
'''simple docstring'''







from typing import Callable, Optional, Union

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


_snake_case				:   Optional[Any]     =				logging.get_logger(__name__)

_snake_case				:   Optional[Any]     =				{
    'microsoft/xprophetnet-large-wiki100-cased': (
        'https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'
    ),
}


class 			lowerCAmelCase (				__lowercase			):
		a							:					Optional[int]       =					'''xlm-prophetnet'''
		a							:					Any       =					['''past_key_values''']
		a							:					Dict       =					{
		    '''num_attention_heads''': '''num_encoder_attention_heads''',
		}




		def __init__(				self					,						UpperCamelCase = 0.1					,						UpperCamelCase = "gelu"					,						UpperCamelCase = 30_522					,						UpperCamelCase = 1_024					,						UpperCamelCase = 4_096					,						UpperCamelCase = 12					,						UpperCamelCase = 16					,						UpperCamelCase = 4_096					,						UpperCamelCase = 12					,						UpperCamelCase = 16					,						UpperCamelCase = 0.1					,						UpperCamelCase = 0.1					,						UpperCamelCase = 512					,						UpperCamelCase = 0.02					,						UpperCamelCase = True					,						UpperCamelCase = True					,						UpperCamelCase = 0					,						UpperCamelCase = 2					,						UpperCamelCase = 32					,						UpperCamelCase = 128					,						UpperCamelCase = False					,						UpperCamelCase = 0.0					,						UpperCamelCase = True					,						UpperCamelCase = 0					,						UpperCamelCase = 1					,						UpperCamelCase = 2					,						**UpperCamelCase					,						):
								_SCREAMING_SNAKE_CASE				= vocab_size
								_SCREAMING_SNAKE_CASE				= hidden_size
								_SCREAMING_SNAKE_CASE				= encoder_ffn_dim
								_SCREAMING_SNAKE_CASE				= num_encoder_layers
								_SCREAMING_SNAKE_CASE				= num_encoder_attention_heads
								_SCREAMING_SNAKE_CASE				= decoder_ffn_dim
								_SCREAMING_SNAKE_CASE				= num_decoder_layers
								_SCREAMING_SNAKE_CASE				= num_decoder_attention_heads
								_SCREAMING_SNAKE_CASE				= max_position_embeddings
								_SCREAMING_SNAKE_CASE				= init_std  # Normal(0, this parameter)
								_SCREAMING_SNAKE_CASE				= activation_function

								# parameters for xlmprophetnet
								_SCREAMING_SNAKE_CASE				= ngram
								_SCREAMING_SNAKE_CASE				= num_buckets
								_SCREAMING_SNAKE_CASE				= relative_max_distance
								_SCREAMING_SNAKE_CASE				= disable_ngram_loss
								_SCREAMING_SNAKE_CASE				= eps

								# 3 Types of Dropout
								_SCREAMING_SNAKE_CASE				= attention_dropout
								_SCREAMING_SNAKE_CASE				= activation_dropout
								_SCREAMING_SNAKE_CASE				= dropout

								_SCREAMING_SNAKE_CASE				= use_cache

								super().__init__(
								    pad_token_id=__a					,						bos_token_id=__a					,						eos_token_id=__a					,						is_encoder_decoder=__a					,						add_cross_attention=__a					,						decoder_start_token_id=__a					,						**__a					,						)




		@property
		def     lowercase       (				self      ):
								return self.num_encoder_layers + self.num_decoder_layers




		@num_hidden_layers.setter
		def     lowercase       (				self					,						UpperCamelCase      ):
								raise NotImplementedError(
								    "This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"
								    " `num_decoder_layers`."      )

'''simple docstring'''







import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 			lowerCAmelCase (				__UpperCAmelCase		,     unittest.TestCase			):
		a							:					int       =					LayoutLMTokenizer
		a							:					Optional[int]       =					LayoutLMTokenizerFast
		a							:					Optional[int]       =					True
		a							:					Any       =					True




		def     lowercase       (				self      ):
								super().setUp()

								_SCREAMING_SNAKE_CASE				= [
								    "[UNK]",
								    "[CLS]",
								    "[SEP]",
								    "want",
								    "##want",
								    "##ed",
								    "wa",
								    "un",
								    "runn",
								    "##ing",
								    ",",
								    "low",
								    "lowest",
								]
								_SCREAMING_SNAKE_CASE				= 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					,						**UpperCamelCase      ):
								return LayoutLMTokenizer.from_pretrained(self.tmpdirname					,						**UpperCamelCase      )




		def     lowercase       (				self					,						UpperCamelCase      ):
								_SCREAMING_SNAKE_CASE				= "UNwant\u00E9d,running"
								_SCREAMING_SNAKE_CASE				= "unwanted, running"
								return input_text, output_text




		def     lowercase       (				self      ):
								_SCREAMING_SNAKE_CASE				= self.tokenizer_class(self.vocab_file      )

								_SCREAMING_SNAKE_CASE				= tokenizer.tokenize("UNwant\u00E9d,running"      )
								self.assertListEqual(UpperCamelCase					,						["un", "##want", "##ed", ",", "runn", "##ing"]      )
								self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase      )					,						[7, 4, 5, 10, 8, 9]      )




		def     lowercase       (				self      ):
								pass