test_train: Adam -> SGD
@@ -18,7 +18,7 @@ def train_one_step(model,X,Y):
pcount = 0
for p in params:
pcount += np.prod(p.shape)
- optimizer = optim.Adam(params, lr=0.001)
+ optimizer = optim.SGD(params, lr=0.001)
print("stepping %r with %.1fM params bs %d" % (type(model), pcount/1e6, BS))
st = time.time()
train(model, X, Y, optimizer, steps=1, BS=BS)
