What are some effective debugging tips for TensorFlow?
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What are some effective debugging tips for TensorFlow?
Here are a few tips: 1. Use TensorFlow's built-in debugging tools like tf.debugging. 2. Check for NaNs and Infs in your tensors. 3. Visualize your model with TensorBoard.
How can I check for NaNs in my tensors?
You can use tf.debugging.check_numerics(tensor, message) to check for NaNs and Infs in your tensors.
What should I do if I find NaNs in my model?
If you find NaNs, check your data for invalid values, adjust your learning rate, or try gradient clipping.
Can TensorBoard help with debugging?
Absolutely! TensorBoard can help visualize your model's performance and identify issues in training.
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