How to do simple operations on the input ? (add, or multiply with a constant tensor) [Tensorflow]
I would like to know if it is possible to do "simple" operations like adding or multiplying with a constant tensor ?
I tried this model :
X = tf.placeholder(dtype=tf.float32, shape=(1,2,2,1), name = "in037") # note: I also tried to declare this one as a variable
Y = tf.Variable([ [ [ , ], [ ,  ] ] ], name='testvar', dtype=tf.float32)
Z = tf.math.add(Y, X, name="out037")
init_op = tf.global_variables_initializer()
with tf.Session() as sess:
saver = tf.train.Saver(tf.global_variables())
I may be doing something wrong, but I get errors, like if the compiler did not like the second variable declared. (I also checked with "--new-parser" by curiosity, but it break the assertion that a node can't have more than one producer (that feels actually weird, but I guess it's still a work in progress anyway) )
If it's not possible, where can I find a precise list of all the constraints and supported operations, etc ?