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Your scaled_attention_logits is calculated wrong, since it gives:
scaled_attention_logits
--------------------------------------------------------------------------- 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,
The text was updated successfully, but these errors were encountered:
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Your
scaled_attention_logits
is calculated wrong, since it gives:The correct value should be:
Cheers,
The text was updated successfully, but these errors were encountered: