import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class     _A   (    __snake_case	, unittest.TestCase							):

  '''simple docstring'''





  SCREAMING_SNAKE_CASE_	:	Any						=MgpstrTokenizer
  SCREAMING_SNAKE_CASE_	:	List[str]						=False
  SCREAMING_SNAKE_CASE_	:	int						={}
  SCREAMING_SNAKE_CASE_	:	List[str]						=False






  def 		_a					(self	)		->      Dict:





       '''simple docstring'''





       super().setUp()

       # fmt: off
       UpperCamelCase__										=      ["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
       # fmt: on
       UpperCamelCase__										=      dict(zip(_lowercase   ,				range(len(_lowercase	)	)	)	)

       UpperCamelCase__										=      os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''vocab_file''']	)
       with open(self.vocab_file   ,				'''w'''   ,				encoding='''utf-8'''	) as fp:
            fp.write(json.dumps(_lowercase	) + '''\n'''	)






  def 		_a					(self   ,				**SCREAMING_SNAKE_CASE_	)		->      Tuple:





       '''simple docstring'''





       return MgpstrTokenizer.from_pretrained(self.tmpdirname   ,				**_lowercase	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      Dict:





       '''simple docstring'''





       UpperCamelCase__										=      """tester"""
       UpperCamelCase__										=      """tester"""
       return input_text, output_text






  @unittest.skip('''MGP-STR always lower cases letters.'''	)
  def 		_a					(self	)		->      Any:





       '''simple docstring'''





       pass






  def 		_a					(self	)		->      Optional[Any]:





       '''simple docstring'''





       UpperCamelCase__										=      self.get_tokenizers(do_lower_case=_lowercase	)
       for tokenizer in tokenizers:
            with self.subTest(F"{tokenizer.__class__.__name__}"	):
                 UpperCamelCase__										=      """[SPECIAL_TOKEN]"""

                 tokenizer.add_special_tokens({'''cls_token''': special_token}	)
                 UpperCamelCase__										=      tokenizer.encode([special_token]   ,				add_special_tokens=_lowercase	)
                 self.assertEqual(len(_lowercase	)   ,				1	)

                 UpperCamelCase__										=      tokenizer.decode(_lowercase   ,				skip_special_tokens=_lowercase	)
                 self.assertTrue(special_token not in decoded	)






  def 		_a					(self	)		->      str:





       '''simple docstring'''





       UpperCamelCase__										=      self.get_tokenizers()
       for tokenizer in tokenizers:
            with self.subTest(F"{tokenizer.__class__.__name__}"	):
                 UpperCamelCase__										=      self.get_input_output_texts(_lowercase	)

                 UpperCamelCase__										=      tokenizer.tokenize(_lowercase	)
                 UpperCamelCase__										=      tokenizer.convert_tokens_to_ids(_lowercase	)
                 UpperCamelCase__										=      tokenizer.encode(_lowercase   ,				add_special_tokens=_lowercase	)
                 self.assertListEqual(_lowercase   ,				_lowercase	)

                 UpperCamelCase__										=      tokenizer.convert_ids_to_tokens(_lowercase	)
                 self.assertNotEqual(len(_lowercase	)   ,				0	)
                 UpperCamelCase__										=      tokenizer.decode(_lowercase	)
                 self.assertIsInstance(_lowercase   ,				_lowercase	)

                 self.assertEqual(text_a.replace(''' '''   ,				''''''	)   ,				_lowercase	)






  @unittest.skip('''MGP-STR tokenizer only handles one sequence.'''	)
  def 		_a					(self	)		->      Optional[int]:





       '''simple docstring'''





       pass






  @unittest.skip('''inputs cannot be pretokenized in MgpstrTokenizer'''	)
  def 		_a					(self	)		->      Dict:





       '''simple docstring'''





       pass




import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


__magic_name__								=logging.get_logger(__name__)  # pylint: disable=invalid-name



class     _A   (    __UpperCamelCase							):






  def __init__(self   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_=768	)		->      Dict:





       '''simple docstring'''





       super().__init__(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      proj_size

       UpperCamelCase__										=      CLIPVisionModel(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      PaintByExampleMapper(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      nn.LayerNorm(config.hidden_size	)
       UpperCamelCase__										=      nn.Linear(config.hidden_size   ,				self.proj_size	)

       # uncondition for scaling
       UpperCamelCase__										=      nn.Parameter(torch.randn((1, 1, self.proj_size)	)	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_=False	)		->      List[str]:





       '''simple docstring'''





       UpperCamelCase__										=      self.model(pixel_values=SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      clip_output.pooler_output
       UpperCamelCase__										=      self.mapper(latent_states[:, None]	)
       UpperCamelCase__										=      self.final_layer_norm(SCREAMING_SNAKE_CASE_	)
       UpperCamelCase__										=      self.proj_out(SCREAMING_SNAKE_CASE_	)
       if return_uncond_vector:
            return latent_states, self.uncond_vector

       return latent_states



class     _A   (    nn.Module							):






  def __init__(self   ,				SCREAMING_SNAKE_CASE_	)		->      int:





       '''simple docstring'''





       super().__init__()
       UpperCamelCase__										=      (config.num_hidden_layers + 1) // 5
       UpperCamelCase__										=      config.hidden_size
       UpperCamelCase__										=      1
       UpperCamelCase__										=      nn.ModuleList(
           [
               BasicTransformerBlock(SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_   ,				SCREAMING_SNAKE_CASE_   ,				activation_fn='''gelu'''   ,				attention_bias=SCREAMING_SNAKE_CASE_	)
               for _ in range(SCREAMING_SNAKE_CASE_	)
           ]	)






  def 		_a					(self   ,				SCREAMING_SNAKE_CASE_	)		->      str:





       '''simple docstring'''





       for block in self.blocks:
            UpperCamelCase__										=      block(SCREAMING_SNAKE_CASE_	)

       return hidden_states



