Calculate Parameter Count for Grouped Convolutions

Implement a function to calculate the parameter count ratio between grouped convolutions and standard convolutions. Grouped convolutions are a technique used in ConvNext architectures to reduce computational costs by splitting input and output channels into $G$ groups, where each group operates on a subset of the channels.

This process can be broken down into the following steps:

1. Determine the number of parameters in a standard convolution, given by $K_W \times K_H \times C_{in} \times C_{out}$.
2. Calculate the number of parameters in a grouped convolution, where each of the $G$ groups operates on $C_{in}/G$ input channels producing $C_{out}/G$ output channels. The key formula for the ratio of parameters is

This technique is widely used in deep learning models for image classification tasks.