


'''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 			UpperCAmelCase			(							unittest.TestCase):
 _lowerCamelCase			:       Optional[int]            =       EsmTokenizer

 def 		lowercase_    (			self			:						int       ):





    """simple docstring"""



    super().setUp()
    UpperCamelCase__			    =    tempfile.mkdtemp()
    # fmt: off
    UpperCamelCase__			    =    ["<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
    UpperCamelCase__			    =    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 		lowercase_    (			self			:						Optional[int],       **a_			:						Dict       ):





    """simple docstring"""



    return [self.get_tokenizer(**a_       )]

 def 		lowercase_    (			self			:						List[Any],       **a_			:						Dict       ):





    """simple docstring"""



    return self.tokenizer_class.from_pretrained(self.tmpdirname,       **a_       )

 def 		lowercase_    (			self			:						int       ):





    """simple docstring"""



    UpperCamelCase__			    =    self.tokenizer_class(self.vocab_file       )

    UpperCamelCase__			    =    tokenizer.tokenize("LAGVS"       )
    self.assertListEqual(a_,       ["L", "A", "G", "V", "S"]       )
    self.assertListEqual(tokenizer.convert_tokens_to_ids(a_       ),       [4, 5, 6, 7, 8]       )

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





    """simple docstring"""



    UpperCamelCase__			    =    self.tokenizer_class(self.vocab_file       )

    UpperCamelCase__			    =    "LAGVS"
    self.assertListEqual(tokenizer.encode(a_       ),       [0, 4, 5, 6, 7, 8, 2]       )

 def 		lowercase_    (			self			:						List[str]       ):





    """simple docstring"""



    UpperCamelCase__			    =    self.tokenizer_class(self.vocab_file       )

    UpperCamelCase__			    =    ["LAGVS", "WCB"]
    UpperCamelCase__			    =    tokenizer(a_,       padding=a_       )["input_ids"]

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

 def 		lowercase_    (			self			:						int       ):





    """simple docstring"""



    UpperCamelCase__			    =    self.tokenizer_class(self.vocab_file       )

    UpperCamelCase__			    =    ["LAGVS", "WCB"]
    UpperCamelCase__			    =    tokenizer(a_,       padding=a_       )["input_ids"]

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

 def 		lowercase_    (			self			:						Tuple       ):





    """simple docstring"""



    UpperCamelCase__			    =    self.get_tokenizers(fast=a_       )
    for tokenizer in tokenizers:
       with self.subTest(f'{tokenizer.__class__.__name__}'       ):
          UpperCamelCase__			    =    "<unk>"
          UpperCamelCase__			    =    "<mask>"

          UpperCamelCase__			    =    tokenizer.tokenize(a_       )
          UpperCamelCase__			    =    tokenizer.tokenize(a_       )

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



'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

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


__lowercase:		List[str]    						=  logging.get_logger(__name__)

__lowercase:		List[Any]    						=  {
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):
 _lowerCamelCase			:       Optional[int]            =       'plbart'
 _lowerCamelCase			:       Union[str, Any]            =       ['past_key_values']
 _lowerCamelCase			:       Tuple            =       {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

 def __init__(			self			:						Optional[Any],       a_			:						Union[str, Any]=5_0005,       a_			:						int=1024,       a_			:						str=6,       a_			:						Union[str, Any]=3072,       a_			:						Optional[int]=12,       a_			:						Optional[Any]=6,       a_			:						Dict=3072,       a_			:						Dict=12,       a_			:						int=0.0,       a_			:						List[Any]=0.0,       a_			:						Optional[Any]=True,       a_			:						List[str]=True,       a_			:						Tuple="gelu",       a_			:						Any=768,       a_			:						Dict=0.1,       a_			:						List[Any]=0.1,       a_			:						Union[str, Any]=0.0,       a_			:						Optional[Any]=0.02,       a_			:						Union[str, Any]=0.0,       a_			:						int=True,       a_			:						Dict=1,       a_			:						Optional[int]=0,       a_			:						Optional[int]=2,       a_			:						Any=2,       **a_			:						Optional[Any],       ):





    """simple docstring"""



    UpperCamelCase__			    =    vocab_size
    UpperCamelCase__			    =    max_position_embeddings
    UpperCamelCase__			    =    d_model
    UpperCamelCase__			    =    encoder_ffn_dim
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    encoder_attention_heads
    UpperCamelCase__			    =    decoder_ffn_dim
    UpperCamelCase__			    =    decoder_layers
    UpperCamelCase__			    =    decoder_attention_heads
    UpperCamelCase__			    =    dropout
    UpperCamelCase__			    =    attention_dropout
    UpperCamelCase__			    =    activation_dropout
    UpperCamelCase__			    =    activation_function
    UpperCamelCase__			    =    init_std
    UpperCamelCase__			    =    encoder_layerdrop
    UpperCamelCase__			    =    decoder_layerdrop
    UpperCamelCase__			    =    classifier_dropout
    UpperCamelCase__			    =    use_cache
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    scale_embedding  # scale factor will be sqrt(d_model) if True
    super().__init__(
        pad_token_id=a_,       bos_token_id=a_,       eos_token_id=a_,       is_encoder_decoder=a_,       forced_eos_token_id=a_,       **a_,       )







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):

 @property
 def 		lowercase_    (			self			:						int       ):





    """simple docstring"""



    return OrderedDict(
        [
            ("input_ids", {0: "batch", 1: "sequence"}),
            ("attention_mask", {0: "batch", 1: "sequence"}),
        ]       )

 @property
 def 		lowercase_    (			self			:						Tuple       ):





    """simple docstring"""



    if self.use_past:
       return OrderedDict(
           [
               ("last_hidden_state", {0: "batch", 1: "sequence"}),
               ("past_keys", {0: "batch", 2: "sequence"}),
               ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
           ]       )
    else:
       return OrderedDict(
           [
               ("last_hidden_state", {0: "batch", 1: "sequence"}),
               ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
           ]       )