






from collections import OrderedDict
from typing import Mapping

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


lowercase  							=					logging.get_logger(__name__)

lowercase  							=					{
    "YituTech/conv-bert-base": "https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json",
    "YituTech/conv-bert-medium-small": (
        "https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"
    ),
    "YituTech/conv-bert-small": "https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= '''convbert'''




	def __init__(       self       ,			a=3_05_22       ,			a=7_68       ,			a=12       ,			a=12       ,			a=30_72       ,			a="gelu"       ,			a=0.1       ,			a=0.1       ,			a=5_12       ,			a=2       ,			a=0.02       ,			a=1E-12       ,			a=1       ,			a=0       ,			a=2       ,			a=7_68       ,			a=2       ,			a=9       ,			a=1       ,			a=None       ,			**a       ,			)       ->    Optional[int]:
								super().__init__(
								    pad_token_id=a       ,			bos_token_id=a       ,			eos_token_id=a       ,			**a       ,			)

								snake_case_				=							vocab_size
								snake_case_				=							hidden_size
								snake_case_				=							num_hidden_layers
								snake_case_				=							num_attention_heads
								snake_case_				=							intermediate_size
								snake_case_				=							hidden_act
								snake_case_				=							hidden_dropout_prob
								snake_case_				=							attention_probs_dropout_prob
								snake_case_				=							max_position_embeddings
								snake_case_				=							type_vocab_size
								snake_case_				=							initializer_range
								snake_case_				=							layer_norm_eps
								snake_case_				=							embedding_size
								snake_case_				=							head_ratio
								snake_case_				=							conv_kernel_size
								snake_case_				=							num_groups
								snake_case_				=							classifier_dropout






class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




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













import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


lowercase  							=					logging.getLogger(__name__)




@dataclass
class  UpperCamelCase_      (			snake_case_				):



	'''simple docstring'''




	lowerCAmelCase													= field(
	    default=0.0       ,					metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''Whether to SortishSamler or not.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''whether to use adafactor'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(default=snake_case_       ,					metadata={'''help''': '''Dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default=snake_case_       ,					metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}				)
	lowerCAmelCase													= field(
	    default='''linear'''       ,					metadata={'''help''': F'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()				)}'''}       ,					)





