train_catastrophe_model_human.py 文件源码

def model(self, features, labels):
        x = features["observation"]
        x = tf.contrib.layers.convolution2d(x, 2, kernel_size=[3, 3], stride=[2, 2], activation_fn=tf.nn.elu)
        x = tf.contrib.layers.convolution2d(x, 2, kernel_size=[3, 3], stride=[2, 2], activation_fn=tf.nn.elu)
        x = tf.contrib.layers.flatten(x)
        x = tf.contrib.layers.fully_connected(x, 100, activation_fn=tf.nn.elu)
        x = tf.contrib.layers.fully_connected(x, 100, activation_fn=tf.nn.elu)
        logits = tf.contrib.layers.fully_connected(x, 1, activation_fn=None)
        prediction = tf.sigmoid(logits)
        loss = tf.reduce_mean(tf.nn.sigmoid_cross_entropy_with_logits(logits, tf.expand_dims(labels, axis=1)))
        train_op = tf.contrib.layers.optimize_loss(
          loss, tf.contrib.framework.get_global_step(), optimizer='Adam',
          learning_rate=0.01)
        tf.add_to_collection('prediction', prediction)
        tf.add_to_collection('loss', loss)
        return prediction, loss, train_op