # the entire list of constraints are fulfilled
             if self.completed:
                 break
 def 	A_      ( self    : List[Any]     ,	UpperCAmelCase    : int      )     ->      Dict:
     if not isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
         raise ValueError(F"""`token_id` should be an `int`, but is `{token_id}`."""      )

     lowerCamelCase__					,				lowerCamelCase__       : Optional[Any]   					=						False, False

     if self.completed:
         lowerCamelCase__       : int   					=						True
         lowerCamelCase__       : Any   					=						False
         return complete, stepped

     if self.inprogress_constraint is not None:
         # In the middle of fulfilling a constraint. If the `token_id` *does* makes an incremental progress to current
         # job, simply update the state

         lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : Tuple   					=						self.inprogress_constraint.update(UpperCAmelCase      )
         if reset:
             # 1. If the next token breaks the progress, then we must restart.
             #     e.g. constraint = "I love pies" and sequence so far is "I love" but `token_id` == "books".

             #     But that doesn't mean we self.init_state(), since we only reset the state for this particular
             #     constraint, not the full list of constraints.

             self.pending_constraints.append(self.inprogress_constraint.copy(stateful=UpperCAmelCase      )      )
             lowerCamelCase__       : List[str]   					=						None

         if complete:
             # 2. If the next token completes the constraint, move it to completed list, set
             #     inprogress to None. If there are no pending constraints either, then this full list of constraints
             #     is complete.

             self.complete_constraints.append(self.inprogress_constraint      )
             lowerCamelCase__       : Union[str, Any]   					=						None

             if len(self.pending_constraints      ) == 0:
                 # we're done!
                 lowerCamelCase__       : List[str]   					=						True

     else:
         # Not in the middle of fulfilling a constraint. So does this `token_id` helps us step towards any of our list
         # of constraints?

         for cidx, pending_constraint in enumerate(self.pending_constraints      ):
             if pending_constraint.does_advance(UpperCAmelCase      ):
                 lowerCamelCase__					,				lowerCamelCase__					,				lowerCamelCase__       : List[Any]   					=						pending_constraint.update(UpperCAmelCase      )

                 if not stepped:
                     raise Exception(
                         '`constraint.update(token_id)` is not yielding incremental progress, '
                         'even though `constraint.does_advance(token_id)` is true.'      )

                 if complete:
                     self.complete_constraints.append(UpperCAmelCase      )
                     lowerCamelCase__       : Tuple   					=						None

                 if not complete and stepped:
                     lowerCamelCase__       : Any   					=						pending_constraint

                 if complete or stepped:
                     # If we made any progress at all, then it's at least not a "pending constraint".

                     lowerCamelCase__       : List[Any]   					=						(
                         self.pending_constraints[:cidx] + self.pending_constraints[cidx + 1 :]
                     )

                     if len(self.pending_constraints      ) == 0 and self.inprogress_constraint is None:
                         # If there's no longer any pending after this and no inprogress either, then we must be
                         # complete.

                         lowerCamelCase__       : Union[str, Any]   					=						True

                     break  # prevent accidentally stepping through multiple constraints with just one token.

     return complete, stepped







 def 	A_      ( self    : Union[str, Any]     ,	UpperCAmelCase    : Tuple=True      )     ->      Tuple:
     lowerCamelCase__       : Optional[int]   					=						ConstraintListState(self.constraints      )  # we actually never though self.constraints objects
     # throughout this process. So it's at initialization state.

     if stateful:
         lowerCamelCase__       : Any   					=						[
             constraint.copy(stateful=UpperCAmelCase      ) for constraint in self.complete_constraints
         ]
         if self.inprogress_constraint is not None:
             lowerCamelCase__       : Any   					=						self.inprogress_constraint.copy(stateful=UpperCAmelCase      )
         lowerCamelCase__       : List[Any]   					=						[constraint.copy() for constraint in self.pending_constraints]

     return new_state












import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
    from PIL import Image

    from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor

@require_tokenizers
@require_vision
class   lowerCAmelCase				(   unittest.TestCase     ):
 def 	A_      ( self    : str      )     ->      Dict:
     lowerCamelCase__       : Optional[Any]   					=						tempfile.mkdtemp()

     # fmt: off
     lowerCamelCase__       : Tuple   					=						['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
     # fmt: on
     lowerCamelCase__       : int   					=						os.path.join(self.tmpdirname     ,	VOCAB_FILES_NAMES['vocab_file']      )
     with open(self.vocab_file     ,	'w'     ,	encoding='utf-8'      ) as vocab_writer:
         vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]      )      )

     lowerCamelCase__       : Any   					=						{
         'do_resize': True,
         'size': {'height': 18, 'width': 18},
         'do_normalize': True,
         'image_mean': [0.5, 0.5, 0.5],
         'image_std': [0.5, 0.5, 0.5],
     }
     lowerCamelCase__       : int   					=						os.path.join(self.tmpdirname     ,	UpperCAmelCase      )
     with open(self.image_processor_file     ,	'w'     ,	encoding='utf-8'      ) as fp:
         json.dump(UpperCAmelCase     ,	UpperCAmelCase      )
 def 	A_      ( self    : List[str]     ,	**UpperCAmelCase    : str      )     ->      int:
     return BertTokenizer.from_pretrained(self.tmpdirname     ,	**UpperCAmelCase      )
 def 	A_      ( self    : Optional[int]     ,	**UpperCAmelCase    : List[str]      )     ->      List[str]:
     return ViTImageProcessor.from_pretrained(self.tmpdirname     ,	**UpperCAmelCase      )
 def 	A_      ( self    : int      )     ->      Any:
     shutil.rmtree(self.tmpdirname      )
 def 	A_      ( self    : str      )     ->      str:
     lowerCamelCase__       : List[Any]   					=						[np.random.randint(255     ,	size=(3, 30, 400)     ,	dtype=np.uinta      )]

     lowerCamelCase__       : Union[str, Any]   					=						[Image.fromarray(np.moveaxis(UpperCAmelCase     ,	0     ,	-1      )      ) for x in image_inputs]

     return image_inputs
 def 	A_      ( self    : Dict      )     ->      Dict:
     lowerCamelCase__       : List[Any]   					=						self.get_tokenizer()
     lowerCamelCase__       : Tuple   					=						self.get_image_processor()

     lowerCamelCase__       : Union[str, Any]   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     processor.save_pretrained(self.tmpdirname      )
     lowerCamelCase__       : List[str]   					=						VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname      )

     self.assertEqual(processor.tokenizer.get_vocab()     ,	tokenizer.get_vocab()      )
     self.assertIsInstance(processor.tokenizer     ,	(BertTokenizer, BertTokenizerFast)      )

     self.assertEqual(processor.image_processor.to_json_string()     ,	image_processor.to_json_string()      )
     self.assertIsInstance(processor.image_processor     ,	UpperCAmelCase      )
 def 	A_      ( self    : List[str]      )     ->      Tuple:
     lowerCamelCase__       : List[Any]   					=						VisionTextDualEncoderProcessor(
         tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()      )
     processor.save_pretrained(self.tmpdirname      )

     lowerCamelCase__       : Tuple   					=						self.get_tokenizer(bos_token='(BOS)'     ,	eos_token='(EOS)'      )
     lowerCamelCase__       : int   					=						self.get_image_processor(do_normalize=UpperCAmelCase     ,	padding_value=1.0      )

     lowerCamelCase__       : Union[str, Any]   					=						VisionTextDualEncoderProcessor.from_pretrained(
         self.tmpdirname     ,	bos_token='(BOS)'     ,	eos_token='(EOS)'     ,	do_normalize=UpperCAmelCase     ,	padding_value=1.0      )

     self.assertEqual(processor.tokenizer.get_vocab()     ,	tokenizer_add_kwargs.get_vocab()      )
     self.assertIsInstance(processor.tokenizer     ,	(BertTokenizer, BertTokenizerFast)      )

     self.assertEqual(processor.image_processor.to_json_string()     ,	image_processor_add_kwargs.to_json_string()      )
     self.assertIsInstance(processor.image_processor     ,	UpperCAmelCase      )
 def 	A_      ( self    : Any      )     ->      Tuple:
     lowerCamelCase__       : List[Any]   					=						self.get_image_processor()
     lowerCamelCase__       : Any   					=						self.get_tokenizer()

     lowerCamelCase__       : Optional[int]   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     lowerCamelCase__       : Optional[int]   					=						self.prepare_image_inputs()

     lowerCamelCase__       : int   					=						image_processor(UpperCAmelCase     ,	return_tensors='np'      )
     lowerCamelCase__       : List[str]   					=						processor(images=UpperCAmelCase     ,	return_tensors='np'      )

     for key in input_feat_extract.keys():
         self.assertAlmostEqual(input_feat_extract[key].sum()     ,	input_processor[key].sum()     ,	delta=1e-2      )
 def 	A_      ( self    : Tuple      )     ->      List[Any]:
     lowerCamelCase__       : Dict   					=						self.get_image_processor()
     lowerCamelCase__       : List[str]   					=						self.get_tokenizer()

     lowerCamelCase__       : str   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     lowerCamelCase__       : Tuple   					=						'lower newer'

     lowerCamelCase__       : Tuple   					=						processor(text=UpperCAmelCase      )

     lowerCamelCase__       : Any   					=						tokenizer(UpperCAmelCase      )

     for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key]     ,	encoded_processor[key]      )
 def 	A_      ( self    : Optional[int]      )     ->      Any:
     lowerCamelCase__       : Optional[int]   					=						self.get_image_processor()
     lowerCamelCase__       : Tuple   					=						self.get_tokenizer()

     lowerCamelCase__       : Tuple   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     lowerCamelCase__       : str   					=						'lower newer'
     lowerCamelCase__       : Dict   					=						self.prepare_image_inputs()

     lowerCamelCase__       : int   					=						processor(text=UpperCAmelCase     ,	images=UpperCAmelCase      )

     self.assertListEqual(list(inputs.keys()      )     ,	['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']      )

     # test if it raises when no input is passed
     with self.assertRaises(UpperCAmelCase      ):
         processor()
 def 	A_      ( self    : Optional[Any]      )     ->      List[str]:
     lowerCamelCase__       : Dict   					=						self.get_image_processor()
     lowerCamelCase__       : Union[str, Any]   					=						self.get_tokenizer()

     lowerCamelCase__       : List[str]   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     lowerCamelCase__       : List[str]   					=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     lowerCamelCase__       : Dict   					=						processor.batch_decode(UpperCAmelCase      )
     lowerCamelCase__       : List[str]   					=						tokenizer.batch_decode(UpperCAmelCase      )

     self.assertListEqual(UpperCAmelCase     ,	UpperCAmelCase      )







 def 	A_      ( self    : Optional[int]      )     ->      List[str]:
     lowerCamelCase__       : Tuple   					=						self.get_image_processor()
     lowerCamelCase__       : List[str]   					=						self.get_tokenizer()

     lowerCamelCase__       : Union[str, Any]   					=						VisionTextDualEncoderProcessor(tokenizer=UpperCAmelCase     ,	image_processor=UpperCAmelCase      )

     lowerCamelCase__       : Dict   					=						'lower newer'
     lowerCamelCase__       : List[Any]   					=						self.prepare_image_inputs()

     lowerCamelCase__       : Union[str, Any]   					=						processor(text=UpperCAmelCase     ,	images=UpperCAmelCase      )

     self.assertListEqual(list(inputs.keys()      )     ,	processor.model_input_names      )





