




'''simple docstring'''







from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PretrainedConfig, PreTrainedTokenizer
from ...onnx import OnnxConfig, PatchingSpec
from ...utils import TensorType, is_torch_available, logging


A			   =logging.get_logger(__name__)

A			   ={
    'microsoft/layoutlm-base-uncased': (
        'https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/config.json'
    ),
    'microsoft/layoutlm-large-uncased': (
        'https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/config.json'
    ),
}


class       _a  (     __a			):
       __a    :					List[Any]           = """layoutlm"""
       def __init__(     self						:     Optional[Any]       ,    lowercase						:     Union[str, Any]=30_522       ,    lowercase						:     Tuple=768       ,    lowercase						:     Union[str, Any]=12       ,    lowercase						:     int=12       ,    lowercase						:     List[str]=3_072       ,    lowercase						:     Tuple="gelu"       ,    lowercase						:     Optional[int]=0.1       ,    lowercase						:     List[Any]=0.1       ,    lowercase						:     Optional[Any]=512       ,    lowercase						:     int=2       ,    lowercase						:     List[Any]=0.02       ,    lowercase						:     int=1E-12       ,    lowercase						:     Any=0       ,    lowercase						:     List[Any]="absolute"       ,    lowercase						:     Dict=True       ,    lowercase						:     Optional[int]=1_024       ,    **lowercase						:     str       ,    ):



           '''simple docstring'''

           super().__init__(pad_token_id=lowercase       ,    **lowercase    )
           UpperCAmelCase      	=		vocab_size
           UpperCAmelCase      	=		hidden_size
           UpperCAmelCase      	=		num_hidden_layers
           UpperCAmelCase      	=		num_attention_heads
           UpperCAmelCase      	=		hidden_act
           UpperCAmelCase      	=		intermediate_size
           UpperCAmelCase      	=		hidden_dropout_prob
           UpperCAmelCase      	=		attention_probs_dropout_prob
           UpperCAmelCase      	=		max_position_embeddings
           UpperCAmelCase      	=		type_vocab_size
           UpperCAmelCase      	=		initializer_range
           UpperCAmelCase      	=		layer_norm_eps
           UpperCAmelCase      	=		position_embedding_type
           UpperCAmelCase      	=		use_cache
           UpperCAmelCase      	=		max_ad_position_embeddings






class       _a  (     __a			):
       def __init__(     self						:     Optional[int]       ,    lowercase						:     PretrainedConfig       ,    lowercase						:     str = "default"       ,    lowercase						:     List[PatchingSpec] = None       ,    ):



           '''simple docstring'''

           super().__init__(lowercase       ,    task=lowercase       ,    patching_specs=lowercase    )
           UpperCAmelCase      	=		config.max_ad_position_embeddings - 1
       @property
       def    A				(     self						:     int    ):



           '''simple docstring'''

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







       def    A				(     self						:     int       ,    lowercase						:     PreTrainedTokenizer       ,    lowercase						:     int = -1       ,    lowercase						:     int = -1       ,    lowercase						:     bool = False       ,    lowercase						:     Optional[TensorType] = None       ,    ):



           '''simple docstring'''

           UpperCAmelCase      	=		super().generate_dummy_inputs(
               lowercase       ,    batch_size=lowercase       ,    seq_length=lowercase       ,    is_pair=lowercase       ,    framework=lowercase    )

           # Generate a dummy bbox
           UpperCAmelCase      	=		[48, 84, 73, 128]

           if not framework == TensorType.PYTORCH:
               raise NotImplementedError('''Exporting LayoutLM to ONNX is currently only supported for PyTorch.'''    )

           if not is_torch_available():
               raise ValueError('''Cannot generate dummy inputs without PyTorch installed.'''    )
           import torch

           UpperCAmelCase	,					UpperCAmelCase      	=		input_dict['''input_ids'''].shape
           UpperCAmelCase      	=		torch.tensor([*[box] * seq_length]    ).tile(lowercase       ,    1       ,    1    )
           return input_dict










'''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			):
       __a    :					Optional[int]           = EsmTokenizer
       def    A				(     self						:     Tuple    ):



           '''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    A				(     self						:     Union[str, Any]       ,    **lowercase						:     Tuple    ):



           '''simple docstring'''

           return [self.get_tokenizer(**lowercase    )]
       def    A				(     self						:     Optional[Any]       ,    **lowercase						:     str    ):



           '''simple docstring'''

           return self.tokenizer_class.from_pretrained(self.tmpdirname       ,    **lowercase    )
       def    A				(     self						:     Optional[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		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						:     str    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		'''LAGVS'''
           self.assertListEqual(tokenizer.encode(lowercase    )       ,    [0, 4, 5, 6, 7, 8, 2]    )
       def    A				(     self						:     Optional[Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		['''LAGVS''', '''WCB''']
           UpperCAmelCase      	=		tokenizer(lowercase       ,    padding=lowercase    )['''input_ids''']

           self.assertListEqual(lowercase       ,    [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]    )
       def    A				(     self						:     Union[str, Any]    ):



           '''simple docstring'''

           UpperCAmelCase      	=		self.tokenizer_class(self.vocab_file    )

           UpperCAmelCase      	=		['''LAGVS''', '''WCB''']
           UpperCAmelCase      	=		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						:     Any    ):



           '''simple docstring'''

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

                   UpperCAmelCase      	=		tokenizer.tokenize(lowercase    )
                   UpperCAmelCase      	=		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    )




