def __init__(self, kernel_size, strides=(1, 1), padding='valid', depth_multiplier=1, data_format=None, activation=None, use_bias=True, depthwise_initializer='glorot_uniform', bias_initializer='zeros', depthwise_regularizer=None, bias_regularizer=None, activity_regularizer=None, depthwise_constraint=None, bias_constraint=None, **kwargs):
    super(DepthwiseConv2D, self).__init__(filters=None, kernel_size=kernel_size, strides=strides, padding=padding, data_format=data_format, activation=activation, use_bias=use_bias, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, bias_constraint=bias_constraint, **kwargs)
    self.depth_multiplier = depth_multiplier
    self.depthwise_initializer = initializers.get(depthwise_initializer)
    self.depthwise_regularizer = regularizers.get(depthwise_regularizer)
    self.depthwise_constraint = constraints.get(depthwise_constraint)
    self.bias_initializer = initializers.get(bias_initializer)
def __init__(self, kernel_size, strides=(1, 1), padding='valid', depth_multiplier=1, data_format=None, activation=None, use_bias=True, depthwise_initializer='glorot_uniform', bias_initializer='zeros', depthwise_regularizer=None, bias_regularizer=None, activity_regularizer=None, depthwise_constraint=None, bias_constraint=None, **kwargs):
    super(DepthwiseConv2D, self).__init__(filters=None, kernel_size=kernel_size, strides=strides, padding=padding, data_format=data_format, activation=activation, use_bias=use_bias, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, bias_constraint=bias_constraint, **kwargs)
    self.depth_multiplier = depth_multiplier
    self.depthwise_initializer = initializers.get(depthwise_initializer)
    self.depthwise_regularizer = regularizers.get(depthwise_regularizer)
    self.depthwise_constraint = constraints.get(depthwise_constraint)
    self.bias_initializer = initializers.get(bias_initializer)