Hi,

I am following: LINEAR → RELU → LINEAR → RELU → LINEAR

in # GRADED FUNCTION: forward_propagation

**def forward_propagation(X, parameters):** function after doing this:

# YOUR CODE STARTS HERE

```
Z1 = tf.math.add(tf.linalg.matmul(W1, X), b1) # Z1 = np.dot(W1, X) + b1
A1 = tf.keras.activations.relu(Z1) # A1 = relu(Z1)
Z2 = tf.math.add(tf.linalg.matmul(W2, A1), b2) # Z2 = np.dot(W2, a1) + b2
A2 = tf.keras.activations.relu(Z2) # A2 = relu(Z2)
Z3 = tf.math.add(tf.linalg.matmul(W3, A2), b3) # Z3 = np.dot(W3,Z2) + b3
# YOUR CODE ENDS HERE
```

Getting following error:

NameError Traceback (most recent call last)

in

18 print("\033[92mAll test passed")

19

—> 20 forward_propagation_test(forward_propagation, new_train)

in forward_propagation_test(target, examples)

2 minibatches = examples.batch(2)

3 for minibatch in minibatches:

----> 4 forward_pass = target(tf.transpose(minibatch), parameters)

5 print(forward_pass)

6 assert type(forward_pass) == EagerTensor, “Your output is not a tensor”

NameError: name ‘parameters’ is not defined