code: def __init__(self, context: pytorch.PyTorchTrialContext):
      self.context = context
      self.dataset_len = context.get_hparam("dataset_len")
      self.metrics_callback = MetricsCallback()
      self.checkpoint_callback = CheckpointCallback()
  
      model = nn.Linear(1, 1, False)
      model.weight.data.fill_(0)
  
      self.model = context.wrap_model(model)
  
      opt = torch.optim.SGD(self.model.parameters(), 0.1)
      self.opt = context.wrap_optimizer(opt)
  
imports: import random
  from typing import Any, Dict, Tuple
  import numpy
  import torch
  from torch import nn
  from determined import pytorch
label_desc: Use image node_id 1 to create a new NoopPyTorchTrial object from inherited base classes: pytorch with example: obj = NoopPyTorchTrial(context)