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patching supervised loss weight because it is not passed to NeuralAdmixture class #46

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patching supervised loss weight because it is not passed to NeuralAdmixture class #46

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4 changes: 2 additions & 2 deletions neural_admixture/model/train.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@

def train(epochs: int, batch_size: int, learning_rate: float, K: int, seed: int,
data: torch.Tensor, device: torch.device, num_gpus: int, hidden_size: int,
master: bool, V: np.ndarray, pops : np.ndarray, min_k: int=None, max_k: int=None, n_components: int=None) -> Tuple[torch.Tensor, torch.Tensor, torch.nn.Module]:
master: bool, V: np.ndarray, pops : np.ndarray, min_k: int=None, max_k: int=None, n_components: int=None, supervised_loss_weight: int=100) -> Tuple[torch.Tensor, torch.Tensor, torch.nn.Module]:
"""
Initializes P and Q matrices and trains a neural admixture model using GMM.

Expand Down Expand Up @@ -128,7 +128,7 @@ def train(epochs: int, batch_size: int, learning_rate: float, K: int, seed: int,
pack2bit = None
packed_data = data

model = NeuralAdmixture(K, epochs, batch_size, learning_rate, device, seed, num_gpus, master, pack2bit, min_k, max_k)
model = NeuralAdmixture(K, epochs, batch_size, learning_rate, device, seed, num_gpus, master, pack2bit, min_k, max_k,supervised_loss_weight)
Qs, Ps, model = model.launch_training(P_init, packed_data, hidden_size, V.shape[1], V, M, N, pops)

if master:
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5 changes: 3 additions & 2 deletions neural_admixture/src/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,8 +32,9 @@ def fit_model(args: argparse.Namespace, data: torch.Tensor, device: torch.device
min_k = int(args.min_k)
max_k = int(args.max_k)
K = None

Ps, Qs, model = train(epochs, batch_size, learning_rate, K, seed, data, device, num_gpus, hidden_size, master, V, pops, min_k, max_k, n_components)
if args.supervised_loss_weight is None:
args.supervised_loss_weight = 100
Ps, Qs, model = train(epochs, batch_size, learning_rate, K, seed, data, device, num_gpus, hidden_size, master, V, pops, min_k, max_k, n_components, args.supervised_loss_weight)

if master:
Path(save_dir).mkdir(parents=True, exist_ok=True)
Expand Down