"""simple docstring"""







import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 		UpperCamelCase      (   lowercase				,     unittest.TestCase						):
				UpperCAmelCase    :				List[Any]   =		MgpstrTokenizer
				UpperCAmelCase    :				int   =		False
				UpperCAmelCase    :				int   =		{}
				UpperCAmelCase    :				List[str]   =		False



				def  _lowercase					(self    :				Optional[int])   ->     int:
					super().setUp()

					# fmt: off
					__snake_case      :							Any						=			['[GO]', '[s]', '0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z']
					# fmt: on
					__snake_case      :							int						=			dict(zip(_A     ,  range(len(_A))))

					__snake_case      :							int						=			os.path.join(self.tmpdirname     ,  VOCAB_FILES_NAMES['vocab_file'])
					with open(self.vocab_file     ,  'w'     ,  encoding='utf-8') as fp:
						fp.write(json.dumps(_A) + '\n')



				def  _lowercase					(self    :				Union[str, Any]     ,  **_A    :				str)   ->     Optional[int]:
					return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,  **_A)



				def  _lowercase					(self    :				Tuple     ,  _A    :				Optional[int])   ->     Optional[int]:
					__snake_case      :							Optional[Any]						=			'tester'
					__snake_case      :							Dict						=			'tester'
					return input_text, output_text



				@unittest.skip('MGP-STR always lower cases letters.')
				def  _lowercase					(self    :				Union[str, Any])   ->     List[Any]:
					pass



				def  _lowercase					(self    :				str)   ->     Any:
					__snake_case      :							Optional[Any]						=			self.get_tokenizers(do_lower_case=_A)
					for tokenizer in tokenizers:
						with self.subTest(f"{tokenizer.__class__.__name__}"):
							__snake_case      :							int						=			'[SPECIAL_TOKEN]'

							tokenizer.add_special_tokens({'cls_token': special_token})
							__snake_case      :							Optional[Any]						=			tokenizer.encode([special_token]     ,  add_special_tokens=_A)
							self.assertEqual(len(_A)     ,  1)

							__snake_case      :							Optional[Any]						=			tokenizer.decode(_A     ,  skip_special_tokens=_A)
							self.assertTrue(special_token not in decoded)



				def  _lowercase					(self    :				Optional[Any])   ->     List[str]:
					__snake_case      :							Any						=			self.get_tokenizers()
					for tokenizer in tokenizers:
						with self.subTest(f"{tokenizer.__class__.__name__}"):
							__snake_case      :							Optional[Any]						=			self.get_input_output_texts(_A)

							__snake_case      :							List[Any]						=			tokenizer.tokenize(_A)
							__snake_case      :							str						=			tokenizer.convert_tokens_to_ids(_A)
							__snake_case      :							Any						=			tokenizer.encode(_A     ,  add_special_tokens=_A)
							self.assertListEqual(_A     ,  _A)

							__snake_case      :							Tuple						=			tokenizer.convert_ids_to_tokens(_A)
							self.assertNotEqual(len(_A)     ,  0)
							__snake_case      :							List[str]						=			tokenizer.decode(_A)
							self.assertIsInstance(_A     ,  _A)

							self.assertEqual(text_a.replace(' '     ,  '')     ,  _A)



				@unittest.skip('MGP-STR tokenizer only handles one sequence.')
				def  _lowercase					(self    :				List[str])   ->     Union[str, Any]:
					pass






				@unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer')
				def  _lowercase					(self    :				Any)   ->     Optional[int]:
					pass






"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


_a					:					Tuple=			{
    "albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
    "albert-large-v1": "https://huggingface.co/albert-large-v1/resolve/main/config.json",
    "albert-xlarge-v1": "https://huggingface.co/albert-xlarge-v1/resolve/main/config.json",
    "albert-xxlarge-v1": "https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json",
    "albert-base-v2": "https://huggingface.co/albert-base-v2/resolve/main/config.json",
    "albert-large-v2": "https://huggingface.co/albert-large-v2/resolve/main/config.json",
    "albert-xlarge-v2": "https://huggingface.co/albert-xlarge-v2/resolve/main/config.json",
    "albert-xxlarge-v2": "https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json",
}

class 		UpperCamelCase      (   lowercase						):
				UpperCAmelCase    :				str   =		"""albert"""



				def __init__(self    :				Union[str, Any]     ,  _A    :				int=3_00_00     ,  _A    :				Any=1_28     ,  _A    :				Tuple=40_96     ,  _A    :				int=12     ,  _A    :				Tuple=1     ,  _A    :				int=64     ,  _A    :				Optional[Any]=1_63_84     ,  _A    :				Optional[Any]=1     ,  _A    :				List[str]="gelu_new"     ,  _A    :				Any=0     ,  _A    :				Optional[Any]=0     ,  _A    :				List[Any]=5_12     ,  _A    :				List[Any]=2     ,  _A    :				Dict=0.02     ,  _A    :				Union[str, Any]=1E-12     ,  _A    :				Tuple=0.1     ,  _A    :				int="absolute"     ,  _A    :				List[Any]=0     ,  _A    :				str=2     ,  _A    :				int=3     ,  **_A    :				Tuple     ,  )   ->     Union[str, Any]:
					super().__init__(pad_token_id=_A     ,  bos_token_id=_A     ,  eos_token_id=_A     ,  **_A)

					__snake_case      :							str						=			vocab_size
					__snake_case      :							List[Any]						=			embedding_size
					__snake_case      :							Tuple						=			hidden_size
					__snake_case      :							Optional[Any]						=			num_hidden_layers
					__snake_case      :							List[str]						=			num_hidden_groups
					__snake_case      :							Dict						=			num_attention_heads
					__snake_case      :							Any						=			inner_group_num
					__snake_case      :							Union[str, Any]						=			hidden_act
					__snake_case      :							List[Any]						=			intermediate_size
					__snake_case      :							List[str]						=			hidden_dropout_prob
					__snake_case      :							int						=			attention_probs_dropout_prob
					__snake_case      :							Any						=			max_position_embeddings
					__snake_case      :							Optional[int]						=			type_vocab_size
					__snake_case      :							Optional[Any]						=			initializer_range
					__snake_case      :							List[Any]						=			layer_norm_eps
					__snake_case      :							Optional[Any]						=			classifier_dropout_prob
					__snake_case      :							List[str]						=			position_embedding_type







class 		UpperCamelCase      (   lowercase						):



				@property
				def  _lowercase					(self    :				Tuple)   ->     Mapping[str, Mapping[int, str]]:
					if self.task == "multiple-choice":
						__snake_case      :							int						=			{0: 'batch', 1: 'choice', 2: 'sequence'}
					else:
						__snake_case      :							Optional[Any]						=			{0: 'batch', 1: 'sequence'}
					return OrderedDict(
					    [
					        ('input_ids', dynamic_axis),
					        ('attention_mask', dynamic_axis),
					        ('token_type_ids', dynamic_axis),
					    ])





