






"""simple docstring"""







import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin


class    __UpperCAmelCase(       SCREAMING_SNAKE_CASE__  ,  unittest.TestCase							):




						"""simple docstring"""




						__lowerCamelCase    	= BioGptTokenizer
						__lowerCamelCase    	= False




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												lowercase__    :				Any=	[
												    "l",
												    "o",
												    "w",
												    "e",
												    "r",
												    "s",
												    "t",
												    "i",
												    "d",
												    "n",
												    "w</w>",
												    "r</w>",
												    "t</w>",
												    "lo",
												    "low",
												    "er</w>",
												    "low</w>",
												    "lowest</w>",
												    "newer</w>",
												    "wider</w>",
												    "<unk>",
												]
												lowercase__    :				List[str]=	dict(zip(snake_case__	,  range(len(snake_case__      )      )      )      )
												lowercase__    :				Tuple=	["l o 123", "lo w 1456", "e r</w> 1789", ""]

												lowercase__    :				Dict=	os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["vocab_file"]      )
												lowercase__    :				Union[str, Any]=	os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["merges_file"]      )
												with open(self.vocab_file	,  "w"      ) as fp:
																		fp.write(json.dumps(snake_case__      )      )
												with open(self.merges_file	,  "w"      ) as fp:
																		fp.write("\n".join(snake_case__      )      )




						def 		UpperCAmelCase_	(       self	,  snake_case__      ):
												'''simple docstring'''
												lowercase__    :				int=	"lower newer"
												lowercase__    :				Tuple=	"lower newer"
												return input_text, output_text




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	BioGptTokenizer(self.vocab_file	,  self.merges_file      )

												lowercase__    :				str=	"lower"
												lowercase__    :				Optional[Any]=	["low", "er</w>"]
												lowercase__    :				Dict=	tokenizer.tokenize(snake_case__      )
												self.assertListEqual(snake_case__	,  snake_case__      )

												lowercase__    :				Any=	tokens + ["<unk>"]
												lowercase__    :				Any=	[14, 15, 20]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__      )	,  snake_case__      )




						@slow
						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	BioGptTokenizer.from_pretrained("microsoft/biogpt"      )

												lowercase__    :				List[str]=	tokenizer.encode("sequence builders"	,  add_special_tokens=snake_case__      )
												lowercase__    :				Optional[Any]=	tokenizer.encode("multi-sequence build"	,  add_special_tokens=snake_case__      )

												lowercase__    :				Dict=	tokenizer.build_inputs_with_special_tokens(snake_case__      )
												lowercase__    :				Tuple=	tokenizer.build_inputs_with_special_tokens(snake_case__	,  snake_case__      )

												self.assertTrue(encoded_sentence == [2] + text      )
												self.assertTrue(encoded_pair == [2] + text + [2] + text_a      )














"""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,
			    BertTokenizerFast,
			    BlipImageProcessor,
			    GPTaTokenizer,
			    InstructBlipProcessor,
			    PreTrainedTokenizerFast,
			)


@require_vision
class    __UpperCAmelCase(       unittest.TestCase							):




						"""simple docstring"""




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[str]=	tempfile.mkdtemp()

												lowercase__    :				Union[str, Any]=	BlipImageProcessor()
												lowercase__    :				Any=	GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model"      )
												lowercase__    :				Any=	BertTokenizerFast.from_pretrained("hf-internal-testing/tiny-random-bert"      )

												lowercase__    :				str=	InstructBlipProcessor(snake_case__	,  snake_case__	,  snake_case__      )

												processor.save_pretrained(self.tmpdirname      )




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return AutoProcessor.from_pretrained(self.tmpdirname	,  **snake_case__      ).tokenizer




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return AutoProcessor.from_pretrained(self.tmpdirname	,  **snake_case__      ).image_processor




						def 		UpperCAmelCase_	(       self	,  **snake_case__      ):
												'''simple docstring'''
												return AutoProcessor.from_pretrained(self.tmpdirname	,  **snake_case__      ).qformer_tokenizer




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												shutil.rmtree(self.tmpdirname      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Union[str, Any]=	[np.random.randint(255	,  size=(3, 30, 400)	,  dtype=np.uinta      )]

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

												return image_inputs




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	InstructBlipProcessor(
												    tokenizer=self.get_tokenizer()	,  image_processor=self.get_image_processor()	,  qformer_tokenizer=self.get_qformer_tokenizer()	,  )
												processor.save_pretrained(self.tmpdirname      )

												lowercase__    :				Optional[Any]=	self.get_tokenizer(bos_token="(BOS)"	,  eos_token="(EOS)"      )
												lowercase__    :				Optional[Any]=	self.get_image_processor(do_normalize=snake_case__	,  padding_value=1.0      )

												lowercase__    :				Optional[Any]=	InstructBlipProcessor.from_pretrained(
												    self.tmpdirname	,  bos_token="(BOS)"	,  eos_token="(EOS)"	,  do_normalize=snake_case__	,  padding_value=1.0      )

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

												self.assertEqual(processor.image_processor.to_json_string()	,  image_processor_add_kwargs.to_json_string()      )
												self.assertIsInstance(processor.image_processor	,  snake_case__      )
												self.assertIsInstance(processor.qformer_tokenizer	,  snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Tuple=	self.get_image_processor()
												lowercase__    :				Optional[int]=	self.get_tokenizer()
												lowercase__    :				Any=	self.get_qformer_tokenizer()

												lowercase__    :				Any=	InstructBlipProcessor(
												    tokenizer=snake_case__	,  image_processor=snake_case__	,  qformer_tokenizer=snake_case__      )

												lowercase__    :				Tuple=	self.prepare_image_inputs()

												lowercase__    :				int=	image_processor(snake_case__	,  return_tensors="np"      )
												lowercase__    :				List[str]=	processor(images=snake_case__	,  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 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				List[Any]=	self.get_image_processor()
												lowercase__    :				List[str]=	self.get_tokenizer()
												lowercase__    :				Optional[Any]=	self.get_qformer_tokenizer()

												lowercase__    :				Optional[Any]=	InstructBlipProcessor(
												    tokenizer=snake_case__	,  image_processor=snake_case__	,  qformer_tokenizer=snake_case__      )

												lowercase__    :				Optional[Any]=	"lower newer"

												lowercase__    :				Any=	processor(text=snake_case__      )

												lowercase__    :				Union[str, Any]=	tokenizer(snake_case__	,  return_token_type_ids=snake_case__      )
												lowercase__    :				List[Any]=	qformer_tokenizer(snake_case__	,  return_token_type_ids=snake_case__      )

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

												for key in encoded_tokens_qformer.keys():
																		self.assertListEqual(encoded_tokens_qformer[key]	,  encoded_processor["qformer_" + key]      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				int=	self.get_image_processor()
												lowercase__    :				Optional[int]=	self.get_tokenizer()
												lowercase__    :				Any=	self.get_qformer_tokenizer()

												lowercase__    :				Optional[int]=	InstructBlipProcessor(
												    tokenizer=snake_case__	,  image_processor=snake_case__	,  qformer_tokenizer=snake_case__      )

												lowercase__    :				List[str]=	"lower newer"
												lowercase__    :				Optional[int]=	self.prepare_image_inputs()

												lowercase__    :				Dict=	processor(text=snake_case__	,  images=snake_case__      )

												self.assertListEqual(
												    list(inputs.keys()      )	,  ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]	,  )

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




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				Optional[Any]=	self.get_image_processor()
												lowercase__    :				int=	self.get_tokenizer()
												lowercase__    :				Optional[int]=	self.get_qformer_tokenizer()

												lowercase__    :				Any=	InstructBlipProcessor(
												    tokenizer=snake_case__	,  image_processor=snake_case__	,  qformer_tokenizer=snake_case__      )

												lowercase__    :				Dict=	[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

												lowercase__    :				Optional[Any]=	processor.batch_decode(snake_case__      )
												lowercase__    :				List[Any]=	tokenizer.batch_decode(snake_case__      )

												self.assertListEqual(snake_case__	,  snake_case__      )




						def 		UpperCAmelCase_	(       self      ):
												'''simple docstring'''
												lowercase__    :				str=	self.get_image_processor()
												lowercase__    :				Optional[int]=	self.get_tokenizer()
												lowercase__    :				Optional[Any]=	self.get_qformer_tokenizer()

												lowercase__    :				int=	InstructBlipProcessor(
												    tokenizer=snake_case__	,  image_processor=snake_case__	,  qformer_tokenizer=snake_case__      )

												lowercase__    :				Union[str, Any]=	"lower newer"
												lowercase__    :				int=	self.prepare_image_inputs()

												lowercase__    :				Dict=	processor(text=snake_case__	,  images=snake_case__      )

												self.assertListEqual(
												    list(inputs.keys()      )	,  ["input_ids", "attention_mask", "qformer_input_ids", "qformer_attention_mask", "pixel_values"]	,  )






