(self, input)
return output
input: (samples_num, freq_bins, time_steps, 1)
input: (samples_num, freq_bins, time_steps, 1)
input : ( samples_num freq_bins time_steps 1 )
def forward(self, input):
        """input: (samples_num, freq_bins, time_steps, 1)
        """
        drop_rate = self.drop_rate

        # (samples_num, hidden_units, time_steps, 1)
        b1 = self.emb(input)

        # (samples_num, hidden_units)
        b2 = self.attention(b1)
        b2 = F.dropout(
            F.relu(
                self.bn_attention(b2)),
            p=drop_rate,
            training=self.training)

        # (samples_num, classes_num)
        output = F.sigmoid(self.fc_final(b2))

        return output
def forward ( self , input ) : drop_rate = self . drop_rate # (samples_num, hidden_units, time_steps, 1) b1 = self . emb ( input ) # (samples_num, hidden_units) b2 = self . attention ( b1 ) b2 = F . dropout ( F . relu ( self . bn_attention ( b2 ) ) , p = drop_rate , training = self . training ) # (samples_num, classes_num) output = F . sigmoid ( self . fc_final ( b2 ) ) return output