


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
       from PIL import Image

       from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor





@require_vision
class  lowerCAmelCase__(    unittest.TestCase						):






    '''simple docstring'''





    def 					_lowerCamelCase (	self				:   str	):





       '''simple docstring'''
       UpperCAmelCase_							:      int						=   tempfile.mkdtemp()

       UpperCAmelCase_							:      Dict						=   [
           '''[UNK]''',
           '''[CLS]''',
           '''[SEP]''',
           '''[PAD]''',
           '''[MASK]''',
           '''的''',
           '''价''',
           '''格''',
           '''是''',
           '''15''',
           '''便''',
           '''alex''',
           '''##andra''',
           '''，''',
           '''。''',
           '''-''',
           '''t''',
           '''shirt''',
       ]
       UpperCAmelCase_							:      Tuple						=   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]	)	)

       UpperCAmelCase_							:      Dict						=   {
           '''do_resize''': True,
           '''size''': {'''height''': 224, '''width''': 224},
           '''do_center_crop''': True,
           '''crop_size''': {'''height''': 18, '''width''': 18},
           '''do_normalize''': True,
           '''image_mean''': [0.48_145_466, 0.4_578_275, 0.40_821_073],
           '''image_std''': [0.26_862_954, 0.26_130_258, 0.27_577_711],
           '''do_convert_rgb''': True,
       }
       UpperCAmelCase_							:      List[str]						=   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				:   Tuple       ,   **__snake_case				:   Any	):





       '''simple docstring'''
       return BertTokenizer.from_pretrained(self.tmpdirname       ,   **__UpperCamelCase	)





    def 					_lowerCamelCase (	self				:   str       ,   **__snake_case				:   str	):





       '''simple docstring'''
       return BertTokenizerFast.from_pretrained(self.tmpdirname       ,   **__UpperCamelCase	)





    def 					_lowerCamelCase (	self				:   str       ,   **__snake_case				:   Any	):





       '''simple docstring'''
       return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname       ,   **__UpperCamelCase	)





    def 					_lowerCamelCase (	self				:   Optional[int]	):





       '''simple docstring'''
       shutil.rmtree(self.tmpdirname	)





    def 					_lowerCamelCase (	self				:   str	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   [np.random.randint(255       ,   size=(3, 30, 400)       ,   dtype=np.uinta	)]

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

       return image_inputs





    def 					_lowerCamelCase (	self				:   Tuple	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[Any]						=   self.get_tokenizer()
       UpperCAmelCase_							:      Dict						=   self.get_rust_tokenizer()
       UpperCAmelCase_							:      Dict						=   self.get_image_processor()

       UpperCAmelCase_							:      Tuple						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)
       processor_slow.save_pretrained(self.tmpdirname	)
       UpperCAmelCase_							:      Union[str, Any]						=   ChineseCLIPProcessor.from_pretrained(self.tmpdirname       ,   use_fast=__UpperCamelCase	)

       UpperCAmelCase_							:      Optional[int]						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)
       processor_fast.save_pretrained(self.tmpdirname	)
       UpperCAmelCase_							:      Optional[int]						=   ChineseCLIPProcessor.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				:   str	):





       '''simple docstring'''
       UpperCAmelCase_							:      Dict						=   ChineseCLIPProcessor(tokenizer=self.get_tokenizer()       ,   image_processor=self.get_image_processor()	)
       processor.save_pretrained(self.tmpdirname	)

       UpperCAmelCase_							:      Optional[int]						=   self.get_tokenizer(cls_token='''(CLS)'''       ,   sep_token='''(SEP)'''	)
       UpperCAmelCase_							:      Optional[int]						=   self.get_image_processor(do_normalize=__UpperCamelCase	)

       UpperCAmelCase_							:      Any						=   ChineseCLIPProcessor.from_pretrained(
           self.tmpdirname       ,   cls_token='''(CLS)'''       ,   sep_token='''(SEP)'''       ,   do_normalize=__UpperCamelCase	)

       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				:   str	):





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

       UpperCAmelCase_							:      List[str]						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)

       UpperCAmelCase_							:      str						=   self.prepare_image_inputs()

       UpperCAmelCase_							:      int						=   image_processor(__UpperCamelCase       ,   return_tensors='''np'''	)
       UpperCAmelCase_							:      List[str]						=   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				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      str						=   self.get_image_processor()
       UpperCAmelCase_							:      Any						=   self.get_tokenizer()

       UpperCAmelCase_							:      str						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)

       UpperCAmelCase_							:      int						=   '''Alexandra，T-shirt的价格是15便士。'''

       UpperCAmelCase_							:      Optional[Any]						=   processor(text=__UpperCamelCase	)

       UpperCAmelCase_							:      Any						=   tokenizer(__UpperCamelCase	)

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





    def 					_lowerCamelCase (	self				:   Any	):





       '''simple docstring'''
       UpperCAmelCase_							:      List[Any]						=   self.get_image_processor()
       UpperCAmelCase_							:      Dict						=   self.get_tokenizer()

       UpperCAmelCase_							:      List[Any]						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)

       UpperCAmelCase_							:      Optional[int]						=   '''Alexandra，T-shirt的价格是15便士。'''
       UpperCAmelCase_							:      Optional[int]						=   self.prepare_image_inputs()

       UpperCAmelCase_							:      List[str]						=   processor(text=__UpperCamelCase       ,   images=__UpperCamelCase	)

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

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





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





       '''simple docstring'''
       UpperCAmelCase_							:      List[Any]						=   self.get_image_processor()
       UpperCAmelCase_							:      str						=   self.get_tokenizer()

       UpperCAmelCase_							:      Union[str, Any]						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)

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

       UpperCAmelCase_							:      Union[str, Any]						=   processor.batch_decode(__UpperCamelCase	)
       UpperCAmelCase_							:      List[Any]						=   tokenizer.batch_decode(__UpperCamelCase	)

       self.assertListEqual(__UpperCamelCase       ,   __UpperCamelCase	)





    def 					_lowerCamelCase (	self				:   Any	):





       '''simple docstring'''
       UpperCAmelCase_							:      Dict						=   self.get_image_processor()
       UpperCAmelCase_							:      Optional[Any]						=   self.get_tokenizer()

       UpperCAmelCase_							:      Any						=   ChineseCLIPProcessor(tokenizer=__UpperCamelCase       ,   image_processor=__UpperCamelCase	)

       UpperCAmelCase_							:      Optional[Any]						=   '''Alexandra，T-shirt的价格是15便士。'''
       UpperCAmelCase_							:      int						=   self.prepare_image_inputs()

       UpperCAmelCase_							:      int						=   processor(text=__UpperCamelCase       ,   images=__UpperCamelCase	)

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






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase				:  Any      					=							logging.get_logger(__name__)

__UpperCamelCase				:  Dict      					=							{
    'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    A_  :     List[str]			= 'gpt_bigcode'
    A_  :     Optional[Any]			= ['past_key_values']
    A_  :     Optional[int]			= {
        'hidden_size': 'n_embd',
        'max_position_embeddings': 'n_positions',
        'num_attention_heads': 'n_head',
        'num_hidden_layers': 'n_layer',
    }





    def __init__(	self				:   int       ,   __snake_case				:   Dict=50_257       ,   __snake_case				:   List[str]=1_024       ,   __snake_case				:   Dict=768       ,   __snake_case				:   Optional[int]=12       ,   __snake_case				:   str=12       ,   __snake_case				:   List[str]=None       ,   __snake_case				:   List[str]="gelu_pytorch_tanh"       ,   __snake_case				:   Optional[Any]=0.1       ,   __snake_case				:   str=0.1       ,   __snake_case				:   Optional[Any]=0.1       ,   __snake_case				:   List[str]=1E-5       ,   __snake_case				:   Dict=0.02       ,   __snake_case				:   Optional[int]=True       ,   __snake_case				:   Tuple=True       ,   __snake_case				:   Optional[Any]=50_256       ,   __snake_case				:   Optional[Any]=50_256       ,   __snake_case				:   Optional[Any]=True       ,   __snake_case				:   Optional[Any]=True       ,   __snake_case				:   List[Any]=True       ,   **__snake_case				:   List[str]       ,   ):





       '''simple docstring'''
       UpperCAmelCase_							:      Any						=   vocab_size
       UpperCAmelCase_							:      int						=   n_positions
       UpperCAmelCase_							:      Any						=   n_embd
       UpperCAmelCase_							:      Union[str, Any]						=   n_layer
       UpperCAmelCase_							:      List[str]						=   n_head
       UpperCAmelCase_							:      List[Any]						=   n_inner
       UpperCAmelCase_							:      Optional[int]						=   activation_function
       UpperCAmelCase_							:      str						=   resid_pdrop
       UpperCAmelCase_							:      Optional[Any]						=   embd_pdrop
       UpperCAmelCase_							:      str						=   attn_pdrop
       UpperCAmelCase_							:      Any						=   layer_norm_epsilon
       UpperCAmelCase_							:      List[str]						=   initializer_range
       UpperCAmelCase_							:      Optional[int]						=   scale_attn_weights
       UpperCAmelCase_							:      Union[str, Any]						=   use_cache
       UpperCAmelCase_							:      Dict						=   attention_softmax_in_fpaa
       UpperCAmelCase_							:      Union[str, Any]						=   scale_attention_softmax_in_fpaa
       UpperCAmelCase_							:      Optional[int]						=   multi_query

       UpperCAmelCase_							:      Optional[Any]						=   bos_token_id
       UpperCAmelCase_							:      Tuple						=   eos_token_id

       super().__init__(bos_token_id=__snake_case       ,   eos_token_id=__snake_case       ,   **__snake_case	)