






"""simple docstring"""


import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase






@require_tokenizers
class __a ( unittest.TestCase					):
  __lowercase     :     List[str]       						=       EsmTokenizer



  def     A_					(self	:		Any )		->				Dict:
   super().setUp()
   __A						:							str      =						tempfile.mkdtemp()
   # fmt: off
   __A						:							List[str]      =						["<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>"]  # noqa: E501
   # fmt: on
   __A						:							int      =						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] ) )



  def     A_					(self	:		Any					,      **lowercase_	:		Optional[int] )		->				List[PreTrainedTokenizerBase]:
   return [self.get_tokenizer(**lowercase_ )]



  def     A_					(self	:		List[Any]					,      **lowercase_	:		str )		->				PreTrainedTokenizer:
   return self.tokenizer_class.from_pretrained(self.tmpdirname					,      **lowercase_ )



  def     A_					(self	:		Optional[Any] )		->				Optional[int]:
   __A						:							List[str]      =						self.tokenizer_class(self.vocab_file )

   __A						:							int      =						tokenizer.tokenize('LAGVS' )
   self.assertListEqual(lowercase_					,      ['L', 'A', 'G', 'V', 'S'] )
   self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_ )					,      [4, 5, 6, 7, 8] )



  def     A_					(self	:		Tuple )		->				List[Any]:
   __A						:							Dict      =						self.tokenizer_class(self.vocab_file )

   __A						:							Optional[int]      =						'LAGVS'
   self.assertListEqual(tokenizer.encode(lowercase_ )					,      [0, 4, 5, 6, 7, 8, 2] )



  def     A_					(self	:		Union[str, Any] )		->				List[str]:
   __A						:							Union[str, Any]      =						self.tokenizer_class(self.vocab_file )

   __A						:							List[str]      =						['LAGVS', 'WCB']
   __A						:							Tuple      =						tokenizer(lowercase_					,      padding=lowercase_ )['input_ids']

   self.assertListEqual(lowercase_					,      [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]] )



  def     A_					(self	:		Any )		->				List[Any]:
   __A						:							Dict      =						self.tokenizer_class(self.vocab_file )

   __A						:							Optional[int]      =						['LAGVS', 'WCB']
   __A						:							int      =						tokenizer(lowercase_					,      padding=lowercase_ )['input_ids']

   self.assertListEqual(lowercase_					,      [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]] )



  def     A_					(self	:		str )		->				Optional[Any]:
   __A						:							Any      =						self.get_tokenizers(fast=lowercase_ )
   for tokenizer in tokenizers:
    with self.subTest(f"{tokenizer.__class__.__name__}" ):
     __A						:							Optional[Any]      =						'<unk>'
     __A						:							Dict      =						'<mask>'

     __A						:							Optional[int]      =						tokenizer.tokenize(lowercase_ )
     __A						:							Tuple      =						tokenizer.tokenize(lowercase_ )

     self.assertEqual(len(lowercase_ )					,      1 )
     self.assertEqual(len(lowercase_ )					,      1 )
     self.assertEqual(token_a[0]					,      lowercase_ )
     self.assertEqual(token_a[0]					,      lowercase_ )










"""simple docstring"""




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


_UpperCamelCase:					Tuple     				=	logging.get_logger(__name__)

_UpperCamelCase:					List[str]     				=	{
    'facebook/regnet-y-040': 'https://huggingface.co/facebook/regnet-y-040/blob/main/config.json',
}


class 	a__		(    SCREAMING_SNAKE_CASE__  ):
   _lowerCamelCase       				=					'regnet'
   _lowerCamelCase       				=					['x', 'y']


   def __init__(				self   :				Union[str, Any],  lowerCAmelCase   :				Union[str, Any]=3,  lowerCAmelCase   :				Tuple=32,  lowerCAmelCase   :				Optional[int]=[128, 192, 512, 1088],  lowerCAmelCase   :				Optional[int]=[2, 6, 12, 2],  lowerCAmelCase   :				str=64,  lowerCAmelCase   :				List[str]="y",  lowerCAmelCase   :				Optional[int]="relu",  **lowerCAmelCase   :				List[Any],  )     ->							Union[str, Any]:
         super().__init__(**lowerCAmelCase      )
         if layer_type not in self.layer_types:
               raise ValueError(f'''layer_type={layer_type} is not one of {','.join(self.layer_types      )}'''      )
         lowercase	:   str											= num_channels
         lowercase	:   str											= embedding_size
         lowercase	:   int											= hidden_sizes
         lowercase	:   Tuple											= depths
         lowercase	:   str											= groups_width
         lowercase	:   List[str]											= layer_type
         lowercase	:   Optional[int]											= hidden_act
         # always downsample in the first stage
         lowercase	:   Optional[Any]											= True
