estimators_blog_cnn_classifer.py

training = (mode == tf.estimator.ModeKeys.TRAIN)
dropout_emb = tf.layers.dropout(inputs=input_layer, 
                                rate=0.2, 
                                training=training)
conv = tf.layers.conv1d(
    inputs=dropout_emb,
    filters=32,
    kernel_size=3,
    padding="same",
    activation=tf.nn.relu)
pool = tf.reduce_max(input_tensor=conv, axis=1)
hidden = tf.layers.dense(inputs=pool, units=250, activation=tf.nn.relu)
dropout = tf.layers.dropout(inputs=hidden, rate=0.2, training=training)
logits = tf.layers.dense(inputs=dropout_hidden, units=1)