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Fix 3 documentation issues in basic_training_loops guide #2429

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Fix 3 documentation issues in basic_training_loops guide #2429

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12 changes: 6 additions & 6 deletions site/en/guide/basic_training_loops.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -266,7 +266,7 @@
"id": "-50nq-wPBsAW"
},
"source": [
"Before training the model, you can visualize the loss value by plotting the model's predictions in red and the training data in blue:"
"Before training the model, you can visualize the loss value by plotting the model's predictions and the training data:"
]
},
{
Expand Down Expand Up @@ -322,11 +322,11 @@
" current_loss = loss(y, model(x))\n",
"\n",
" # Use GradientTape to calculate the gradients with respect to W and b\n",
" dw, db = t.gradient(current_loss, [model.w, model.b])\n",
" grad_w, grad_b = t.gradient(current_loss, [model.w, model.b])\n",
"\n",
" # Subtract the gradient scaled by the learning rate\n",
" model.w.assign_sub(learning_rate * dw)\n",
" model.b.assign_sub(learning_rate * db)"
" model.w.assign_sub(learning_rate * grad_w)\n",
" model.b.assign_sub(learning_rate * grad_b)"
]
},
{
Expand Down Expand Up @@ -491,7 +491,7 @@
"training_loop(keras_model, x, y)\n",
"\n",
"# You can also save a checkpoint using Keras's built-in support\n",
"keras_model.save_weights(\"my_checkpoint\")"
"keras_model.save_weights(\"my_checkpoint.weights.h5\")"
]
},
{
Expand Down Expand Up @@ -595,4 +595,4 @@
},
"nbformat": 4,
"nbformat_minor": 0
}
}