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Optimize tensor conversion in evaluate_gat_model by using np.array #8

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Optimize tensor conversion in evaluate_gat_model by using np.array #8

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5 changes: 4 additions & 1 deletion models/gat_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@
import torch
import torch.nn as nn
from torch_geometric.nn import GATConv, global_mean_pool
import numpy as np

class NextTaskGAT(nn.Module):
"""
Expand Down Expand Up @@ -111,5 +112,7 @@ def evaluate_gat_model(model, val_loader, device):
return (
torch.tensor(y_true_all),
torch.tensor(y_pred_all),
torch.tensor(y_prob_all)
torch.tensor(np.array(y_prob_all))
# ^Convert list of NumPy arrays to a single array for efficient tensor creation
# Fixes warning: "Creating a tensor from a list of numpy.ndarrays is extremely slow"
)