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use Half precision for reduced memory usage & faster speed #4

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Merged
lstein merged 1 commit into from Aug 20, 2022
Merged

use Half precision for reduced memory usage & faster speed #4

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7 changes: 5 additions & 2 deletions ldm/simplet2i.py
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Original file line number Diff line number Diff line change
Expand Up @@ -256,6 +256,8 @@ def img2img(self,prompt,outdir=None,init_img=None,batch_size=None,iterations=Non

model = self.load_model() # will instantiate the model or return it from cache

precision_scope = autocast if self.precision=="autocast" else nullcontext

# grid and individual are mutually exclusive, with individual taking priority.
# not necessary, but needed for compatability with dream bot
if (grid is None):
Expand All @@ -279,7 +281,8 @@ def img2img(self,prompt,outdir=None,init_img=None,batch_size=None,iterations=Non
assert os.path.isfile(init_img)
init_image = self._load_img(init_img).to(self.device)
init_image = repeat(init_image, '1 ... -> b ...', b=batch_size)
init_latent = model.get_first_stage_encoding(model.encode_first_stage(init_image)) # move to latent space
with precision_scope("cuda"):
init_latent = model.get_first_stage_encoding(model.encode_first_stage(init_image)) # move to latent space

sampler.make_schedule(ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False)

Expand All @@ -292,7 +295,6 @@ def img2img(self,prompt,outdir=None,init_img=None,batch_size=None,iterations=Non
t_enc = int(strength * steps)
print(f"target t_enc is {t_enc} steps")

precision_scope = autocast if self.precision=="autocast" else nullcontext
images = list()
seeds = list()

Expand Down Expand Up @@ -401,6 +403,7 @@ def _load_model_from_config(self, config, ckpt):
m, u = model.load_state_dict(sd, strict=False)
model.cuda()
model.eval()
model.half()
return model

def _load_img(self,path):
Expand Down