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





class     __UpperCamelCase (							lowerCAmelCase__       ):






     """simple docstring"""







     def __init__(				self							:							Union[str, Any] ):







       """simple docstring"""




       self.test()



     def  UpperCAmelCase__							(				self							:							List[str] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[str]					=		0
       __SCREAMING_SNAKE_CASE      :	str					=		False
       while not completed:
         if counter == 1:
           self.reset()
         __SCREAMING_SNAKE_CASE      :	int					=		self.advance()
         if not self.does_advance(_A ):
           raise Exception(
               '''Custom Constraint is not defined correctly. self.does_advance(self.advance()) must be true.''' )

         __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Optional[int]					=		self.update(_A )
         counter += 1

         if counter > 1_0000:
           raise Exception('''update() does not fulfill the constraint.''' )

       if self.remaining() != 0:
         raise Exception('''Custom Constraint is not defined correctly.''' )



     @abstractmethod
     def  UpperCAmelCase__							(				self							:							List[Any] ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )



     @abstractmethod
     def  UpperCAmelCase__							(				self							:							Tuple     ,						_A							:							int ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )



     @abstractmethod
     def  UpperCAmelCase__							(				self							:							Any     ,						_A							:							int ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )



     @abstractmethod
     def  UpperCAmelCase__							(				self							:							List[str] ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )



     @abstractmethod
     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )




     @abstractmethod
     def  UpperCAmelCase__							(				self							:							Tuple     ,						_A							:							Dict=False ):







       """simple docstring"""




       raise NotImplementedError(
           F'''{self.__class__} is an abstract class. Only classes inheriting this class can be called.''' )






class     __UpperCamelCase (							lowerCAmelCase__       ):






     """simple docstring"""







     def __init__(				self							:							int     ,						_A							:							List[int] ):







       """simple docstring"""




       super(_A     ,						self ).__init__()

       if not isinstance(_A     ,						_A ) or len(_A ) == 0:
         raise ValueError(F'''`token_ids` has to be a non-empty list, but is {token_ids}.''' )
       if any((not isinstance(_A     ,						_A ) 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}.''' )

       __SCREAMING_SNAKE_CASE      :	Tuple					=		token_ids

       __SCREAMING_SNAKE_CASE      :	List[Any]					=		len(self.token_ids )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		-1  # the index of the currently fulfilled step
       __SCREAMING_SNAKE_CASE      :	int					=		False



     def  UpperCAmelCase__							(				self							:							Dict ):







       """simple docstring"""




       if self.completed:
         return None
       return self.token_ids[self.fulfilled_idx + 1]



     def  UpperCAmelCase__							(				self							:							Tuple     ,						_A							:							int ):







       """simple docstring"""




       if not isinstance(_A     ,						_A ):
         raise ValueError(F'''`token_id` has to be an `int`, but is {token_id} of type {type(_A )}''' )

       if self.completed:
         return False

       return token_id == self.token_ids[self.fulfilled_idx + 1]



     def  UpperCAmelCase__							(				self							:							str     ,						_A							:							int ):







       """simple docstring"""




       if not isinstance(_A     ,						_A ):
         raise ValueError(F'''`token_id` has to be an `int`, but is {token_id} of type {type(_A )}''' )

       __SCREAMING_SNAKE_CASE      :	Any					=		False
       __SCREAMING_SNAKE_CASE      :	Tuple					=		False
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		False

       if self.does_advance(_A ):
         self.fulfilled_idx += 1
         __SCREAMING_SNAKE_CASE      :	int					=		True
         if self.fulfilled_idx == (self.seqlen - 1):
           __SCREAMING_SNAKE_CASE      :	Any					=		True
         __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		completed
       else:
         # failed to make progress.
         __SCREAMING_SNAKE_CASE      :	Optional[int]					=		True
         self.reset()
       return stepped, completed, reset



     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Any					=		False
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		0



     def  UpperCAmelCase__							(				self							:							int ):







       """simple docstring"""




       return self.seqlen - (self.fulfilled_idx + 1)




     def  UpperCAmelCase__							(				self							:							Union[str, Any]     ,						_A							:							List[Any]=False ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		PhrasalConstraint(self.token_ids )

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

       return new_constraint






class     __UpperCamelCase :






     """simple docstring"""







     def __init__(				self							:							Optional[int]     ,						_A							:							List[List[int]]     ,						_A							:							Tuple=True ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	str					=		max([len(_A ) for one in nested_token_ids] )

       __SCREAMING_SNAKE_CASE      :	List[str]					=		{}
       for token_ids in nested_token_ids:
         __SCREAMING_SNAKE_CASE      :	List[str]					=		root
         for tidx, token_id in enumerate(_A ):
           if token_id not in level:
             __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		{}

           __SCREAMING_SNAKE_CASE      :	Dict					=		level[token_id]

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

       __SCREAMING_SNAKE_CASE      :	Dict					=		root



     def  UpperCAmelCase__							(				self							:							Dict     ,						_A							:							Any ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[str]					=		self.trie

       for current_token in current_seq:
         __SCREAMING_SNAKE_CASE      :	str					=		start[current_token]

       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		list(start.keys() )

       return next_tokens



     def  UpperCAmelCase__							(				self							:							Tuple     ,						_A							:							Dict ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[str]					=		self.next_tokens(_A )

       return len(_A ) == 0



     def  UpperCAmelCase__							(				self							:							int     ,						_A							:							Tuple ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	str					=		list(root.values() )
       if len(_A ) == 0:
         return 1
       else:
         return sum([self.count_leaves(_A ) for nn in next_nodes] )




     def  UpperCAmelCase__							(				self							:							Union[str, Any]     ,						_A							:							List[Any]     ,						_A							:							int ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		self.count_leaves(_A )
       return len(_A ) != leaf_count






class     __UpperCamelCase (							lowerCAmelCase__       ):






     """simple docstring"""







     def __init__(				self							:							str     ,						_A							:							List[List[int]] ):







       """simple docstring"""




       super(_A     ,						self ).__init__()

       if not isinstance(_A     ,						_A ) or len(_A ) == 0:
         raise ValueError(F'''`nested_token_ids` has to be a non-empty list, but is {nested_token_ids}.''' )
       if any(not isinstance(_A     ,						_A ) 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(_A     ,						_A ) 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}.''' )

       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		DisjunctiveTrie(_A )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		nested_token_ids

       __SCREAMING_SNAKE_CASE      :	Any					=		self.trie.max_height
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		[]
       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		False



     def  UpperCAmelCase__							(				self							:							int ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[str]					=		self.trie.next_tokens(self.current_seq )

       if len(_A ) == 0:
         return None
       else:
         return token_list



     def  UpperCAmelCase__							(				self							:							Union[str, Any]     ,						_A							:							int ):







       """simple docstring"""




       if not isinstance(_A     ,						_A ):
         raise ValueError(F'''`token_id` is supposed to be type `int`, but is {token_id} of type {type(_A )}''' )

       __SCREAMING_SNAKE_CASE      :	List[str]					=		self.trie.next_tokens(self.current_seq )

       return token_id in next_tokens



     def  UpperCAmelCase__							(				self							:							List[str]     ,						_A							:							int ):







       """simple docstring"""




       if not isinstance(_A     ,						_A ):
         raise ValueError(F'''`token_id` is supposed to be type `int`, but is {token_id} of type {type(_A )}''' )

       __SCREAMING_SNAKE_CASE      :	int					=		False
       __SCREAMING_SNAKE_CASE      :	Dict					=		False
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		False

       if self.does_advance(_A ):
         self.current_seq.append(_A )
         __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		True
       else:
         __SCREAMING_SNAKE_CASE      :	Tuple					=		True
         self.reset()

       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		self.trie.reached_leaf(self.current_seq )
       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		completed

       return stepped, completed, reset



     def  UpperCAmelCase__							(				self							:							Tuple ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Any					=		False
       __SCREAMING_SNAKE_CASE      :	Any					=		[]



     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




       if self.completed:
         # since this can be completed without reaching max height
         return 0
       else:
         return self.seqlen - len(self.current_seq )




     def  UpperCAmelCase__							(				self							:							Dict     ,						_A							:							List[str]=False ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	str					=		DisjunctiveConstraint(self.token_ids )

       if stateful:
         __SCREAMING_SNAKE_CASE      :	Dict					=		self.seqlen
         __SCREAMING_SNAKE_CASE      :	Tuple					=		self.current_seq
         __SCREAMING_SNAKE_CASE      :	Optional[int]					=		self.completed

       return new_constraint






class     __UpperCamelCase :






     """simple docstring"""







     def __init__(				self							:							Dict     ,						_A							:							List[Constraint] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[int]					=		constraints

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

       self.init_state()



     def  UpperCAmelCase__							(				self							:							Union[str, Any] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[Any]					=		[]
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		None
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		[constraint.copy(stateful=_A ) for constraint in self.constraints]



     def  UpperCAmelCase__							(				self							:							int ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Optional[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  UpperCAmelCase__							(				self							:							List[str] ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	List[str]					=		[]
       if self.inprogress_constraint is None:
         for constraint in self.pending_constraints:  # "pending" == "unfulfilled yet"
           __SCREAMING_SNAKE_CASE      :	Any					=		constraint.advance()
           if isinstance(_A     ,						_A ):
             token_list.append(_A )
           elif isinstance(_A     ,						_A ):
             token_list.extend(_A )
       else:
         __SCREAMING_SNAKE_CASE      :	Any					=		self.inprogress_constraint.advance()
         if isinstance(_A     ,						_A ):
           token_list.append(_A )
         elif isinstance(_A     ,						_A ):
           token_list.extend(_A )

       if len(_A ) == 0:
         return None
       else:
         return token_list



     def  UpperCAmelCase__							(				self							:							int     ,						_A							:							Optional[List[int]] ):







       """simple docstring"""




       self.init_state()

       if token_ids is not None:
         for token in token_ids:
           # completes or steps **one** constraint
           __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Optional[Any]					=		self.add(_A )

           # the entire list of constraints are fulfilled
           if self.completed:
             break



     def  UpperCAmelCase__							(				self							:							Optional[int]     ,						_A							:							int ):







       """simple docstring"""




       if not isinstance(_A     ,						_A ):
         raise ValueError(F'''`token_id` should be an `int`, but is `{token_id}`.''' )

       __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	List[Any]					=		False, False

       if self.completed:
         __SCREAMING_SNAKE_CASE      :	Dict					=		True
         __SCREAMING_SNAKE_CASE      :	List[str]					=		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

         __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		self.inprogress_constraint.update(_A )
         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=_A ) )
           __SCREAMING_SNAKE_CASE      :	int					=		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 )
           __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		None

           if len(self.pending_constraints ) == 0:
             # we're done!
             __SCREAMING_SNAKE_CASE      :	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(_A ):
             __SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		pending_constraint.update(_A )

             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(_A )
               __SCREAMING_SNAKE_CASE      :	Tuple					=		None

             if not complete and stepped:
               __SCREAMING_SNAKE_CASE      :	List[str]					=		pending_constraint

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

               __SCREAMING_SNAKE_CASE      :	Optional[int]					=		(
                   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.

                 __SCREAMING_SNAKE_CASE      :	Any					=		True

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

       return complete, stepped




     def  UpperCAmelCase__							(				self							:							Union[str, Any]     ,						_A							:							int=True ):







       """simple docstring"""




       __SCREAMING_SNAKE_CASE      :	Tuple					=		ConstraintListState(self.constraints )  # we actually never though self.constraints objects
       # throughout this process. So it's at initialization state.

       if stateful:
         __SCREAMING_SNAKE_CASE      :	List[str]					=		[
             constraint.copy(stateful=_A ) for constraint in self.complete_constraints
         ]
         if self.inprogress_constraint is not None:
           __SCREAMING_SNAKE_CASE      :	Tuple					=		self.inprogress_constraint.copy(stateful=_A )
         __SCREAMING_SNAKE_CASE      :	Optional[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
import pytest

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


if is_vision_available():
   from PIL import Image

   from transformers import AlignProcessor, EfficientNetImageProcessor


@require_vision
class 	lowerCamelCase__	(       unittest.TestCase):



 """simple docstring"""

 def     snake_case_      (    self					:					Tuple      )   ->	Optional[int]:
    _A      =       tempfile.mkdtemp()

    _A      =       [
        '''[UNK]''',
        '''[CLS]''',
        '''[SEP]''',
        '''[PAD]''',
        '''[MASK]''',
        '''want''',
        '''##want''',
        '''##ed''',
        '''wa''',
        '''un''',
        '''runn''',
        '''##ing''',
        ''',''',
        '''low''',
        '''lowest''',
    ]
    _A      =       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]      )      )

    _A      =       {
        '''do_resize''': True,
        '''size''': 20,
        '''do_center_crop''': True,
        '''crop_size''': 18,
        '''do_normalize''': True,
        '''image_mean''': [0.4814_5466, 0.457_8275, 0.4082_1073],
        '''image_std''': [0.2686_2954, 0.2613_0258, 0.2757_7711],
    }
    _A      =       os.path.join(self.tmpdirname			,						__lowerCAmelCase      )
    with open(self.image_processor_file			,						'''w'''			,						encoding='''utf-8'''      ) as fp:
       json.dump(__lowerCAmelCase			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					Dict			,						**__lowerCAmelCase					:					int      )   ->	Optional[int]:
    return BertTokenizer.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					str			,						**__lowerCAmelCase					:					Optional[Any]      )   ->	Tuple:
    return BertTokenizerFast.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					Tuple			,						**__lowerCAmelCase					:					str      )   ->	Union[str, Any]:
    return EfficientNetImageProcessor.from_pretrained(self.tmpdirname			,						**__lowerCAmelCase      )

 def     snake_case_      (    self					:					Optional[Any]      )   ->	Optional[int]:
    shutil.rmtree(self.tmpdirname      )

 def     snake_case_      (    self					:					int      )   ->	Optional[Any]:
    _A      =       [np.random.randint(2_55			,						size=(3, 30, 4_00)			,						dtype=np.uinta      )]
    _A      =       [Image.fromarray(np.moveaxis(__lowerCAmelCase			,						0			,						-1      )      ) for x in image_inputs]
    return image_inputs

 def     snake_case_      (    self					:					Dict      )   ->	List[str]:
    _A      =       self.get_tokenizer()
    _A      =       self.get_rust_tokenizer()
    _A      =       self.get_image_processor()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )
    processor_slow.save_pretrained(self.tmpdirname      )
    _A      =       AlignProcessor.from_pretrained(self.tmpdirname			,						use_fast=__lowerCAmelCase      )

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )
    processor_fast.save_pretrained(self.tmpdirname      )
    _A      =       AlignProcessor.from_pretrained(self.tmpdirname      )

    self.assertEqual(processor_slow.tokenizer.get_vocab()			,						tokenizer_slow.get_vocab()      )
    self.assertEqual(processor_fast.tokenizer.get_vocab()			,						tokenizer_fast.get_vocab()      )
    self.assertEqual(tokenizer_slow.get_vocab()			,						tokenizer_fast.get_vocab()      )
    self.assertIsInstance(processor_slow.tokenizer			,						__lowerCAmelCase      )
    self.assertIsInstance(processor_fast.tokenizer			,						__lowerCAmelCase      )

    self.assertEqual(processor_slow.image_processor.to_json_string()			,						image_processor.to_json_string()      )
    self.assertEqual(processor_fast.image_processor.to_json_string()			,						image_processor.to_json_string()      )
    self.assertIsInstance(processor_slow.image_processor			,						__lowerCAmelCase      )
    self.assertIsInstance(processor_fast.image_processor			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					List[Any]      )   ->	List[str]:
    _A      =       AlignProcessor(tokenizer=self.get_tokenizer()			,						image_processor=self.get_image_processor()      )
    processor.save_pretrained(self.tmpdirname      )

    _A      =       self.get_tokenizer(bos_token='''(BOS)'''			,						eos_token='''(EOS)'''      )
    _A      =       self.get_image_processor(do_normalize=__lowerCAmelCase			,						padding_value=1.0      )

    _A      =       AlignProcessor.from_pretrained(
        self.tmpdirname			,						bos_token='''(BOS)'''			,						eos_token='''(EOS)'''			,						do_normalize=__lowerCAmelCase			,						padding_value=1.0      )

    self.assertEqual(processor.tokenizer.get_vocab()			,						tokenizer_add_kwargs.get_vocab()      )
    self.assertIsInstance(processor.tokenizer			,						__lowerCAmelCase      )

    self.assertEqual(processor.image_processor.to_json_string()			,						image_processor_add_kwargs.to_json_string()      )
    self.assertIsInstance(processor.image_processor			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					str      )   ->	List[Any]:
    _A      =       self.get_image_processor()
    _A      =       self.get_tokenizer()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )

    _A      =       self.prepare_image_inputs()

    _A      =       image_processor(__lowerCAmelCase			,						return_tensors='''np'''      )
    _A      =       processor(images=__lowerCAmelCase			,						return_tensors='''np'''      )

    for key in input_image_proc.keys():
       self.assertAlmostEqual(input_image_proc[key].sum()			,						input_processor[key].sum()			,						delta=1E-2      )

 def     snake_case_      (    self					:					Union[str, Any]      )   ->	Dict:
    _A      =       self.get_image_processor()
    _A      =       self.get_tokenizer()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )

    _A      =       '''lower newer'''

    _A      =       processor(text=__lowerCAmelCase      )

    _A      =       tokenizer(__lowerCAmelCase			,						padding='''max_length'''			,						max_length=64      )

    for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key]			,						encoded_processor[key]      )

 def     snake_case_      (    self					:					List[str]      )   ->	Any:
    _A      =       self.get_image_processor()
    _A      =       self.get_tokenizer()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )

    _A      =       '''lower newer'''
    _A      =       self.prepare_image_inputs()

    _A      =       processor(text=__lowerCAmelCase			,						images=__lowerCAmelCase      )

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

    # test if it raises when no input is passed
    with pytest.raises(__lowerCAmelCase      ):
       processor()

 def     snake_case_      (    self					:					Optional[Any]      )   ->	str:
    _A      =       self.get_image_processor()
    _A      =       self.get_tokenizer()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )

    _A      =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

    _A      =       processor.batch_decode(__lowerCAmelCase      )
    _A      =       tokenizer.batch_decode(__lowerCAmelCase      )

    self.assertListEqual(__lowerCAmelCase			,						__lowerCAmelCase      )

 def     snake_case_      (    self					:					str      )   ->	str:
    _A      =       self.get_image_processor()
    _A      =       self.get_tokenizer()

    _A      =       AlignProcessor(tokenizer=__lowerCAmelCase			,						image_processor=__lowerCAmelCase      )

    _A      =       '''lower newer'''
    _A      =       self.prepare_image_inputs()

    _A      =       processor(text=__lowerCAmelCase			,						images=__lowerCAmelCase      )

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



