cifar.py 文件源码

def conv(self, inputs, num_outputs, activations, normalizer_fn = batch_norm, kernel_size=3, stride=1, scope=None):
        '''Creates a convolutional layer with default arguments'''
        if activations == 'relu':
            activation_fn = tf.nn.relu
        elif activations == 'softplus':
            activation_fn = tf.nn.softplus
        else:
            raise ValueError("Invalid activation function.")
        return conv2d( inputs = inputs,
            num_outputs = num_outputs,
            kernel_size = kernel_size,
            stride = stride,
            padding = 'SAME',
            activation_fn = activation_fn,
            normalizer_fn = normalizer_fn,
            normalizer_params = {'is_training' : self.is_training, 'updates_collections': None, 'decay': 0.9},
            scope=scope )