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update cli

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Vladimir Mandic
2023-05-13 15:21:00 -04:00
parent c46f0dbdeb
commit 819d105d1d
42 changed files with 198 additions and 2640 deletions
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cli/train/train.py
+20 -19
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@@ -46,8 +46,6 @@ lycoris_path = os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir
sys.path.append(lycoris_path)
import train_network
print('HERE6')
# globals
args = None
valid_steps = ['original', 'face', 'body', 'blur', 'range', 'upscale', 'restore', 'interrogate', 'resize', 'square', 'segment']
@@ -69,26 +67,29 @@ def mem_stats():
def parse_args():
global args # pylint: disable=global-statement
parser = argparse.ArgumentParser(description = 'train')
# basic section
parser.add_argument('--type', type=str, choices=['embedding', 'lora', 'lycoris', 'dreambooth'], default=None, required=True, help='training type')
parser.add_argument('--name', type=str, default=None, required=True, help='output filename')
parser.add_argument('--overwrite', default = False, action='store_true', help = "overwrite existing training, default: %(default)s")
parser.add_argument('--tag', type=str, default='person', required=False, help='primary tags, default: %(default)s')
parser.add_argument('--input', type=str, default=None, required=True, help='input folder with training images')
parser.add_argument('--output', type=str, default='', required=False, help='where to store processed images, default is system temp/train')
parser.add_argument('--process', type=str, default='original,interrogate,resize,square', required=False, help=f'list of possible processing steps: {valid_steps}, default: %(default)s')
parser = argparse.ArgumentParser(description = 'Train')
# global params
parser.add_argument('--gradient', type=int, default=1, required=False, help='gradient accumulation steps, default: %(default)s')
parser.add_argument('--steps', type=int, default=2500, required=False, help='training steps, default: %(default)s')
parser.add_argument('--batch', type=int, default=1, required=False, help='batch size, default: %(default)s')
parser.add_argument('--lr', type=float, default=1e-04, required=False, help='model learning rate, default: %(default)s')
parser.add_argument('--dim', type=int, default=40, required=False, help='network dimension or number of vectors, default: %(default)s')
group_main = parser.add_argument_group('Main')
group_main.add_argument('--type', type=str, choices=['embedding', 'lora', 'lycoris', 'dreambooth'], default=None, required=True, help='training type')
group_main.add_argument('--name', type=str, default=None, required=True, help='output filename')
group_main.add_argument('--overwrite', default = False, action='store_true', help = "overwrite existing training, default: %(default)s")
group_main.add_argument('--tag', type=str, default='person', required=False, help='primary tags, default: %(default)s')
group_data = parser.add_argument_group('Dataset')
group_data.add_argument('--input', type=str, default=None, required=True, help='input folder with training images')
group_data.add_argument('--output', type=str, default='', required=False, help='where to store processed images, default is system temp/train')
group_data.add_argument('--process', type=str, default='original,interrogate,resize,square', required=False, help=f'list of possible processing steps: {valid_steps}, default: %(default)s')
group_train = parser.add_argument_group('Train')
group_train.add_argument('--gradient', type=int, default=1, required=False, help='gradient accumulation steps, default: %(default)s')
group_train.add_argument('--steps', type=int, default=2500, required=False, help='training steps, default: %(default)s')
group_train.add_argument('--batch', type=int, default=1, required=False, help='batch size, default: %(default)s')
group_train.add_argument('--lr', type=float, default=1e-04, required=False, help='model learning rate, default: %(default)s')
group_train.add_argument('--dim', type=int, default=40, required=False, help='network dimension or number of vectors, default: %(default)s')
# lora params
parser.add_argument('--repeats', type=int, default=10, required=False, help='number of repeats per image, default: %(default)s')
parser.add_argument('--alpha', type=float, default=0, required=False, help='alpha for weights scaling, default: dim/2')
group_train.add_argument('--repeats', type=int, default=10, required=False, help='number of repeats per image, default: %(default)s')
group_train.add_argument('--alpha', type=float, default=0, required=False, help='alpha for weights scaling, default: dim/2')
args = parser.parse_args()