lr = 1e-3 # learning rate
n_epochs = 10000  # number of epochs
lamda = 0.001  # l2 loss regulation weight

batch_size = 1000
n_layers = 3 # number of layers
shape = (64, 32, 16) # network shape
# path settings
train_filename = "../data/ml-1m/train_users.dat"
test_filename = "../data/ml-1m/test_users.dat"
valid_filename = "../data/ml-1m/valid_users.dat"

29f1fe8fd3c2c501a615859a4ea63e5896a20ff5
<mask token>

lr = 0.001
n_epochs = 10000
lamda = 0.001
batch_size = 1000
n_layers = 3
shape = 64, 32, 16
train_filename = '../data/ml-1m/train_users.dat'
test_filename = '../data/ml-1m/test_users.dat'
valid_filename = '../data/ml-1m/valid_users.dat'

lr = 1e-3 # learning rate
n_epochs = 10000  # number of epochs
lamda = 0.001  # l2 loss regulation weight

batch_size = 1000
n_layers = 3 # number of layers
shape = (64, 32, 16) # network shape
# path settings
train_filename = "../data/ml-1m/train_users.dat"
test_filename = "../data/ml-1m/test_users.dat"
valid_filename = "../data/ml-1m/valid_users.dat"
