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In your code feedforward function of module.py,
line 297:
outputs = tf.contrib.layers.fully_connected(**params)
line 301:
params = {"inputs": inputs, "num_outputs": num_units[1], "activation_fn": None}
I guess the key "inputs" of dict params at line 301 correspond to the value is outputs at line 297, according the fomulate: FFN(x) = max(0, xW1+b1)W2+b2 at fifth page in paper "Attention is all you need".
The text was updated successfully, but these errors were encountered:
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I have some doubts about the function feedforward in module.py
I have some doubts about the function feedforward in modules.py
Mar 21, 2019
In your code feedforward function of module.py,
line 297:
outputs = tf.contrib.layers.fully_connected(**params)
line 301:
params = {"inputs": inputs, "num_outputs": num_units[1], "activation_fn": None}
I guess the key "inputs" of dict params at line 301 correspond to the value is outputs at line 297, according the fomulate: FFN(x) = max(0, xW1+b1)W2+b2 at fifth page in paper "Attention is all you need".
The text was updated successfully, but these errors were encountered: