docstr: Check for warnings when passing in a lazy weight Tensor
  Even when asking for flops calculation.
docstr_tok: ["Check","for","warnings","when","passing","in","a","lazy","weight","Tensor","Even","when","asking","for","flops","calculation","."]
code: def test_lazy_tensor_flops(self) -> None:
      """Check for warnings when passing in a lazy weight Tensor
      Even when asking for flops calculation."""
      model = torch.nn.LazyLinear(10)
      ms = get_module_summary(model, module_args=(torch.randn(1, 10),))
      with self.assertWarns(Warning):
          ms.num_parameters
      with self.assertWarns(Warning):
          ms.num_trainable_parameters
      self.assertTrue(ms.has_uninitialized_param)
      self.assertEqual(ms.flops_backward, "?")
      self.assertEqual(ms.flops_forward, "?")
  
imports: import unittest
  from typing import Any, Dict, Optional, Tuple
  import torch
  from torchtnt.utils.module_summary import _get_human_readable_count, get_module_summary, ModuleSummary, prune_module_summary
  from torchvision import models
  from torchvision.models.alexnet import AlexNet_Weights
  from torchvision.models.resnet import ResNet18_Weights
label_desc: Use image node_id 6 for calling the ModuleSummaryTest obj's underlying member method code with example usage: obj.test_lazy_tensor_flops() without return types