I'm getting started with TensorFlow. http://ift.tt/2hUWjxq
While I was evaluating multiple times seeing how to feed the data, I found that the loss changes with executions.
eval_input_fn = tf.contrib.learn.io.numpy_input_fn({"x":x}, y, batch_size=4,
num_epochs=1)
estimator.evaluate(input_fn = eval_input_fn)
For example, I had losses following:
0.024675447 or 0.030844312 when batch_size == 2, num_epochs == 2
0.020562874 or 0.030844312 when batch_size == 4, num_epochs == 2
0.015422156 or 0.030844312 when batch_size == 4, num_epochs == 1
Is this phenomenon normal? I do not understand the principle behind it.
Aucun commentaire:
Enregistrer un commentaire