docstr: Whether the optimizer supports collapsing of the model
  parameters/gradients into a single contiguous Tensor.
docstr_tok: ["Whether","the","optimizer","supports","collapsing","of","the","model","parameters\/gradients","into","a","single","contiguous","Tensor","."]
code: def supports_flat_params(self):
      """
      Whether the optimizer supports collapsing of the model
      parameters/gradients into a single contiguous Tensor.
      """
      if hasattr(self.optimizer, "supports_flat_params"):
          return self.optimizer.supports_flat_params
      return False
  
imports: import torch
  from fairseq import utils
  from fairseq.dataclass.utils import gen_parser_from_dataclass
  from collections import defaultdict
label_desc: Use image node_id 22 for calling the FairseqOptimizer obj's underlying member method code with example usage: obj.supports_flat_params() and returns: False, self