What is the difference between tf.nn.dropout() vs tf.layers.dropout()?
I'm using dropout with TensorFlow and couldn't get what is the difference between nn.dropout and layers.dropout.
I'm using dropout with TensorFlow and couldn't get what is the difference between nn.dropout and layers.dropout.
They are almost the same. as they do not have trainable parameters, there is no difference.
Dropout only needs a flag about evaluation or training regimes.