class_docstr: Test the Regnet FSDP model in comparison with the DDP Regnet
  to verify that both converge to the same losses
class_docstr_tok: ["Test","the","Regnet","FSDP","model","in","comparison","with","the","DDP","Regnet","to","verify","that","both","converge","to","the","same","losses"]
code: def run_linear_eval(
      self,
      checkpoint_path: str,
      with_fsdp: bool,
      with_mixed_precision: bool,
      auto_wrap_threshold: int = 0,
  ):
      with in_temporary_directory():
          config = self._create_linear_evaluation_config(
              with_fsdp=with_fsdp,
              with_mixed_precision=with_mixed_precision,
              auto_wrap_threshold=auto_wrap_threshold,
          )
          config.MODEL.WEIGHTS_INIT.PARAMS_FILE = checkpoint_path
          result = run_integration_test(config)
          return result.get_losses()
  
imports: import os
  import unittest
  import numpy
  import torch
  from vissl.utils.checkpoint import CheckpointFormatConverter
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict
  from vissl.utils.test_utils import gpu_test, in_temporary_directory, run_integration_test
label_desc: Use image node_id 7 for calling the TestRegnetFSDPIntegration obj's underlying member method code with example usage: obj.run_linear_eval(checkpoint_path, with_fsdp, with_mixed_precision, auto_wrap_threshold) and returns: result