I have some neural network (tensorflow)
n_steps = 10
n_inputs = 3
n_outputs = 1
n_neurons = 100
n_layers = 3
X = tf.placeholder(tf.float32, [None, n_steps, n_inputs])
y = tf.placeholder(tf.float32, [None, n_steps, n_outputs])
layers = []
for i in range(n_layers):
layers.append(tf.contrib.rnn.BasicRNNCell(num_units=n_neurons, activation=tf.nn.relu))
multi_layer_cell = tf.contrib.rnn.MultiRNNCell(layers)
rnn_outputs, states = tf.nn.dynamic_rnn(multi_layer_cell, X, dtype=tf.float32)
Like this (below) is correct? It is working but i'm not sure ;)
training = tf.placeholder_with_default(True,shape=())
X_dropout = tf.layers.dropout(X,dropout_rate,training=training)
rnn_outputs, states = tf.nn.dynamic_rnn(multi_layer_cell, X_dropout, dtype=tf.float32)
How to add into this neural network tensorflow dropout?
Thanks for any sugestions!