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Minor edit to comments #6

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4 changes: 2 additions & 2 deletions models/graphcnn.py
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Expand Up @@ -16,8 +16,8 @@ def __init__(self, num_layers, num_mlp_layers, input_dim, hidden_dim, output_dim
output_dim: number of classes for prediction
final_dropout: dropout ratio on the final linear layer
learn_eps: If True, learn epsilon to distinguish center nodes from neighboring nodes. If False, aggregate neighbors and center nodes altogether.
neighbor_pooling_type: how to aggregate neighbors (mean, average, or max)
graph_pooling_type: how to aggregate entire nodes in a graph (mean, average)
neighbor_pooling_type: how to aggregate neighbors (sum, average, or max)
graph_pooling_type: how to aggregate entire nodes in a graph (sum, average)
device: which device to use
'''

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