


'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 CLIPSegProcessor, ViTImageProcessor
@require_vision
class    lowercase	(							unittest.TestCase					):

		"""simple docstring"""

		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= tempfile.mkdtemp()

							# fmt: off
							UpperCamelCase__   :int												= ['''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
							# fmt: on
							UpperCamelCase__   :int												= dict(zip(UpperCamelCase_    ,   range(len(UpperCamelCase_							)							)							)							)
							UpperCamelCase__   :Optional[int]												= ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
							UpperCamelCase__   :Union[str, Any]												= {'''unk_token''': '''<unk>'''}

							UpperCamelCase__   :Optional[Any]												= os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES['''vocab_file''']							)
							UpperCamelCase__   :Dict												= os.path.join(self.tmpdirname    ,   VOCAB_FILES_NAMES['''merges_file''']							)
							with open(self.vocab_file    ,   '''w'''    ,   encoding='''utf-8'''							) as fp:
												fp.write(json.dumps(UpperCamelCase_							) + '''\n'''							)
							with open(self.merges_file    ,   '''w'''    ,   encoding='''utf-8'''							) as fp:
												fp.write('''\n'''.join(UpperCamelCase_							)							)

							UpperCamelCase__   :Union[str, Any]												= {
							    '''do_resize''': True,
							    '''size''': 20,
							    '''do_center_crop''': True,
							    '''crop_size''': 18,
							    '''do_normalize''': True,
							    '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
							    '''image_std''': [0.26862954, 0.26130258, 0.27577711],
							}
							UpperCamelCase__   :Any												= os.path.join(self.tmpdirname    ,   UpperCamelCase_							)
							with open(self.image_processor_file    ,   '''w'''    ,   encoding='''utf-8'''							) as fp:
												json.dump(UpperCamelCase_    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							return CLIPTokenizer.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self    ,   **UpperCamelCase_							):

							'''simple docstring'''


							return ViTImageProcessor.from_pretrained(self.tmpdirname    ,   **UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= [np.random.randint(255    ,   size=(3, 30, 400)    ,   dtype=np.uinta							)]

							UpperCamelCase__   :Optional[Any]												= [Image.fromarray(np.moveaxis(UpperCamelCase_    ,   0    ,   -1							)							) for x in image_inputs]

							return image_inputs




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[int]												= self.get_tokenizer()
							UpperCamelCase__   :Dict												= self.get_rust_tokenizer()
							UpperCamelCase__   :Dict												= self.get_image_processor()

							UpperCamelCase__   :Optional[Any]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)
							processor_slow.save_pretrained(self.tmpdirname							)
							UpperCamelCase__   :str												= CLIPSegProcessor.from_pretrained(self.tmpdirname    ,   use_fast=UpperCamelCase_							)

							UpperCamelCase__   :Optional[int]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)
							processor_fast.save_pretrained(self.tmpdirname							)
							UpperCamelCase__   :Any												= CLIPSegProcessor.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    ,   UpperCamelCase_							)
							self.assertIsInstance(processor_fast.tokenizer    ,   UpperCamelCase_							)

							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    ,   UpperCamelCase_							)
							self.assertIsInstance(processor_fast.image_processor    ,   UpperCamelCase_							)




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= CLIPSegProcessor(tokenizer=self.get_tokenizer()    ,   image_processor=self.get_image_processor()							)
							processor.save_pretrained(self.tmpdirname							)

							UpperCamelCase__   :Dict												= self.get_tokenizer(bos_token='''(BOS)'''    ,   eos_token='''(EOS)'''							)
							UpperCamelCase__   :Optional[Any]												= self.get_image_processor(do_normalize=UpperCamelCase_    ,   padding_value=1.0							)

							UpperCamelCase__   :List[str]												= CLIPSegProcessor.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    ,   UpperCamelCase_							)

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= self.get_image_processor()
							UpperCamelCase__   :str												= self.get_tokenizer()

							UpperCamelCase__   :List[Any]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :str												= self.prepare_image_inputs()

							UpperCamelCase__   :Optional[int]												= image_processor(UpperCamelCase_    ,   return_tensors='''np'''							)
							UpperCamelCase__   :Dict												= 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     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Tuple												= self.get_image_processor()
							UpperCamelCase__   :Optional[Any]												= self.get_tokenizer()

							UpperCamelCase__   :List[str]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :List[str]												= '''lower newer'''

							UpperCamelCase__   :str												= processor(text=UpperCamelCase_							)

							UpperCamelCase__   :Any												= tokenizer(UpperCamelCase_							)

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :List[str]												= self.get_image_processor()
							UpperCamelCase__   :Tuple												= self.get_tokenizer()

							UpperCamelCase__   :List[str]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :Tuple												= '''lower newer'''
							UpperCamelCase__   :List[Any]												= self.prepare_image_inputs()

							UpperCamelCase__   :List[Any]												= processor(text=UpperCamelCase_    ,   images=UpperCamelCase_							)

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

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Any												= self.get_image_processor()
							UpperCamelCase__   :Any												= self.get_tokenizer()

							UpperCamelCase__   :Dict												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :List[str]												= self.prepare_image_inputs()
							UpperCamelCase__   :Optional[int]												= self.prepare_image_inputs()

							UpperCamelCase__   :List[Any]												= processor(images=UpperCamelCase_    ,   visual_prompt=UpperCamelCase_							)

							self.assertListEqual(list(inputs.keys()							)    ,   ['''pixel_values''', '''conditional_pixel_values''']							)

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




		def     lowerCAmelCase__				(		self							):

							'''simple docstring'''


							UpperCamelCase__   :Dict												= self.get_image_processor()
							UpperCamelCase__   :Optional[Any]												= self.get_tokenizer()

							UpperCamelCase__   :Optional[int]												= CLIPSegProcessor(tokenizer=UpperCamelCase_    ,   image_processor=UpperCamelCase_							)

							UpperCamelCase__   :Union[str, Any]												= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							UpperCamelCase__   :Union[str, Any]												= processor.batch_decode(UpperCamelCase_							)
							UpperCamelCase__   :Dict												= tokenizer.batch_decode(UpperCamelCase_							)

							self.assertListEqual(UpperCamelCase_    ,   UpperCamelCase_							)



'''simple docstring'''
from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


__snake_case							      =     logging.get_logger(__name__)

__snake_case							      =     {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__snake_case							      =     {
    '''vocab_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''facebook/blenderbot_small-90M''': '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'''
    },
    '''tokenizer_config_file''': {
        '''facebook/blenderbot_small-90M''': (
            '''https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'''
        )
    },
}

__snake_case							      =     {
    '''facebook/blenderbot_small-90M''': 512,
}
class    lowercase	(							A__					):

		"""simple docstring"""

		_a     =				VOCAB_FILES_NAMES
		_a     =				PRETRAINED_VOCAB_FILES_MAP
		_a     =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_a     =				BlenderbotSmallTokenizer




		def __init__(		self    ,   UpperCamelCase_=None    ,   UpperCamelCase_=None    ,   UpperCamelCase_="<|endoftext|>"    ,   UpperCamelCase_="<|endoftext|>"    ,   UpperCamelCase_="<|endoftext|>"    ,   UpperCamelCase_=False    ,   UpperCamelCase_=True    ,   **UpperCamelCase_    ,   ):

							'''simple docstring'''


							super().__init__(
							    ByteLevelBPETokenizer(
							        vocab=UpperCamelCase_    ,   merges=UpperCamelCase_    ,   add_prefix_space=UpperCamelCase_    ,   trim_offsets=UpperCamelCase_    ,   )    ,   bos_token=UpperCamelCase_    ,   eos_token=UpperCamelCase_    ,   unk_token=UpperCamelCase_    ,   **UpperCamelCase_    ,   )
							UpperCamelCase__   :Union[str, Any]												= add_prefix_space




		def     lowerCAmelCase__				(		self    ,   UpperCamelCase_    ,   UpperCamelCase_=None							):

							'''simple docstring'''


							UpperCamelCase__   :List[Any]												= [self.bos_token_id] + token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
												return output

							return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




		def     lowerCAmelCase__				(		self    ,   UpperCamelCase_    ,   UpperCamelCase_ = None							):

							'''simple docstring'''


							UpperCamelCase__   :Optional[int]												= [self.sep_token_id]
							UpperCamelCase__   :Any												= [self.cls_token_id]

							if token_ids_a is None:
												return len(cls + token_ids_a + sep							) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep							) * [0]