class_docstr: Fixed learning rate scheduler with optional linear warm-up strategy
code: def get_lr(self, epoch: int, curr_iter: int) -> float:
      if curr_iter < self.warmup_iterations:
          curr_lr = self.warmup_init_lr + curr_iter * self.warmup_step
      else:
          curr_lr = self.fixed_lr
      return max(0.0, curr_lr)
  
file_path: ml-cvnets/optim/scheduler/fixed.py
imports: import argparse
  from optim.scheduler import SCHEDULER_REGISTRY
  from optim.scheduler.base_scheduler import BaseLRScheduler
label_desc: Use image node_id 3 for calling the FixedLRScheduler obj's underlying member method code with example usage: obj.get_lr(epoch, curr_iter) and returns: max