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restructuring and renaming

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Kevin
2018-08-04 14:30:47 -07:00
parent 940041d06f
commit 3632c231f0
8 changed files with 155 additions and 156 deletions
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function_learning.py
+14 -13
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@@ -7,7 +7,7 @@ import torch
import torch.nn as nn
import torch.nn.functional as F
from models import MultiLayerNet, MultiLayerNAC, MultiLayerNALU
from models import MLP, NAC, NALU
NORMALIZE = True
NUM_LAYERS = 2
@@ -68,27 +68,27 @@ def main():
save_dir = './results/'
models = [
MultiLayerNet(
'relu6',
MLP(
num_layers=NUM_LAYERS,
in_dim=2,
hidden_dim=HIDDEN_DIM,
out_dim=1
out_dim=1,
activation='relu6',
),
MultiLayerNet(
'none',
MLP(
num_layers=NUM_LAYERS,
in_dim=2,
hidden_dim=HIDDEN_DIM,
out_dim=1
out_dim=1,
activation='none',
),
MultiLayerNAC(
NAC(
num_layers=NUM_LAYERS,
in_dim=2,
hidden_dim=HIDDEN_DIM,
out_dim=1
out_dim=1,
),
MultiLayerNALU(
NALU(
num_layers=NUM_LAYERS,
in_dim=2,
hidden_dim=HIDDEN_DIM,
@@ -110,9 +110,10 @@ def main():
# random model
random_mse = []
for i in range(100):
net = MultiLayerNet(
'relu6', num_layers=NUM_LAYERS,
in_dim=2, hidden_dim=HIDDEN_DIM, out_dim=1
net = MLP(
num_layers=NUM_LAYERS, in_dim=2,
hidden_dim=HIDDEN_DIM, out_dim=1,
activation='relu6',
)
mse = test(net, X_test, y_test)
random_mse.append(mse.mean().item())