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fix img2img variations/MPS (#353)

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* fix img2img variations

* fix assert for variation_amount
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Kevin Gibbons 2022-09-03 23:34:20 -07:00 committed by GitHub
parent c22c3dec56
commit 751283a2de
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1 changed files with 8 additions and 7 deletions
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15
ldm/simplet2i.py
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@ -286,7 +286,7 @@ class T2I:
0.0 <= variation_amount <= 1.0 0.0 <= variation_amount <= 1.0
), '-v --variation_amount must be in [0.0, 1.0]' ), '-v --variation_amount must be in [0.0, 1.0]'
if len(with_variations) > 0 or variation_amount > 1.0: if len(with_variations) > 0 or variation_amount > 0.0:
assert seed is not None,\ assert seed is not None,\
'seed must be specified when using with_variations' 'seed must be specified when using with_variations'
if variation_amount == 0.0: if variation_amount == 0.0:
@ -336,6 +336,7 @@ class T2I:
callback=step_callback, callback=step_callback,
) )
else: else:
init_latent = None
make_image = self._txt2img( make_image = self._txt2img(
prompt, prompt,
steps=steps, steps=steps,
@ -351,11 +352,11 @@ class T2I:
if variation_amount > 0 or len(with_variations) > 0: if variation_amount > 0 or len(with_variations) > 0:
# use fixed initial noise plus random noise per iteration # use fixed initial noise plus random noise per iteration
seed_everything(seed) seed_everything(seed)
initial_noise = self._get_noise(init_img,width,height) initial_noise = self._get_noise(init_latent,width,height)
for v_seed, v_weight in with_variations: for v_seed, v_weight in with_variations:
seed = v_seed seed = v_seed
seed_everything(seed) seed_everything(seed)
next_noise = self._get_noise(init_img,width,height) next_noise = self._get_noise(init_latent,width,height)
initial_noise = self.slerp(v_weight, initial_noise, next_noise) initial_noise = self.slerp(v_weight, initial_noise, next_noise)
if variation_amount > 0: if variation_amount > 0:
random.seed() # reset RNG to an actually random state, so we can get a random seed for variations random.seed() # reset RNG to an actually random state, so we can get a random seed for variations
@ -367,7 +368,7 @@ class T2I:
x_T = None x_T = None
if variation_amount > 0: if variation_amount > 0:
seed_everything(seed) seed_everything(seed)
target_noise = self._get_noise(init_img,width,height) target_noise = self._get_noise(init_latent,width,height)
x_T = self.slerp(variation_amount, initial_noise, target_noise) x_T = self.slerp(variation_amount, initial_noise, target_noise)
elif initial_noise is not None: elif initial_noise is not None:
# i.e. we specified particular variations # i.e. we specified particular variations
@ -375,7 +376,7 @@ class T2I:
else: else:
seed_everything(seed) seed_everything(seed)
if self.device.type == 'mps': if self.device.type == 'mps':
x_T = self._get_noise(init_img,width,height) x_T = self._get_noise(init_latent,width,height)
# make_image will do the equivalent of get_noise itself # make_image will do the equivalent of get_noise itself
print(f' DEBUG: seed at make_image() invocation time ={seed}') print(f' DEBUG: seed at make_image() invocation time ={seed}')
image = make_image(x_T) image = make_image(x_T)
@ -606,8 +607,8 @@ class T2I:
return self.model return self.model
# returns a tensor filled with random numbers from a normal distribution # returns a tensor filled with random numbers from a normal distribution
def _get_noise(self,init_img,width,height): def _get_noise(self,init_latent,width,height):
if init_img: if init_latent is not None:
if self.device.type == 'mps': if self.device.type == 'mps':
return torch.randn_like(init_latent, device='cpu').to(self.device) return torch.randn_like(init_latent, device='cpu').to(self.device)
else: else: