C5 W4 A1 Encoder Layer isn't working

Course Q&A Deep Learning Specialization Sequence Models
1

I think I have followed the steps pretty well but I can’t see why it is wrong.

def call(self, x, training, mask):
        """
        Forward pass for the Encoder Layer
        
        Arguments:
            x -- Tensor of shape (batch_size, input_seq_len, fully_connected_dim)
            training -- Boolean, set to true to activate
                        the training mode for dropout layers
            mask -- Boolean mask to ensure that the padding is not 
                    treated as part of the input
        Returns:
            encoder_layer_out -- Tensor of shape (batch_size, input_seq_len, fully_connected_dim)
        """
        # START CODE HERE
        # calculate self-attention using mha(~1 line). Dropout will be applied during training
        attn_output = self.mha(x, x, x, mask, training=training) # Self attention (batch_size, input_seq_len, fully_connected_dim)
        
        # apply layer normalization on sum of the input and the attention output to get the  
        # output of the multi-head attention layer (~1 line)
        out1 = self.layernorm1(x + attn_output)  # (batch_size, input_seq_len, fully_connected_dim)

        # pass the output of the multi-head attention layer through a ffn (~1 line)
        ffn_output = self.ffn(out1)  # (batch_size, input_seq_len, fully_connected_dim)
        
        # apply dropout layer to ffn output during training (~1 line)
        ffn_output =  self.dropout_ffn(out1, training=training)
        
        # apply layer normalization on sum of the output from multi-head attention and ffn output to get the
        # output of the encoder layer (~1 line)
        encoder_layer_out = self.layernorm2(out1 + ffn_output)  # (batch_size, input_seq_len, fully_connected_dim)
        # END CODE HERE
        
        return encoder_layer_out

error msg:

---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-57-00617004b1af> in <module>
      1 # UNIT TEST
----> 2 EncoderLayer_test(EncoderLayer)

~/work/W4A1/public_tests.py in EncoderLayer_test(target)
     92                        [[ 0.23017104, -0.98100424, -0.78707516,  1.5379084 ],
     93                        [-1.2280797 ,  0.76477575, -0.7169283 ,  1.1802323 ],
---> 94                        [ 0.14880152, -0.48318022, -1.1908402 ,  1.5252188 ]]), "Wrong values when training=True"
     95 
     96     encoded = encoder_layer1(q, False, np.array([[1, 1, 0]]))

AssertionError: Wrong values when training=True

UPDATE: I have tried submitting the file and I get 0/100 although all the previous tests have passed

2

self.mha(…) does not need a training argument.
In self.dropout(…), “out1” is not the ffn output.