BatchNormalization¶
- class
dragon.vm.tensorflow.keras.layers.
BatchNormalization
(
axis=- 1,
momentum=0.99,
epsilon=0.001,
center=True,
scale=True,
beta_initializer='zeros',
gamma_initializer='ones',
moving_mean_initializer='zeros',
moving_variance_initializer='ones',
beta_regularizer=None,
gamma_regularizer=None,
name=None,
**kwargs
)[source]¶ Batch normalization layer. [Ioffe & Szegedy, 2015].
__init__¶
BatchNormalization.
__init__
(
axis=- 1,
momentum=0.99,
epsilon=0.001,
center=True,
scale=True,
beta_initializer='zeros',
gamma_initializer='ones',
moving_mean_initializer='zeros',
moving_variance_initializer='ones',
beta_regularizer=None,
gamma_regularizer=None,
name=None,
**kwargs
)[source]¶Create a
BatchNormalization
layer.- Parameters:
- axis (int, optional, default=-1) – The channel axis.
- momentum (float, optional, default=0.99) – The decay factor of running average.
- epsilon (float, optional, default=1e-3) – The epsilon value.
- center (bool, optional, default=True) –
False
to freeze thebeta
anyway. - scale (bool, optional, default=True) –
False
to freeze thegamma
anyway. - beta_initializer (Union[callable, str], optional) – The initializer for beta tensor.
- gamma_initializer (Union[callable, str], optional) – The initializer for gamma tensor.
- moving_mean_initializer (Union[callable, str], optional) – The initializer for moving mean tensor.
- moving_variance_initializer (Union[callable, str], optional) – The initializer for moving variance tensor.
- beta_regularizer (Union[callable, str], optional) – The regularizer for beta tensor.
- gamma_regularizer (Union[callable, str], optional) – The regularizer for gamma tensor.