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FIX Fixes LMNN rollback #100

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FIX Fixes LMNN rollback #100

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31 changes: 23 additions & 8 deletions metric_learn/lmnn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -95,12 +95,16 @@ def fit(self, X, y):
L = self.L_
objective = np.inf

# we initialize the roll back
L_old = L.copy()
G_old = G.copy()
df_old = df.copy()
a1_old = [a.copy() for a in a1]
a2_old = [a.copy() for a in a2]
objective_old = objective

# main loop
for it in xrange(1, self.max_iter):
df_old = df.copy()
a1_old = [a.copy() for a in a1]
a2_old = [a.copy() for a in a2]
objective_old = objective
# Compute pairwise distances under current metric
Lx = L.dot(self.X_.T).T
g0 = _inplace_paired_L2(*Lx[impostors])
Expand Down Expand Up @@ -158,14 +162,25 @@ def fit(self, X, y):
if delta_obj > 0:
# we're getting worse... roll back!
learn_rate /= 2.0
L = L_old
G = G_old
df = df_old
a1 = a1_old
a2 = a2_old
objective = objective_old
else:
# update L
L -= learn_rate * 2 * L.dot(G)
learn_rate *= 1.01
# We did good. We store this point as reference in case we do
# worse next time.
objective_old = objective
L_old = L.copy()
G_old = G.copy()
df_old = df.copy()
a1_old = [a.copy() for a in a1]
a2_old = [a.copy() for a in a2]
# we update L and will see in the next iteration if it does indeed
# better
L -= learn_rate * 2 * L.dot(G)
learn_rate *= 1.01

# check for convergence
if it > self.min_iter and abs(delta_obj) < self.convergence_tol:
Expand All @@ -177,7 +192,7 @@ def fit(self, X, y):
print("LMNN didn't converge in %d steps." % self.max_iter)

# store the last L
self.L_ = L
self.L_ = L_old
self.n_iter_ = it
return self

Expand Down