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New content on http://keras.io : Keras debugging tips.https://keras.io/examples/keras_recipes/debugging_tips/ …
1 - Test the parts before you test the whole 2 - Use `model.summary()` and `plot_model()` to check output shapes and connectivity graph 3 - Use `run_eagerly=True` in `compile()` to debug training step-by-step 4 - Use the TF profiler (simple callback) to fix performance issues
Also, yes -- if you ever find yourself needing second-order gradients when writing a Keras training step, this is how to get them:pic.twitter.com/FY7fm8eE2k
My personal favorite: print(http://K.int _shape(x))
Notebook is not available
Your "deep learning with python" book makes my life easier . What's your thoughts about "PyTorch" ?
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