Fix 3 documentation issues in basic_training_loops guide#2429
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Jah-yee wants to merge 1 commit intotensorflow:masterfrom
Open
Fix 3 documentation issues in basic_training_loops guide#2429Jah-yee wants to merge 1 commit intotensorflow:masterfrom
Jah-yee wants to merge 1 commit intotensorflow:masterfrom
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1. Fixed incorrect color description (cell 17): 'predictions in red and the training data in blue' → 'predictions and the training data' (No explicit colors are set in the plotting code) 2. Improved gradient variable naming for clarity (cell 20): dw, db → grad_w, grad_b (Avoids confusion with weight/bias variables) 3. Fixed Keras save_weights filename bug (cell 30): 'my_checkpoint' → 'my_checkpoint.weights.h5' (Keras requires .weights.h5 extension) Reported via: tensorflow/tensorflow#116299
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PreviewPreview and run these notebook edits with Google Colab: Rendered notebook diffs available on ReviewNB.com.Format and styleUse the TensorFlow docs notebook tools to format for consistent source diffs and lint for style:$ python3 -m pip install -U --user git+https://github.com/tensorflow/docsIf commits are added to the pull request, synchronize your local branch: git pull origin fix-tensorflow-docs-issues
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Good day,
I noticed three issues while reviewing the basic_training_loops guide and would like to propose the following fixes:
Fix 1: Incorrect color description in visualization text
In the markdown cell before the first plotting example, the text incorrectly states that predictions are shown "in red" and training data "in blue", but the actual code uses default matplotlib colors with no explicit color specification.
Before: "Before training the model, you can visualize the loss value by plotting the model's predictions in red and the training data in blue:"
After: "Before training the model, you can visualize the loss value by plotting the model's predictions and the training data:"
Fix 2: Improved gradient variable naming for clarity
In the train function, the gradient variables were named
dwanddb, which could be confused with the weight and bias variables (model.w,model.b). Renamed tograd_wandgrad_bto clearly indicate they are gradients, matching the standard gradient descent notation.Fix 3: Keras save_weights filename bug
The code
keras_model.save_weights("my_checkpoint")produces aValueErrorbecause Kerassave_weightsrequires the explicit.weights.h5extension. Changed tokeras_model.save_weights("my_checkpoint.weights.h5").These issues were reported by a reader in tensorflow/tensorflow#116299.
Thank you for your attention. If there are any issues or suggestions, please leave a comment and I will address them promptly.
Warmly,
RoomWithOutRoof