In the code，the inputs of all the 11 conv layers in a dense block concatenate the output of the transition layer.
However, I calculated the parameters of the Densenet121. If the inputs of all the 11 conv layers in a dense block concatenate the output of the transition layer, the parameters are about 13M, but it
is not larger than 10M in the paper (Densely Connected Convolutional Networks). if the inputs of all 11 layers in a dense block do not include the output of transition layer？ The parameters are about 8.8M. So I think that the inputs of all 11 layers in a dense block do not include the outputs of the transition layer.
In the code，the inputs of all the 11 conv layers in a dense block concatenate the output of the transition layer. However, I calculated the parameters of the Densenet121. If the inputs of all the 11 conv layers in a dense block concatenate the output of the transition layer, the parameters are about 13M, but it is not larger than 10M in the paper (Densely Connected Convolutional Networks). if the inputs of all 11 layers in a dense block do not include the output of transition layer？ The parameters are about 8.8M. So I think that the inputs of all 11 layers in a dense block do not include the outputs of the transition layer.