Hi,

I’m on the programming assignment in week 3, specifically at 5.2 - Test the Model on the Planar Dataset

Everything so far works and I have passed all the tests.

However when I run the cell(no solution here, we just have to run the cell)

# Build a model with a n_h-dimensional hidden layer

parameters = nn_model(X, Y, n_h = 4, num_iterations = 10000, print_cost=True)

# Plot the decision boundary

plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)

plt.title("Decision Boundary for hidden layer size " + str(4))

## I get this output with the error. It looks like a error coming out of the grader, and not through student code:

Cost after iteration 0: 0.693162

Cost after iteration 1000: 0.258625

Cost after iteration 2000: 0.239334

Cost after iteration 3000: 0.230802

Cost after iteration 4000: 0.225528

Cost after iteration 5000: 0.221845

Cost after iteration 6000: 0.219094

Cost after iteration 7000: 0.220661

Cost after iteration 8000: 0.219409

Cost after iteration 9000: 0.218485

AttributeError Traceback (most recent call last)

in

3

4 # Plot the decision boundary

----> 5 plot_decision_boundary(lambda x: predict(parameters, x.T), X, Y)

6 plt.title("Decision Boundary for hidden layer size " + str(4))

~/work/release/W3A1/planar_utils.py in plot_decision_boundary(model, X, y)

14 # Predict the function value for the whole grid

15 Z = model(np.c_[xx.ravel(), yy.ravel()])

—> 16 Z = Z.reshape(xx.shape)

17 # Plot the contour and training examples

18 plt.contourf(xx, yy, Z, cmap=plt.cm.Spectral)

AttributeError: ‘list’ object has no attribute ‘reshape’

Let me know if anyone else faced a similar problem, or any fixed, or if I’m going wrong somewhere

Thanks!