def __init__(self, input_size, layerSize, num_of_classes, learning_rate_local=0.001, save_file='',
activation_function=0, cov_net=False):
self.covnet = cov_net
self.input_size = input_size
self.layerSize = layerSize
self.all_layer_sizes = np.copy(layerSize)
self.all_layer_sizes = np.insert(self.all_layer_sizes, 0, input_size)
self.num_of_classes = num_of_classes
self._num_of_layers = len(layerSize) + 1
self.learning_rate_local = learning_rate_local
self._save_file = save_file
self.hidden = None
self.savers = []
if activation_function == 1:
self.activation_function = tf.nn.relu
elif activation_function == 2:
self.activation_function = None
else:
self.activation_function = tf.nn.tanh
self.prediction
self.optimize
self.accuracy
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