


import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput
@dataclass
class      UpperCAmelCase_ ( UpperCamelCase   ):

   '''simple docstring'''




   __A			:				float
   __A			:				Optional[float]							=		None
   __A			:				Optional[float]							=		None



class      UpperCAmelCase_ ( unittest.TestCase   ):

   '''simple docstring'''




   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[str]   =    ModelOutputTest(a=30			)
     self.assertEqual(x.a						,    30			)
     self.assertIsNone(x.b			)
     self.assertIsNone(x.c			)
     with self.assertRaises(__A			):
       lowerCamelCase			: Tuple   =    x.d






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[Any]   =    ModelOutputTest(a=30						,    b=10			)
     self.assertEqual(x[0]						,    30			)
     self.assertEqual(x[1]						,    10			)
     self.assertEqual(x[:2]						,    (30, 10)			)
     self.assertEqual(x[:]						,    (30, 10)			)

     lowerCamelCase			: Dict   =    ModelOutputTest(a=30						,    c=10			)
     self.assertEqual(x[0]						,    30			)
     self.assertEqual(x[1]						,    10			)
     self.assertEqual(x[:2]						,    (30, 10)			)
     self.assertEqual(x[:]						,    (30, 10)			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[str]   =    ModelOutputTest(a=30						,    b=10			)
     self.assertEqual(x["a"]						,    30			)
     self.assertEqual(x["b"]						,    10			)
     with self.assertRaises(__A			):
       lowerCamelCase			: Optional[int]   =    x["c"]

     lowerCamelCase			: Dict   =    ModelOutputTest(a=30						,    c=10			)
     self.assertEqual(x["a"]						,    30			)
     self.assertEqual(x["c"]						,    10			)
     with self.assertRaises(__A			):
       lowerCamelCase			: List[Any]   =    x["b"]






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[str]   =    ModelOutputTest(a=30			)
     self.assertEqual(list(x.keys()			)						,    ["a"]			)
     self.assertEqual(list(x.values()			)						,    [30]			)
     self.assertEqual(list(x.items()			)						,    [("a", 30)]			)
     self.assertEqual(list(__A			)						,    ["a"]			)

     lowerCamelCase			: Any   =    ModelOutputTest(a=30						,    b=10			)
     self.assertEqual(list(x.keys()			)						,    ["a", "b"]			)
     self.assertEqual(list(x.values()			)						,    [30, 10]			)
     self.assertEqual(list(x.items()			)						,    [("a", 30), ("b", 10)]			)
     self.assertEqual(list(__A			)						,    ["a", "b"]			)

     lowerCamelCase			: Optional[int]   =    ModelOutputTest(a=30						,    c=10			)
     self.assertEqual(list(x.keys()			)						,    ["a", "c"]			)
     self.assertEqual(list(x.values()			)						,    [30, 10]			)
     self.assertEqual(list(x.items()			)						,    [("a", 30), ("c", 10)]			)
     self.assertEqual(list(__A			)						,    ["a", "c"]			)

     with self.assertRaises(__A			):
       lowerCamelCase			: List[Any]   =    x.update({"d": 20}			)
     with self.assertRaises(__A			):
       del x["a"]
     with self.assertRaises(__A			):
       lowerCamelCase			: Optional[Any]   =    x.pop("a"			)
     with self.assertRaises(__A			):
       lowerCamelCase			: Any   =    x.setdefault("d"						,    32			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Optional[int]   =    ModelOutputTest(a=30			)
     lowerCamelCase			: Tuple   =    10
     self.assertEqual(x.a						,    10			)
     self.assertEqual(x["a"]						,    10			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Any   =    ModelOutputTest(a=30			)
     lowerCamelCase			: Dict   =    10
     self.assertEqual(x.a						,    10			)
     self.assertEqual(x["a"]						,    10			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: int   =    ModelOutputTest({"a": 30, "b": 10}			)
     self.assertEqual(list(x.keys()			)						,    ["a", "b"]			)
     self.assertEqual(x.a						,    30			)
     self.assertEqual(x.b						,    10			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Optional[int]   =    ModelOutputTest([("a", 30), ("b", 10)]			)
     self.assertEqual(list(x.keys()			)						,    ["a", "b"]			)
     self.assertEqual(x.a						,    30			)
     self.assertEqual(x.b						,    10			)

     with self.assertRaises(__A			):
       lowerCamelCase			: str   =    ModelOutputTest([("a", 30), (10, 10)]			)

     lowerCamelCase			: Optional[Any]   =    ModelOutputTest(a=(30, 30)			)
     self.assertEqual(list(x.keys()			)						,    ["a"]			)
     self.assertEqual(x.a						,    (30, 30)			)







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      UpperCAmelCase_ ( unittest.TestCase   ):

   '''simple docstring'''




   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Tuple   =    tempfile.mkdtemp()

     lowerCamelCase			: List[Any]   =    CLIPImageProcessor()
     lowerCamelCase			: str   =    BertTokenizer.from_pretrained(
         "hf-internal-testing/tiny-random-BertModel"						,    model_input_names=["input_ids", "attention_mask"]			)

     lowerCamelCase			: List[str]   =    GitProcessor(__A						,    __A			)

     processor.save_pretrained(self.tmpdirname			)






   def _snake_case   (		self						,    **__A			):






     """simple docstring"""





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






   def _snake_case   (		self						,    **__A			):






     """simple docstring"""





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






   def _snake_case   (		self			):






     """simple docstring"""





     shutil.rmtree(self.tmpdirname			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: str   =    [np.random.randint(255						,    size=(3, 30, 400)						,    dtype=np.uinta			)]

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

     return image_inputs






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Tuple   =    GitProcessor(tokenizer=self.get_tokenizer()						,    image_processor=self.get_image_processor()			)
     processor.save_pretrained(self.tmpdirname			)

     lowerCamelCase			: Optional[Any]   =    self.get_tokenizer(bos_token="(BOS)"						,    eos_token="(EOS)"			)
     lowerCamelCase			: List[str]   =    self.get_image_processor(do_normalize=__A						,    padding_value=1.0			)

     lowerCamelCase			: Dict   =    GitProcessor.from_pretrained(
         self.tmpdirname						,    bos_token="(BOS)"						,    eos_token="(EOS)"						,    do_normalize=__A						,    padding_value=1.0			)

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

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






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Any   =    self.get_image_processor()
     lowerCamelCase			: Optional[int]   =    self.get_tokenizer()

     lowerCamelCase			: Optional[Any]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: List[str]   =    self.prepare_image_inputs()

     lowerCamelCase			: str   =    image_processor(__A						,    return_tensors="np"			)
     lowerCamelCase			: Union[str, Any]   =    processor(images=__A						,    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 _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: int   =    self.get_image_processor()
     lowerCamelCase			: Dict   =    self.get_tokenizer()

     lowerCamelCase			: Optional[int]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: int   =    "lower newer"

     lowerCamelCase			: str   =    processor(text=__A			)

     lowerCamelCase			: Union[str, Any]   =    tokenizer(__A						,    return_token_type_ids=__A			)

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






   def _snake_case   (		self			):






     """simple docstring"""





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

     lowerCamelCase			: List[str]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: str   =    "lower newer"
     lowerCamelCase			: Tuple   =    self.prepare_image_inputs()

     lowerCamelCase			: str   =    processor(text=__A						,    images=__A			)

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

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






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: Union[str, Any]   =    self.get_image_processor()
     lowerCamelCase			: Tuple   =    self.get_tokenizer()

     lowerCamelCase			: Tuple   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: Optional[Any]   =    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

     lowerCamelCase			: str   =    processor.batch_decode(__A			)
     lowerCamelCase			: int   =    tokenizer.batch_decode(__A			)

     self.assertListEqual(__A						,    __A			)






   def _snake_case   (		self			):






     """simple docstring"""





     lowerCamelCase			: List[Any]   =    self.get_image_processor()
     lowerCamelCase			: int   =    self.get_tokenizer()

     lowerCamelCase			: Optional[int]   =    GitProcessor(tokenizer=__A						,    image_processor=__A			)

     lowerCamelCase			: Optional[Any]   =    "lower newer"
     lowerCamelCase			: List[Any]   =    self.prepare_image_inputs()

     lowerCamelCase			: Optional[int]   =    processor(text=__A						,    images=__A			)

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



