def get_default_hyperparameters(cls,
mp_style: Optional[str] = None
) -> Dict[str, Any]:
"""Get the default hyperparameter dictionary for the class."""
params = {
f"gnn_{name}": value
for name, value in GNN.get_default_hyperparameters(
mp_style).items()
}
these_hypers: Dict[str, Any] = {
"optimizer": "Adam", # One of "SGD", "RMSProp", "Adam"
"learning_rate": 0.001,
"learning_rate_warmup_steps": None,
"learning_rate_decay_steps": None,
"momentum": 0.85,
"rmsprop_rho":
0.98, # decay of gradients in RMSProp (unused otherwise)
"gradient_clip_value":
None, # Set to float value to clip each gradient separately
"gradient_clip_norm":
None, # Set to value to clip gradients by their norm
"gradient_clip_global_norm":
None, # Set to value to clip gradients by their global norm
"use_intermediate_gnn_results": False,
}
params.update(these_hypers)
return params
def get_default_hyperparameters(cls, mp_style: Optional[str] = None) -> Dict[str, Any]:
"""Get the default hyperparameter dictionary for the class."""
params = {f"gnn_{name}": value for name, value in GNN.get_default_hyperparameters(mp_style).items()}
these_hypers: Dict[str, Any] = {
"optimizer": "Adam", # One of "SGD", "RMSProp", "Adam"
"learning_rate": 0.001,
"learning_rate_decay": 0.98,
"momentum": 0.85,
"gradient_clip_value": 1.0,
"use_intermediate_gnn_results": False,
}
params.update(these_hypers)
return params
def get_default_hyperparameters(cls, mp_style: Optional[str] = None) -> Dict[str, Any]:
"""Get the default hyperparameter dictionary for the class."""
params = {f"gnn_{name}": value for name, value in GNN.get_default_hyperparameters(mp_style).items()}
these_hypers: Dict[str, Any] = {
"graph_aggregation_size": 256,
"graph_aggregation_num_heads": 16,
"graph_aggregation_hidden_layers": [128],
"graph_aggregation_dropout_rate": 0.2,
"token_embedding_size": 64,
"gnn_message_calculation_class": "gnn_edge_mlp",
"gnn_hidden_dim": 64,
"gnn_global_exchange_mode": "mlp",
"gnn_global_exchange_every_num_layers": 10,
"gnn_num_layers": 4,
"graph_encoding_size": 256,
}
params.update(these_hypers)
return params