class_docstr: Members:
      eval_only: If True, only run evaluation using the test dataloader.
      max_epochs: Train for this many epochs. Note that if the model was
          loaded from a checkpoint, we will restart training at the appropriate
          epoch and run for (max_epochs - checkpoint_epoch) epochs.
      store_checkpoints: If True, store model and optimizer state checkpoints.
      store_checkpoints_purge: If >= 0, remove any checkpoints older or equal
          to this many epochs.
      test_interval: Evaluate on a test dataloader each `test_interval` epochs.
      test_when_finished: If True, evaluate on a test dataloader when training
          completes.
      validation_interval: Validate each `validation_interval` epochs.
      clip_grad: Optionally clip the gradient norms.
          If set to a value <=0.0, no clipping
      metric_print_interval: The batch interval at which the stats should be
          logged.
      visualize_interval: The batch interval at which the visualizations
          should be plotted
      visdom_env: The name of the Visdom environment to use for plotting.
      visdom_port: The Visdom port.
      visdom_server: Address of the Visdom server.
code: def __post_init__(self):
      run_auto_creation(self)
  
imports: import logging
  import os
  import time
  from typing import Any, List, Optional
  import torch
  from accelerate import Accelerator
  from pytorch3d.implicitron.evaluation.evaluator import EvaluatorBase
  from pytorch3d.implicitron.models.base_model import ImplicitronModelBase
  from pytorch3d.implicitron.models.generic_model import EvaluationMode
  from pytorch3d.implicitron.tools import model_io, vis_utils
  from pytorch3d.implicitron.tools.config import registry, ReplaceableBase, run_auto_creation
  from pytorch3d.implicitron.tools.stats import Stats
  from torch.utils.data import DataLoader, Dataset
  from .utils import seed_all_random_engines
label_desc: Use image node_id 1 for calling the ImplicitronTrainingLoop obj's underlying member method code with example usage: obj.__post_init__() without return types