class MVCallback(Callback):
'''
Please use MVCallback as a callback of keras model.fit function
For e.g.
```
model.fit(X_train, Y_train,
batch_size=batch_size,
nb_epoch=nb_epoch,
validation_data=(X_test, Y_test),
shuffle=True,
callbacks=[mvcallback(model, freq=1)])
```
'''
def __init__(self, model, freq=1):
'''Initialize the MVCallback class
The `model` should be the be a keras model
The `freq` should be the update frequency of the parameters. For
example, `freq=3` means update the parameters every 3 mini-batch.
'''
super(MVCallback, self).__init__()
self.kpm = KerasParamManager(model)
self.cur_n = 0
if freq < 0:
raise ValueError("Frequency must be an integer greater than 0.")
self.freq = freq
def on_batch_end(self, batch, logs={}):
'''sync all parameters at the end of every batch'''
self.cur_n = (self.cur_n + 1) % self.freq
if self.cur_n % self.freq == 0:
self.kpm.sync_all_param()
def __init__(self, model, freq=1):
'''Initialize the MVCallback class
The `model` should be the be a keras model
The `freq` should be the update frequency of the parameters. For
example, `freq=3` means update the parameters every 3 mini-batch.
'''
super(MVCallback, self).__init__()
self.kpm = KerasParamManager(model)
self.cur_n = 0
if freq < 0:
raise ValueError("Frequency must be an integer greater than 0.")
self.freq = freq
class MVCallback(Callback):
'''
Please use MVCallback as a callback of keras model.fit function
For e.g.
```
model.fit(X_train, Y_train,
batch_size=batch_size,
nb_epoch=nb_epoch,
validation_data=(X_test, Y_test),
shuffle=True,
callbacks=[mvcallback(model)])
```
'''
def __init__(self, model):
super(MVCallback, self).__init__()
self.kpm = KerasParamManager(model)
def on_batch_end(self, batch, logs={}):
'''sync all parameters at the end of every batch'''
self.kpm.sync_all_param()
def __init__(self, model):
super(MVCallback, self).__init__()
self.kpm = KerasParamManager(model)