Installation

Clone this repository and install the dependencies:

git clone https://github.com/liangchingyun/A-Convolution-Module-For-Variable-Input-Channels.git

cd A-Convolution-Module-For-Variable-Input-Channels

pip install -r requirements.txt

Running Jupyter Notebook

Make sure you have Jupyter Notebook installed. If not, you can install it using the following command:

pip install jupyter

Navigate to the cloned repository directory and open the main.ipynb file.

Modifying Training Parameters

You can modify the training parameters below to customize your training process. Here's a brief description of each parameter:

• batch_size: The batch size used for training.
• test_batch_size: The batch size used for testing.
• epochs: The number of epochs to train the model.
• learning_rate: The learning rate used by the optimizer.
• momentum: The momentum used by the optimizer.
• weight_decay: The weight decay (L2 penalty) applied to the model parameters.

To change these parameters, simply update their values in the code cell below.

parser.add_argument('--batch-size', type=int, default=256)
parser.add_argument('--test-batch-size', type=int, default=20)
parser.add_argument('--epochs', type=int, default=100)
parser.add_argument('--lr', type=float, default=0.1, )
parser.add_argument('--momentum', type=float, default=0.9)
parser.add_argument('--weight-decay', type=float, default=1e-4)
parser.add_argument('--net-name', default='resnet18')
parser.add_argument('--channel', default='RG')