## hi, I am having issues with final exercise w4. I am getting the following error and the grader output is not given much details.

AssertionError Traceback (most recent call last)

in

1 # UNIT TEST

----> 2 scaled_dot_product_attention_test(scaled_dot_product_attention)

~/work/W4A1/public_tests.py in scaled_dot_product_attention_test(target)

60 assert np.allclose(weights, [[0.2589478, 0.42693272, 0.15705977, 0.15705977],

61 [0.2772748, 0.2772748, 0.2772748, 0.16817567],

—> 62 [0.33620113, 0.33620113, 0.12368149, 0.2039163 ]])

63

64 assert tf.is_tensor(attention), “Output must be a tensor”

AssertionError:

I printing both output and attention weight variables and both are tf.tensors.

tf.Tensor(

[[0.7464066 0.23822893]

[0.7461551 0.23846523]

[0.7383507 0.24579675]], shape=(3, 2), dtype=float32)

tf.Tensor(

[[0.2535934 0.26994875 0.23822893 0.23822893]

[0.25384492 0.25384492 0.25384492 0.23846523]

[0.26164928 0.26164928 0.23090468 0.24579675]], shape=(3, 4), dtype=float32)

have you an idea what could be wrong?

this is my implementation:

matmul_qk = tf.linalg.matmul(q, k, transpose_b=True) # (…, seq_len_q, seq_len_k)

```
dk = k.shape[-2]
scaled_attention_logits = tf.divide(matmul_qk,dk**2)
if mask is not None: # Don't replace this None
scaled_attention_logits += (1.0-mask)*-1e9
attention_weights = tf.keras.activations.softmax(scaled_attention_logits)
output = tf.linalg.matmul(attention_weights,v)
```