A code I'm modifying is using tf.get_variable
for weight variables, and tf.Variable
for bias initialisation. After some searching, it seems that get_variable
should always be favoured due to its portability in regards to sharing. So I tried to change the bias variable to get_variable
but can't seem to get it to work.
Original: tf.Variable(tf.zeros([128]), trainable=True, name="b1")
My attempt: tf.get_variable(name="b1", shape=[128], initializer=tf.zeros_initializer(shape=[128]))
I get an error saying that the shape should not be specified for constants. But removing the shape then throws an error for no arguments.
I'm very new to tf
so I'm probably misunderstanding something fundamental here. Thanks for the help in advance :)
Following should work:
tf.get_variable(name="b1", shape=[128], initializer=tf.zeros_initializer())