





'''simple docstring'''

from dataclasses import asdict, dataclass
from typing import Optional

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


a   	=    logging.get_logger(__name__)

# TODO Update this
a   	=    {
    "facebook/esm-1b": "https://huggingface.co/facebook/esm-1b/resolve/main/config.json",
    # See all ESM models at https://huggingface.co/models?filter=esm
}







class __a			( _snake_case      ):
   __UpperCamelCase :			str						   =						'esm'





   def __init__(       self					:      Tuple					,lowerCamelCase					:      List[Any]=None					,lowerCamelCase					:      str=None					,lowerCamelCase					:      Any=None					,lowerCamelCase					:      Union[str, Any]=768					,lowerCamelCase					:      Tuple=12					,lowerCamelCase					:      int=12					,lowerCamelCase					:      Optional[int]=3072					,lowerCamelCase					:      List[Any]=0.1					,lowerCamelCase					:      Optional[int]=0.1					,lowerCamelCase					:      Any=1026					,lowerCamelCase					:      str=0.02					,lowerCamelCase					:      int=1E-1_2					,lowerCamelCase					:      Union[str, Any]="absolute"					,lowerCamelCase					:      Optional[Any]=True					,lowerCamelCase					:      str=None					,lowerCamelCase					:      Optional[int]=False					,lowerCamelCase					:      int=False					,lowerCamelCase					:      Union[str, Any]=None					,lowerCamelCase					:      Any=None					,**lowerCamelCase					:      Any					,):

      '''simple docstring'''

      super().__init__(pad_token_id=lowerCamelCase					,mask_token_id=lowerCamelCase					,**lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							vocab_size
      __SCREAMING_SNAKE_CASE   				=							hidden_size
      __SCREAMING_SNAKE_CASE   				=							num_hidden_layers
      __SCREAMING_SNAKE_CASE   				=							num_attention_heads
      __SCREAMING_SNAKE_CASE   				=							intermediate_size
      __SCREAMING_SNAKE_CASE   				=							hidden_dropout_prob
      __SCREAMING_SNAKE_CASE   				=							attention_probs_dropout_prob
      __SCREAMING_SNAKE_CASE   				=							max_position_embeddings
      __SCREAMING_SNAKE_CASE   				=							initializer_range
      __SCREAMING_SNAKE_CASE   				=							layer_norm_eps
      __SCREAMING_SNAKE_CASE   				=							position_embedding_type
      __SCREAMING_SNAKE_CASE   				=							use_cache
      __SCREAMING_SNAKE_CASE   				=							emb_layer_norm_before
      __SCREAMING_SNAKE_CASE   				=							token_dropout
      __SCREAMING_SNAKE_CASE   				=							is_folding_model
      if is_folding_model:
         if esmfold_config is None:
            logger.info("""No esmfold_config supplied for folding model, using default values."""     )
            __SCREAMING_SNAKE_CASE   				=							EsmFoldConfig()
         elif isinstance(lowerCamelCase					,lowerCamelCase     ):
            __SCREAMING_SNAKE_CASE   				=							EsmFoldConfig(**lowerCamelCase     )
         __SCREAMING_SNAKE_CASE   				=							esmfold_config
         if vocab_list is None:
            logger.warning("""No vocab_list supplied for folding model, assuming the ESM-2 vocabulary!"""     )
            __SCREAMING_SNAKE_CASE   				=							get_default_vocab_list()
         else:
            __SCREAMING_SNAKE_CASE   				=							vocab_list
      else:
         __SCREAMING_SNAKE_CASE   				=							None
         __SCREAMING_SNAKE_CASE   				=							None
      if self.esmfold_config is not None and getattr(self.esmfold_config					,"""use_esm_attn_map"""					,lowerCamelCase     ):
         raise ValueError("""The HuggingFace port of ESMFold does not support use_esm_attn_map at this time!"""     )





   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							super().to_dict()
      if isinstance(self.esmfold_config					,lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							self.esmfold_config.to_dict()
      return output







@dataclass
class __a			:
   __UpperCamelCase :			str						   =						None
   __UpperCamelCase :			bool						   =						True
   __UpperCamelCase :			bool						   =						False
   __UpperCamelCase :			bool						   =						False
   __UpperCamelCase :			bool						   =						False
   __UpperCamelCase :			float						   =						0

   __UpperCamelCase :			bool						   =						True
   __UpperCamelCase :			bool						   =						False

   __UpperCamelCase :			int						   =						128
   __UpperCamelCase :			"TrunkConfig"						   =						None





   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      if self.trunk is None:
         __SCREAMING_SNAKE_CASE   				=							TrunkConfig()
      elif isinstance(self.trunk					,lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							TrunkConfig(**self.trunk     )





   def   UpperCAmelCase__  (       self					:      Optional[int]     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							asdict(self     )
      __SCREAMING_SNAKE_CASE   				=							self.trunk.to_dict()
      return output







@dataclass
class __a			:
   __UpperCamelCase :			int						   =						48
   __UpperCamelCase :			int						   =						1024
   __UpperCamelCase :			int						   =						128
   __UpperCamelCase :			int						   =						32
   __UpperCamelCase :			int						   =						32
   __UpperCamelCase :			int						   =						32
   __UpperCamelCase :			float						   =						0
   __UpperCamelCase :			float						   =						0
   __UpperCamelCase :			bool						   =						False
   __UpperCamelCase :			int						   =						4
   __UpperCamelCase :			Optional[int]						   =						128
   __UpperCamelCase :			"StructureModuleConfig"						   =						None





   def   UpperCAmelCase__  (       self					:      List[Any]     ):

      '''simple docstring'''

      if self.structure_module is None:
         __SCREAMING_SNAKE_CASE   				=							StructureModuleConfig()
      elif isinstance(self.structure_module					,lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							StructureModuleConfig(**self.structure_module     )

      if self.max_recycles <= 0:
         raise ValueError(f"""`max_recycles` should be positive, got {self.max_recycles}."""     )
      if self.sequence_state_dim % self.sequence_state_dim != 0:
         raise ValueError(
             """`sequence_state_dim` should be a round multiple of `sequence_state_dim`, got"""
             f""" {self.sequence_state_dim} and {self.sequence_state_dim}."""     )
      if self.pairwise_state_dim % self.pairwise_state_dim != 0:
         raise ValueError(
             """`pairwise_state_dim` should be a round multiple of `pairwise_state_dim`, got"""
             f""" {self.pairwise_state_dim} and {self.pairwise_state_dim}."""     )

      __SCREAMING_SNAKE_CASE   				=							self.sequence_state_dim // self.sequence_head_width
      __SCREAMING_SNAKE_CASE   				=							self.pairwise_state_dim // self.pairwise_head_width

      if self.sequence_state_dim != sequence_num_heads * self.sequence_head_width:
         raise ValueError(
             """`sequence_state_dim` should be equal to `sequence_num_heads * sequence_head_width, got"""
             f""" {self.sequence_state_dim} != {sequence_num_heads} * {self.sequence_head_width}."""     )
      if self.pairwise_state_dim != pairwise_num_heads * self.pairwise_head_width:
         raise ValueError(
             """`pairwise_state_dim` should be equal to `pairwise_num_heads * pairwise_head_width, got"""
             f""" {self.pairwise_state_dim} != {pairwise_num_heads} * {self.pairwise_head_width}."""     )
      if self.pairwise_state_dim % 2 != 0:
         raise ValueError(f"""`pairwise_state_dim` should be even, got {self.pairwise_state_dim}."""     )

      if self.dropout >= 0.4:
         raise ValueError(f"""`dropout` should not be greater than 0.4, got {self.dropout}."""     )





   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							asdict(self     )
      __SCREAMING_SNAKE_CASE   				=							self.structure_module.to_dict()
      return output







@dataclass
class __a			:
   __UpperCamelCase :			int						   =						384
   __UpperCamelCase :			int						   =						128
   __UpperCamelCase :			int						   =						16
   __UpperCamelCase :			int						   =						128
   __UpperCamelCase :			int						   =						12
   __UpperCamelCase :			int						   =						4
   __UpperCamelCase :			int						   =						8
   __UpperCamelCase :			float						   =						0.1
   __UpperCamelCase :			int						   =						8
   __UpperCamelCase :			int						   =						1
   __UpperCamelCase :			int						   =						2
   __UpperCamelCase :			int						   =						7
   __UpperCamelCase :			int						   =						10
   __UpperCamelCase :			float						   =						1E-8
   __UpperCamelCase :			float						   =						1E5





   def   UpperCAmelCase__  (       self					:      List[Any]     ):

      '''simple docstring'''

      return asdict(self     )





def     __magic_name__							(				)    ->       Dict:

   '''simple docstring'''







   return (
       "<cls>",
       "<pad>",
       "<eos>",
       "<unk>",
       "L",
       "A",
       "G",
       "V",
       "S",
       "E",
       "R",
       "T",
       "I",
       "D",
       "P",
       "K",
       "Q",
       "N",
       "F",
       "Y",
       "M",
       "H",
       "W",
       "C",
       "X",
       "B",
       "U",
       "Z",
       "O",
       ".",
       "-",
       "<null_1>",
       "<mask>",
   )












'''simple docstring'''

import json
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
from transformers import (
    CONFIG_MAPPING,
    IMAGE_PROCESSOR_MAPPING,
    AutoConfig,
    AutoImageProcessor,
    CLIPConfig,
    CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER


sys.path.append(str(Path(__file__).parent.parent.parent.parent / "utils"))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_image_processing import CustomImageProcessor  # noqa E402







class __a			( unittest.TestCase      ):





   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							0





   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained("""openai/clip-vit-base-patch32"""     )
      self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      with tempfile.TemporaryDirectory() as tmpdirname:
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """preprocessor_config.json"""
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """config.json"""
         json.dump(
             {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}					,open(lowerCamelCase					,"""w"""     )					,)
         json.dump({"""model_type""": """clip"""}					,open(lowerCamelCase					,"""w"""     )     )

         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     )
         self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Optional[Any]     ):

      '''simple docstring'''

      with tempfile.TemporaryDirectory() as tmpdirname:
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """preprocessor_config.json"""
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """config.json"""
         json.dump(
             {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}					,open(lowerCamelCase					,"""w"""     )					,)
         json.dump({"""model_type""": """clip"""}					,open(lowerCamelCase					,"""w"""     )     )

         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     )
         self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      List[str]     ):

      '''simple docstring'''

      with tempfile.TemporaryDirectory() as tmpdirname:
         __SCREAMING_SNAKE_CASE   				=							CLIPConfig()

         # Create a dummy config file with image_proceesor_type
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """preprocessor_config.json"""
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """config.json"""
         json.dump(
             {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}					,open(lowerCamelCase					,"""w"""     )					,)
         json.dump({"""model_type""": """clip"""}					,open(lowerCamelCase					,"""w"""     )     )

         # remove image_processor_type to make sure config.json alone is enough to load image processor locally
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     ).to_dict()

         config_dict.pop("""image_processor_type"""     )
         __SCREAMING_SNAKE_CASE   				=							CLIPImageProcessor(**lowerCamelCase     )

         # save in new folder
         model_config.save_pretrained(lowerCamelCase     )
         config.save_pretrained(lowerCamelCase     )

         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     )

         # make sure private variable is not incorrectly saved
         __SCREAMING_SNAKE_CASE   				=							json.loads(config.to_json_string()     )
         self.assertTrue("""_processor_class""" not in dict_as_saved     )

      self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )





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

      '''simple docstring'''

      with tempfile.TemporaryDirectory() as tmpdirname:
         __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """preprocessor_config.json"""
         json.dump(
             {"""image_processor_type""": """CLIPImageProcessor""", """processor_class""": """CLIPProcessor"""}					,open(lowerCamelCase					,"""w"""     )					,)

         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     )
         self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )





   def   UpperCAmelCase__  (       self					:      Dict     ):

      '''simple docstring'''

      with self.assertRaisesRegex(
          lowerCamelCase					,"""clip-base is not a local folder and is not a valid model identifier"""     ):
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained("""clip-base"""     )





   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      with self.assertRaisesRegex(
          lowerCamelCase					,r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""     ):
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase					,revision="""aaaaaa"""     )





   def   UpperCAmelCase__  (       self					:      List[Any]     ):

      '''simple docstring'''

      with self.assertRaisesRegex(
          lowerCamelCase					,"""hf-internal-testing/config-no-model does not appear to have a file named preprocessor_config.json."""					,):
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained("""hf-internal-testing/config-no-model"""     )





   def   UpperCAmelCase__  (       self					:      Any     ):

      '''simple docstring'''

      with self.assertRaises(lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""     )
      # If remote code is disabled, we can't load this config.
      with self.assertRaises(lowerCamelCase     ):
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(
             """hf-internal-testing/test_dynamic_image_processor"""					,trust_remote_code=lowerCamelCase     )

      __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(
          """hf-internal-testing/test_dynamic_image_processor"""					,trust_remote_code=lowerCamelCase     )
      self.assertEqual(image_processor.__class__.__name__					,"""NewImageProcessor"""     )

      # Test image processor can be reloaded.
      with tempfile.TemporaryDirectory() as tmp_dir:
         image_processor.save_pretrained(lowerCamelCase     )
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase					,trust_remote_code=lowerCamelCase     )
      self.assertEqual(reloaded_image_processor.__class__.__name__					,"""NewImageProcessor"""     )





   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      try:
         AutoConfig.register("""custom"""					,lowerCamelCase     )
         AutoImageProcessor.register(lowerCamelCase					,lowerCamelCase     )
         # Trying to register something existing in the Transformers library will raise an error
         with self.assertRaises(lowerCamelCase     ):
            AutoImageProcessor.register(lowerCamelCase					,lowerCamelCase     )

         with tempfile.TemporaryDirectory() as tmpdirname:
            __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """preprocessor_config.json"""
            __SCREAMING_SNAKE_CASE   				=							Path(lowerCamelCase     ) / """config.json"""
            json.dump(
                {"""feature_extractor_type""": """CLIPFeatureExtractor""", """processor_class""": """CLIPProcessor"""}					,open(lowerCamelCase					,"""w"""     )					,)
            json.dump({"""model_type""": """clip"""}					,open(lowerCamelCase					,"""w"""     )     )

            __SCREAMING_SNAKE_CASE   				=							CustomImageProcessor.from_pretrained(lowerCamelCase     )

         # Now that the config is registered, it can be used as any other config with the auto-API
         with tempfile.TemporaryDirectory() as tmp_dir:
            image_processor.save_pretrained(lowerCamelCase     )
            __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(lowerCamelCase     )
            self.assertIsInstance(lowerCamelCase					,lowerCamelCase     )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]





   def   UpperCAmelCase__  (       self					:      str     ):

      '''simple docstring'''

      class __a			( _snake_case      ):
         __UpperCamelCase :			int						   =						True

      try:
         AutoConfig.register("""custom"""					,lowerCamelCase     )
         AutoImageProcessor.register(lowerCamelCase					,lowerCamelCase     )
         # If remote code is not set, the default is to use local
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained("""hf-internal-testing/test_dynamic_image_processor"""     )
         self.assertEqual(image_processor.__class__.__name__					,"""NewImageProcessor"""     )
         self.assertTrue(image_processor.is_local     )

         # If remote code is disabled, we load the local one.
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(
             """hf-internal-testing/test_dynamic_image_processor"""					,trust_remote_code=lowerCamelCase     )
         self.assertEqual(image_processor.__class__.__name__					,"""NewImageProcessor"""     )
         self.assertTrue(image_processor.is_local     )

         # If remote is enabled, we load from the Hub
         __SCREAMING_SNAKE_CASE   				=							AutoImageProcessor.from_pretrained(
             """hf-internal-testing/test_dynamic_image_processor"""					,trust_remote_code=lowerCamelCase     )
         self.assertEqual(image_processor.__class__.__name__					,"""NewImageProcessor"""     )
         self.assertTrue(not hasattr(lowerCamelCase					,"""is_local"""     )     )

      finally:
         if "custom" in CONFIG_MAPPING._extra_content:
            del CONFIG_MAPPING._extra_content["custom"]
         if CustomConfig in IMAGE_PROCESSOR_MAPPING._extra_content:
            del IMAGE_PROCESSOR_MAPPING._extra_content[CustomConfig]





