


"""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 CLIPImageProcessor, CLIPProcessor
@require_vision
class 					__magic_name__		(			unittest.TestCase     ):






       def  __snake_case						(   self  :    Tuple				):

              '''simple docstring'''






              lowercase		:str       							=				tempfile.mkdtemp()

              # fmt: off
              lowercase		: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
              lowercase		:Optional[Any]       							=				dict(zip(snake_case__  ,     range(len(snake_case__				)				)				)				)
              lowercase		:Any       							=				['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
              lowercase		:Tuple       							=				{'''unk_token''': '''<unk>'''}

              lowercase		:List[Any]       							=				os.path.join(self.tmpdirname  ,     VOCAB_FILES_NAMES['''vocab_file''']				)
              lowercase		: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(snake_case__				) + '''\n'''				)
              with open(self.merges_file  ,     '''w'''  ,     encoding='''utf-8'''				) as fp:
                     fp.write('''\n'''.join(snake_case__				)				)

              lowercase		:Union[str, Any]       							=				{
                  '''do_resize''': True,
                  '''size''': 2_0,
                  '''do_center_crop''': True,
                  '''crop_size''': 1_8,
                  '''do_normalize''': True,
                  '''image_mean''': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
                  '''image_std''': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
              }
              lowercase		:Optional[int]       							=				os.path.join(self.tmpdirname  ,     snake_case__				)
              with open(self.image_processor_file  ,     '''w'''  ,     encoding='''utf-8'''				) as fp:
                     json.dump(snake_case__  ,     snake_case__				)






       def  __snake_case						(   self  :    Tuple  ,     **snake_case__  :    Union[str, Any]				):

              '''simple docstring'''






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






       def  __snake_case						(   self  :    int  ,     **snake_case__  :    Optional[Any]				):

              '''simple docstring'''






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






       def  __snake_case						(   self  :    Dict  ,     **snake_case__  :    List[Any]				):

              '''simple docstring'''






              return CLIPImageProcessor.from_pretrained(self.tmpdirname  ,     **snake_case__				)






       def  __snake_case						(   self  :    List[Any]				):

              '''simple docstring'''






              shutil.rmtree(self.tmpdirname				)






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






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

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

              return image_inputs






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:Union[str, Any]       							=				self.get_tokenizer()
              lowercase		:Dict       							=				self.get_rust_tokenizer()
              lowercase		:Any       							=				self.get_image_processor()

              lowercase		:str       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)
              processor_slow.save_pretrained(self.tmpdirname				)
              lowercase		:Optional[int]       							=				CLIPProcessor.from_pretrained(self.tmpdirname  ,     use_fast=snake_case__				)

              lowercase		:Any       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)
              processor_fast.save_pretrained(self.tmpdirname				)
              lowercase		:Tuple       							=				CLIPProcessor.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  ,     snake_case__				)
              self.assertIsInstance(processor_fast.tokenizer  ,     snake_case__				)

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






       def  __snake_case						(   self  :    List[str]				):

              '''simple docstring'''






              lowercase		:Tuple       							=				CLIPProcessor(tokenizer=self.get_tokenizer()  ,     image_processor=self.get_image_processor()				)
              processor.save_pretrained(self.tmpdirname				)

              lowercase		:Dict       							=				self.get_tokenizer(bos_token='''(BOS)'''  ,     eos_token='''(EOS)'''				)
              lowercase		:List[str]       							=				self.get_image_processor(do_normalize=snake_case__  ,     padding_value=1.0				)

              lowercase		:Union[str, Any]       							=				CLIPProcessor.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__				)






       def  __snake_case						(   self  :    str				):

              '''simple docstring'''






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

              lowercase		:str       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)

              lowercase		:Any       							=				self.prepare_image_inputs()

              lowercase		:Any       							=				image_processor(snake_case__  ,     return_tensors='''np'''				)
              lowercase		:int       							=				processor(images=snake_case__  ,     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  :    str				):

              '''simple docstring'''






              lowercase		:List[Any]       							=				self.get_image_processor()
              lowercase		:List[str]       							=				self.get_tokenizer()

              lowercase		:Optional[int]       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)

              lowercase		:Optional[Any]       							=				'''lower newer'''

              lowercase		:int       							=				processor(text=snake_case__				)

              lowercase		:List[str]       							=				tokenizer(snake_case__				)

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






       def  __snake_case						(   self  :    Optional[Any]				):

              '''simple docstring'''






              lowercase		:str       							=				self.get_image_processor()
              lowercase		:str       							=				self.get_tokenizer()

              lowercase		:Union[str, Any]       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)

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

              lowercase		:Any       							=				processor(text=snake_case__  ,     images=snake_case__				)

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

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






       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              lowercase		:Union[str, Any]       							=				self.get_image_processor()
              lowercase		:List[Any]       							=				self.get_tokenizer()

              lowercase		:List[Any]       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)

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

              lowercase		:int       							=				processor.batch_decode(snake_case__				)
              lowercase		:Any       							=				tokenizer.batch_decode(snake_case__				)

              self.assertListEqual(snake_case__  ,     snake_case__				)







       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






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

              lowercase		:List[Any]       							=				CLIPProcessor(tokenizer=snake_case__  ,     image_processor=snake_case__				)

              lowercase		:List[str]       							=				'''lower newer'''
              lowercase		:Tuple       							=				self.prepare_image_inputs()

              lowercase		:Any       							=				processor(text=snake_case__  ,     images=snake_case__				)

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










"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase      		=			logging.get_logger(__name__)

UpperCAmelCase      		=			{
    '''facebook/deit-base-distilled-patch16-224''': (
        '''https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json'''
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}
class 					__magic_name__		(			__UpperCAmelCase     ):
       __A			:      Tuple        =   "deit"






       def __init__(   self  :    List[str]  ,     snake_case__  :    int=7_6_8  ,     snake_case__  :    List[Any]=1_2  ,     snake_case__  :    Dict=1_2  ,     snake_case__  :    List[Any]=3_0_7_2  ,     snake_case__  :    Optional[int]="gelu"  ,     snake_case__  :    Dict=0.0  ,     snake_case__  :    str=0.0  ,     snake_case__  :    List[str]=0.02  ,     snake_case__  :    Optional[int]=1e-1_2  ,     snake_case__  :    Any=2_2_4  ,     snake_case__  :    Optional[int]=1_6  ,     snake_case__  :    int=3  ,     snake_case__  :    str=True  ,     snake_case__  :    Optional[int]=1_6  ,     **snake_case__  :    List[Any]  ,     ):

              '''simple docstring'''






              super().__init__(**snake_case__				)

              lowercase		:List[str]       							=				hidden_size
              lowercase		:Union[str, Any]       							=				num_hidden_layers
              lowercase		:Optional[Any]       							=				num_attention_heads
              lowercase		:Optional[Any]       							=				intermediate_size
              lowercase		:int       							=				hidden_act
              lowercase		:int       							=				hidden_dropout_prob
              lowercase		:Dict       							=				attention_probs_dropout_prob
              lowercase		:Optional[int]       							=				initializer_range
              lowercase		:Tuple       							=				layer_norm_eps
              lowercase		:Optional[int]       							=				image_size
              lowercase		:Union[str, Any]       							=				patch_size
              lowercase		:Optional[Any]       							=				num_channels
              lowercase		:Tuple       							=				qkv_bias
              lowercase		:Optional[Any]       							=				encoder_stride







class 					__magic_name__		(			__UpperCAmelCase     ):
       __A			:      Optional[int]        =   version.parse("1.11"     )






       @property
       def  __snake_case						(   self  :    int				):

              '''simple docstring'''






              return OrderedDict(
                  [
                      ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
                  ]				)







       @property
       def  __snake_case						(   self  :    Optional[int]				):

              '''simple docstring'''






              return 1e-4

