






"""simple docstring"""


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import AutoProcessor, BertTokenizer, CLIPImageProcessor, GitProcessor, PreTrainedTokenizerFast






@require_vision
class 						snake_case  (  unittest.TestCase       ):





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


      '''simple docstring'''




      a     :			Optional[Any]				=   tempfile.mkdtemp()

      a     :			Optional[Any]				=   CLIPImageProcessor()
      a     :			Optional[int]				=   BertTokenizer.from_pretrained(
          'hf-internal-testing/tiny-random-BertModel'				,		model_input_names=['input_ids', 'attention_mask']			)

      a     :			Any				=   GitProcessor(UpperCamelCase__				,		UpperCamelCase__			)

      processor.save_pretrained(self.tmpdirname			)





    def 				lowerCamelCase__      (							self	:					List[str]				,		**A	:					List[Any]			):


      '''simple docstring'''




      return AutoProcessor.from_pretrained(self.tmpdirname				,		**UpperCamelCase__			).tokenizer





    def 				lowerCamelCase__      (							self	:					Optional[int]				,		**A	:					Tuple			):


      '''simple docstring'''




      return AutoProcessor.from_pretrained(self.tmpdirname				,		**UpperCamelCase__			).image_processor





    def 				lowerCamelCase__      (							self	:					int			):


      '''simple docstring'''




      shutil.rmtree(self.tmpdirname			)





    def 				lowerCamelCase__      (							self	:					str			):


      '''simple docstring'''




      a     :			Optional[Any]				=   [np.random.randint(2_5_5				,		size=(3, 3_0, 4_0_0)				,		dtype=np.uinta			)]

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

      return image_inputs





    def 				lowerCamelCase__      (							self	:					List[Any]			):


      '''simple docstring'''




      a     :			List[str]				=   GitProcessor(tokenizer=self.get_tokenizer()				,		image_processor=self.get_image_processor()			)
      processor.save_pretrained(self.tmpdirname			)

      a     :			Union[str, Any]				=   self.get_tokenizer(bos_token='(BOS)'				,		eos_token='(EOS)'			)
      a     :			Optional[int]				=   self.get_image_processor(do_normalize=UpperCamelCase__				,		padding_value=1.0			)

      a     :			Union[str, Any]				=   GitProcessor.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	:					Optional[Any]			):


      '''simple docstring'''




      a     :			str				=   self.get_image_processor()
      a     :			Optional[int]				=   self.get_tokenizer()

      a     :			Optional[Any]				=   GitProcessor(tokenizer=UpperCamelCase__				,		image_processor=UpperCamelCase__			)

      a     :			Any				=   self.prepare_image_inputs()

      a     :			Optional[Any]				=   image_processor(UpperCamelCase__				,		return_tensors='np'			)
      a     :			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	:					List[str]			):


      '''simple docstring'''




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

      a     :			Optional[int]				=   GitProcessor(tokenizer=UpperCamelCase__				,		image_processor=UpperCamelCase__			)

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

      a     :			str				=   processor(text=UpperCamelCase__			)

      a     :			Optional[Any]				=   tokenizer(UpperCamelCase__				,		return_token_type_ids=UpperCamelCase__			)

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





    def 				lowerCamelCase__      (							self	:					int			):


      '''simple docstring'''




      a     :			List[Any]				=   self.get_image_processor()
      a     :			Tuple				=   self.get_tokenizer()

      a     :			Optional[Any]				=   GitProcessor(tokenizer=UpperCamelCase__				,		image_processor=UpperCamelCase__			)

      a     :			Dict				=   '''lower newer'''
      a     :			Any				=   self.prepare_image_inputs()

      a     :			str				=   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	:					Optional[Any]			):


      '''simple docstring'''




      a     :			Tuple				=   self.get_image_processor()
      a     :			Any				=   self.get_tokenizer()

      a     :			str				=   GitProcessor(tokenizer=UpperCamelCase__				,		image_processor=UpperCamelCase__			)

      a     :			int				=   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

      a     :			int				=   processor.batch_decode(UpperCamelCase__			)
      a     :			int				=   tokenizer.batch_decode(UpperCamelCase__			)

      self.assertListEqual(UpperCamelCase__				,		UpperCamelCase__			)





    def 				lowerCamelCase__      (							self	:					List[Any]			):


      '''simple docstring'''




      a     :			str				=   self.get_image_processor()
      a     :			Dict				=   self.get_tokenizer()

      a     :			Optional[Any]				=   GitProcessor(tokenizer=UpperCamelCase__				,		image_processor=UpperCamelCase__			)

      a     :			List[str]				=   '''lower newer'''
      a     :			Any				=   self.prepare_image_inputs()

      a     :			Tuple				=   processor(text=UpperCamelCase__				,		images=UpperCamelCase__			)

      # For now the processor supports only ['input_ids', 'attention_mask', 'pixel_values']
      self.assertListEqual(list(inputs.keys()			)				,		['input_ids', 'attention_mask', 'pixel_values']			)






'''simple docstring'''
import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase






@require_tokenizers
class      snake_case__    (	unittest.TestCase ):







		"""simple docstring"""

		lowerCamelCase							=		EsmTokenizer



		def 	lowerCAmelCase							(	self							:       List[Any]	)		->       Any:






				"""simple docstring"""







				super().setUp()
				snake_case   :    Optional[int]			       =		tempfile.mkdtemp()
				# fmt: off
				snake_case   :    List[str]			       =		["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
				# fmt: on
				snake_case   :    List[Any]			       =		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]	)	)



		def 	lowerCAmelCase							(	self							:       str   ,     **UpperCamelCase__							:       Union[str, Any]	)		->       List[PreTrainedTokenizerBase]:






				"""simple docstring"""







				return [self.get_tokenizer(**UpperCamelCase__	)]



		def 	lowerCAmelCase							(	self							:       Union[str, Any]   ,     **UpperCamelCase__							:       Tuple	)		->       PreTrainedTokenizer:






				"""simple docstring"""







				return self.tokenizer_class.from_pretrained(self.tmpdirname   ,     **UpperCamelCase__	)



		def 	lowerCAmelCase							(	self							:       List[str]	)		->       Tuple:






				"""simple docstring"""







				snake_case   :    str			       =		self.tokenizer_class(self.vocab_file	)

				snake_case   :    Optional[int]			       =		tokenizer.tokenize('''LAGVS'''	)
				self.assertListEqual(UpperCamelCase__   ,     ['''L''', '''A''', '''G''', '''V''', '''S''']	)
				self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase__	)   ,     [4, 5, 6, 7, 8]	)



		def 	lowerCAmelCase							(	self							:       List[Any]	)		->       int:






				"""simple docstring"""







				snake_case   :    Dict			       =		self.tokenizer_class(self.vocab_file	)

				snake_case   :    List[Any]			       =		'''LAGVS'''
				self.assertListEqual(tokenizer.encode(UpperCamelCase__	)   ,     [0, 4, 5, 6, 7, 8, 2]	)



		def 	lowerCAmelCase							(	self							:       List[str]	)		->       int:






				"""simple docstring"""







				snake_case   :    Union[str, Any]			       =		self.tokenizer_class(self.vocab_file	)

				snake_case   :    int			       =		['''LAGVS''', '''WCB''']
				snake_case   :    List[str]			       =		tokenizer(UpperCamelCase__   ,     padding=UpperCamelCase__	)['''input_ids''']

				self.assertListEqual(UpperCamelCase__   ,     [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]	)



		def 	lowerCAmelCase							(	self							:       int	)		->       List[str]:






				"""simple docstring"""







				snake_case   :    Dict			       =		self.tokenizer_class(self.vocab_file	)

				snake_case   :    List[str]			       =		['''LAGVS''', '''WCB''']
				snake_case   :    Any			       =		tokenizer(UpperCamelCase__   ,     padding=UpperCamelCase__	)['''input_ids''']

				self.assertListEqual(UpperCamelCase__   ,     [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]	)



		def 	lowerCAmelCase							(	self							:       Any	)		->       int:






				"""simple docstring"""







				snake_case   :    List[str]			       =		self.get_tokenizers(fast=UpperCamelCase__	)
				for tokenizer in tokenizers:
						with self.subTest(f'{tokenizer.__class__.__name__}'	):
								snake_case   :    int			       =		'''<unk>'''
								snake_case   :    int			       =		'''<mask>'''

								snake_case   :    Any			       =		tokenizer.tokenize(UpperCamelCase__	)
								snake_case   :    Any			       =		tokenizer.tokenize(UpperCamelCase__	)

								self.assertEqual(len(UpperCamelCase__	)   ,     1	)
								self.assertEqual(len(UpperCamelCase__	)   ,     1	)
								self.assertEqual(token_a[0]   ,     UpperCamelCase__	)
								self.assertEqual(token_a[0]   ,     UpperCamelCase__	)


