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