How to print weights in Tensorflow?

Question

I am trying to get the weight matrix of my hidden_layer2 and print it. It seems like I am able to get the weight matrix, but I am not able to print it.

When using tf.Print(w, [w]) it prints nothing. When using print(tf.Print(w,[w]) it prints at least the info about the tensor:

Tensor("hidden_layer2_2/Print:0", shape=(3, 2), dtype=float32)

I also tried to use tf.Print() outside of the with-Statement, same result.

Full code is here, I am just processing random data in a feed-forward NN: https://pastebin.com/KiQUBqK4

A part of my Code:

hidden_layer2 = tf.layers.dense(
        inputs=hidden_layer1,
        units=2,
        activation=tf.nn.relu,
        name="hidden_layer2")


with tf.variable_scope("hidden_layer2", reuse=True):
        w = tf.get_variable("kernel")
        tf.Print(w, [w])
        # Also tried tf.Print(hidden_layer2, [w])

Answer 1

UPDATED FOR TENSORFLOW 2.X

Starting from TensorFlow 2.0 (>= 2.0), since the Session object has been removed and the recommended high-level backend is Keras, the way to do get the weights is:

from tensorflow.keras.applications import MobileNetV2

model = MobileNetV2(input_shape=[128, 128, 3], include_top=False) #or whatever model
print(model.layers[0].get_weights()[0])

Answer 2

I believe there are multiple issues to be tackled here.

1. Running eval() should be accompanied by a session. As suggested in In TensorFlow, what is the difference between Session.run() and Tensor.eval()?, .eval() expects a default session to be running which was not likely in your case earlier. So, the best option here was to precede the code with a session. From your comment, we can see that this is done.

2. The variables in the hidden layers (i.e. weights/kernels) need to be initialized once the graph is complete. Hence, you might want to use something similar to this:

   
   init = tf.global_variables_initializer()
   sess = tf.Session()
   sess.run(init)
   with tf.variable_scope("hidden_layer2", reuse=True):
       w = tf.get_variable("kernel")
       print(w.eval(session=sess))