class_docstr: Pretraining machinery using SCRIPT from Nijkamp et al., 2021. Always running sparse prediction.
class_docstr_tok: ["Pretraining","machinery","using","SCRIPT","from","Nijkamp","et","al.",",","2021",".","Always","running","sparse","prediction","."]
docstr: via https://github.com/lucidrains/electra-pytorch/blob/master/electra_pytorch/electra_pytorch.py
code: def _gumbel_noise(self, inputs, eps=1e-9):
      """via https://github.com/lucidrains/electra-pytorch/blob/master/electra_pytorch/electra_pytorch.py"""
      noise = torch.zeros_like(inputs).uniform_(0, 1)
      return -torch.log(-torch.log(noise + eps) + eps)
  
imports: import torch
  from transformers import PretrainedConfig, PreTrainedModel
  from transformers import AutoConfig, AutoModel, AutoModelForMaskedLM, AutoModelForSequenceClassification, AutoModelForTokenClassification
  from typing import Optional
  from omegaconf import OmegaConf
  from .fff import FFF
  from .components import _get_norm_fn, _get_nonlin_fn, EmbeddingComponent, PoolingComponent, PredictionHeadComponent, GLU, get_extended_attention_mask, _init_module
  from .attention import get_attention_mechanism
label_desc: Use image node_id 6 for calling the ScriptableLMForSCRIPTTraining obj's underlying member method code with example usage: obj._gumbel_noise(inputs, eps) and returns: unknown