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View Code? Open in Web Editor NEWEnergy Management Using Real-Time Non-Intrusive Load Monitoring
License: MIT License
Energy Management Using Real-Time Non-Intrusive Load Monitoring
License: MIT License
Hello, thank you for providing this repository.
I was wondering if in the following code the activation function should be applied to x_fc1?
return self.fully_connected2(self.activation(x_fc1))
instead of return self.activation(self.fully_connected2(x_fc1))
original code lin 326:
https://github.com/goruck/nilm/blob/main/ml/transformer_model.py
class PositionwiseFeedForward(tf.keras.layers.Layer):
"""PositionwiseFeedForward layer.
This is an implementation of position wise feed-forward as described in the
paper "Attention is all you Need" (Vaswani et al., 2017)."""
def __init__(self, d_model, d_ff, **kwargs):
super().__init__(**kwargs)
self.fully_connected1 = tf.keras.layers.Dense(d_ff) # First fully connected layer
self.fully_connected2 = tf.keras.layers.Dense(d_model) # Second fully connected layer
self.activation = GELU()
def call(self, inputs, *args, **kwargs):
# The input is passed into the two fully-connected layers, with GELU activation.
x_fc1 = self.fully_connected1(inputs)
return self.activation(self.fully_connected2(x_fc1))
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