coursera-deep-learning-specialization
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C5_W4_A1_Transformer_EX3_scaled_attention_logits
Your scaled_attention_logits
is calculated wrong, since it gives:
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-41-00665b20febb> in <module>
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)
73 assert np.allclose(weights, [[0.30719590187072754, 0.5064803957939148, 0.0, 0.18632373213768005],
74 [0.3836517333984375, 0.3836517333984375, 0.0, 0.2326965481042862],
---> 75 [0.3836517333984375, 0.3836517333984375, 0.0, 0.2326965481042862]]), "Wrong masked weights"
76 assert np.allclose(attention, [[0.6928040981292725, 0.18632373213768005],
77 [0.6163482666015625, 0.2326965481042862],
AssertionError: Wrong masked weights
The correct value should be:
if mask is not None: # Don't replace this None
scaled_attention_logits += ( (1-mask) * -1e9 )
Cheers,