class_docstr: Linear Ramp warm-up followed by constant linear learning rate annealing
class_docstr_tok: ["Linear","Ramp","warm-up","followed","by","constant","linear","learning","rate","annealing"]
code: def _get_closed_form_lr(self):
      linear_lr = [
          base_lr * (1 + self.last_epoch) / self.ramp_len  # type: ignore
          for base_lr in self.base_lrs  # type: ignore
      ]
      return (
          linear_lr
          if self.last_epoch < self.ramp_len
          else self.base_lrs
      )
  
file_path: NeuralCompression/projects/torch_vct/utils/schedulers.py
imports: import math
  import torch
label_desc: Use image node_id 3 for calling the LinearRampLinearLR obj's underlying member method code with example usage: obj._get_closed_form_lr() and returns: unknown