lostoxygen / bioinf_kernel_eval

Performance Evaluation between Normal and Depthwise Seperable Convolutions for Medical Image Classification.

BioInformatics Kernel Evaluation

Performance Evaluation between Normal and Depthwise Seperable Convolutions for Medical Image Classification.

Usage:

python main.py [-h] [--gpu | -g DEVICE_ID] [--batch_size | -bs BATCH_SIZE] [--epochs | -e EPOCHS]

Example Usage:

python main.py --gpu 0 --batch_size 32 --epochs 100

Training Arguments

Argument	Type	Description
-h, --help	None	shows argument help message
-g, --gpu	INT	specifies device ID to use. [0, N] for GPU and -1 for CPU (default=-1)
-e, --epochs	INT	number of epochs to train (default=100)
-bs, --batch_size	INT	batch size (default=128)
-lr, --learning_rate	FLOAT	learning rate (default=0.1)
-m, --model_type	STRING	model type to use [vgg11, vgg13, vgg16, vgg19, resnet34] (default='vgg11')
-d, --depthwise	BOOL	use depthwise separable convolutions (default=False)
-ev, --eval_only	BOOL	evaluate model only (default=False)

Project Poster: