TrainingExtensions/torch/src/python/aimet_torch/model_preparer.py
def _verify_symbolic_traced_model(symbolic_traced_model: torch.fx.GraphModule):
    """
    Does some checks to make sure the graph is well formed and recompile the forward() method of symbolic_traced
    model from its graph
    :param symbolic_traced_model: Symbolically traced model
    :return: None
    """
    symbolic_traced_model.graph.lint()
    symbolic_traced_model.recompile()

    Does some checks to make sure the graph is well formed and recompile the forward() method of symbolic_traced
    model from its graph
    :param symbolic_traced_model: Symbolically traced model
    :return: None
    
Does some checks to make sure the graph is well formed and recompile the forward() method of symbolic_traced
model from its graph
Does some checks to make sure the graph is well formed and recompile the forward () method of symbolic_traced model from its graph
def _verify_symbolic_traced_model(symbolic_traced_model: torch.fx.GraphModule):
    symbolic_traced_model.graph.lint()
    symbolic_traced_model.recompile()
def _verify_symbolic_traced_model ( symbolic_traced_model : torch . fx . GraphModule ) : symbolic_traced_model . graph . lint ( ) symbolic_traced_model . recompile ( )
Does some checks to make sure the graph is well formed and recompile the forward() method of symbolic_traced
model from its graph
Does some checks to make sure the graph is well formed and recompile the forward () method of symbolic_traced model from its graph
"""
    Does some checks to make sure the graph is well formed and recompile the forward() method of symbolic_traced
    model from its graph
    :param symbolic_traced_model: Symbolically traced model
    :return: None
    """
None
symbolic_traced_model
torch.fx.GraphModule
Symbolically traced model
Symbolically traced model