I want the input of each convolutional layer to be the output of its previous layer multiplied by an adaptive multiple. The model is ResNet50 in torchvision.models.
For example, there is a three layers CNN: Conv1, Conv2, Conv3.
The first iteration:
the_input_of_Conv2 =  1.31 * the_output_of_Conv1
the_input_of_Conv3 =  1.24 * the_output_of_Conv2 
The second iteration:
the_input_of_Conv2 =  1.40 * the_output_of_Conv1
the_input_of_Conv3 =  1.27 * the_output_of_Conv2 
The third iteration:
..............
and so on ......

The above figures 1.31, 1.24, 1.40 and 1.27 are just an example. The exact multiple can be calculated in the program.
Dose anyone know how to achieve this forward propagation?
Thanks!