def compute_total_loss_test(target, Y):

pred = tf.constant([[ 2.4048107, 5.0334096 ],

[-0.7921977, -4.1523376 ],

[ 0.9447198, -0.46802214],

[ 1.158121, 3.9810789 ],

[ 4.768706, 2.3220146 ],

[ 6.1481323, 3.909829 ]])

minibatches = Y.batch(2)

for minibatch in minibatches:

result = target(pred, tf.transpose(minibatch))

break

```
print(result)
assert(type(result) == EagerTensor), "Use the TensorFlow API"
assert (np.abs(result - (0.50722074 + 1.1133534) / 2.0) < 1e-7), "Test does not match. Did you get the reduce sum of your loss functions?"
print("\033[92mAll test passed")
```

compute_total_loss_test(compute_total_loss, new_y_train )

Error:

## tf.Tensor(0.028503546, shape=(), dtype=float32)

AssertionError Traceback (most recent call last)

in

17 print(“\033[92mAll test passed”)

18

—> 19 compute_total_loss_test(compute_total_loss, new_y_train )

in compute_total_loss_test(target, Y)

13 print(result)

14 assert(type(result) == EagerTensor), “Use the TensorFlow API”

—> 15 assert (np.abs(result - (0.50722074 + 1.1133534) / 2.0) < 1e-7), “Test does not match. Did you get the reduce sum of your loss functions?”

16

17 print(“\033[92mAll test passed”)

AssertionError: Test does not match. Did you get the reduce sum of your loss functions?