CODEWITHSUNDEEP
pythontensorflowinteractive-shell
F.S.
F.S.

Reputation: 1261

tf.InteractiveSession() or tf.enable_eager_execution()

This is a beginner question on learning Tensorflow. I'm used to playing around machine learning models in interactive shell like Jupyter notebook. I understand tensorflow adopts the lazy execution style, so I can't easily print tensors to check.

After some research, I found two work around: tf.InteractiveSession() or tf.enable_eager_execution(). From what I understand, both allow me to print variables as I write them. Is this correct? And is there a preference?

Upvotes: 0

Views: 571

Answers (1)

Srikar
Srikar

Reputation: 112

When using tf.InteractiveSession() you are still in lazy execution. So you can't print variable values. You only can get to see symbols.

sess = tf.InteractiveSession()
a = tf.random.uniform(shape=(2,3))
print(a) # <tf.Tensor 'random_uniform:0' shape=(2, 3) dtype=float32>

When using tf.enable_eager_execution() you can get to see variable values.

tf.enable_eager_execution()
a = tf.random.uniform(shape=(2,3))
print(a) # prints out value

Upvotes: 1

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