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TensorFlow: Difference between revisions
→Estimators
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While you can train using <code>model.compile</code> and <code>model.fit</code>, using your own custom training loop is much more flexable and easier to understand. | While you can train using <code>model.compile</code> and <code>model.fit</code>, using your own custom training loop is much more flexable and easier to understand. | ||
You can write your own training loop by doing the following: | You can write your own training loop by doing the following: | ||
<syntaxhighlight | <syntaxhighlight lang="python"> | ||
my_model= keras.Sequential([ | my_model= keras.Sequential([ | ||
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==Usage (TF1)== | ==Usage (TF1)== | ||
==Estimators== | |||
[https://towardsdatascience.com/first-contact-with-tensorflow-estimator-69a5e072998d First Contact w/ TF Estimator (TDS)]<br> | |||
===Training Statistics=== | |||
[https://stackoverflow.com/questions/48940155/tensorflow-is-there-a-way-to-store-the-training-loss-in-tf-estimator Reference]<br> | |||
You can extract the training loss from the events file in tensorflow. | |||