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idata
Community Manager
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How to do simple operations on the input ? (add, or multiply with a constant tensor) [Tensorflow]

Hi,

 

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 :

 

tf.reset_default_graph() 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([ [ [ [1],[1] ], [ [1], [1] ] ] ], name='testvar', dtype=tf.float32) Z = tf.math.add(Y, X, name="out037") init_op = tf.global_variables_initializer() with tf.Session() as sess: sess.run(init_op) saver = tf.train.Saver(tf.global_variables()) saver.save(sess, './test/test')

 

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 ?

 

Thank you in advance !

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