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fix compatibility issues with newer keras version #11

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fix compatibility issues with newer keras version #11

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26 changes: 11 additions & 15 deletions keras/weightnorm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@

# adapted from keras.optimizers.SGD
class SGDWithWeightnorm(SGD):
def get_updates(self, params, constraints, loss):
def get_updates(self, params, loss):
grads = self.get_gradients(loss, params)
self.updates = []

Expand Down Expand Up @@ -47,9 +47,8 @@ def get_updates(self, params, constraints, loss):
new_V_param = V + v_v

# if there are constraints we apply them to V, not W
if p in constraints:
c = constraints[p]
new_V_param = c(new_V_param)
if getattr(p, 'constraint', None) is not None:
new_V_param = p.constraint(new_V_param)

# wn param updates --> W updates
add_weightnorm_param_updates(self.updates, new_V_param, new_g_param, p, V_scaler)
Expand All @@ -64,24 +63,23 @@ def get_updates(self, params, constraints, loss):
new_p = p + v

# apply constraints
if p in constraints:
c = constraints[p]
new_p = c(new_p)
if getattr(p, 'constraint', None) is not None:
new_p = p.constraint(new_p)

self.updates.append(K.update(p, new_p))
return self.updates

# adapted from keras.optimizers.Adam
class AdamWithWeightnorm(Adam):
def get_updates(self, params, constraints, loss):
def get_updates(self, params, loss):
grads = self.get_gradients(loss, params)
self.updates = [K.update_add(self.iterations, 1)]

lr = self.lr
if self.initial_decay > 0:
lr *= (1. / (1. + self.decay * self.iterations))

t = self.iterations + 1
t = tf.to_float(self.iterations + 1)
lr_t = lr * K.sqrt(1. - K.pow(self.beta_2, t)) / (1. - K.pow(self.beta_1, t))

shapes = [K.get_variable_shape(p) for p in params]
Expand Down Expand Up @@ -119,9 +117,8 @@ def get_updates(self, params, constraints, loss):
self.updates.append(K.update(v, v_t))

# if there are constraints we apply them to V, not W
if p in constraints:
c = constraints[p]
new_V_param = c(new_V_param)
if getattr(p, 'constraint', None) is not None:
new_p = p.constraint(new_p)

# wn param updates --> W updates
add_weightnorm_param_updates(self.updates, new_V_param, new_g_param, p, V_scaler)
Expand All @@ -136,9 +133,8 @@ def get_updates(self, params, constraints, loss):

new_p = p_t
# apply constraints
if p in constraints:
c = constraints[p]
new_p = c(new_p)
if getattr(p, 'constraint', None) is not None:
new_p = p.constraint(new_p)
self.updates.append(K.update(p, new_p))
return self.updates

Expand Down