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Merge pull request #33 from laksjdjf/sub 

Apply xformers in diffusers_trainer.py
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Anthony Mercurio 2022-11-10 09:21:30 -07:00 committed by GitHub
parent 1ea31eb71e 353200b039
commit 2f8d71c589
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diffusers_trainer.py
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@ -81,6 +81,7 @@ parser.add_argument('--image_log_inference_steps', type=int, default=50, help='N
parser.add_argument('--image_log_scheduler', type=str, default="PNDMScheduler", help='Number of inference steps to use to log images.') parser.add_argument('--image_log_scheduler', type=str, default="PNDMScheduler", help='Number of inference steps to use to log images.')
parser.add_argument('--clip_penultimate', type=bool, default=False, help='Use penultimate CLIP layer for text embedding') parser.add_argument('--clip_penultimate', type=bool, default=False, help='Use penultimate CLIP layer for text embedding')
parser.add_argument('--output_bucket_info', type=bool, default=False, help='Outputs bucket information and exits') parser.add_argument('--output_bucket_info', type=bool, default=False, help='Outputs bucket information and exits')
parser.add_argument('--use_xformers', type=bool, default=False, help='Use memory efficient attention')
args = parser.parse_args() args = parser.parse_args()
def setup(): def setup():
@ -550,6 +551,9 @@ def main():
if args.gradient_checkpointing: if args.gradient_checkpointing:
unet.enable_gradient_checkpointing() unet.enable_gradient_checkpointing()
if args.use_xformers:
unet.set_use_memory_efficient_attention_xformers(True)
if args.use_8bit_adam: # Bits and bytes is only supported on certain CUDA setups, so default to regular adam if it fails. if args.use_8bit_adam: # Bits and bytes is only supported on certain CUDA setups, so default to regular adam if it fails.
try: try:
import bitsandbytes as bnb import bitsandbytes as bnb