set mlp default params
@@ -8,14 +8,14 @@ class MLP(chainer.Chain):
"""Basic implementation for MLP
Args:
+ out_dim (int): dimension of output feature vector
hidden_dim (int): dimension of feature vector
associated to each atom
- out_dim (int): dimension of output feature vector
n_layers (int): number of layers
activation (chainer.functions): activation function
"""
- def __init__(self, hidden_dim, out_dim, n_layers=2, activation=relu):
+ def __init__(self, out_dim, hidden_dim=16, n_layers=2, activation=relu):
super(MLP, self).__init__()
if n_layers <= 0:
raise ValueError('n_layers must be positive integer, but set {}'
