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Support for Offset Noise in examples #2753

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merged 2 commits into from
Mar 23, 2023
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Support for Offset Noise in examples #2753

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dc75196
add noise offset
haofanwang Mar 20, 2023
fb24f8f
make style
haofanwang Mar 23, 2023
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7 changes: 7 additions & 0 deletions examples/text_to_image/train_text_to_image.py
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Original file line number Diff line number Diff line change
Expand Up @@ -297,6 +297,7 @@ def parse_args():
parser.add_argument(
"--enable_xformers_memory_efficient_attention", action="store_true", help="Whether or not to use xformers."
)
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset.")
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Suggested change
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset.")
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset. See: https://www.crosslabs.org//blog/diffusion-with-offset-noise for more information.")


args = parser.parse_args()
env_local_rank = int(os.environ.get("LOCAL_RANK", -1))
Expand Down Expand Up @@ -705,6 +706,12 @@ def collate_fn(examples):

# Sample noise that we'll add to the latents
noise = torch.randn_like(latents)
if args.noise_offset:
# https://www.crosslabs.org//blog/diffusion-with-offset-noise
noise += args.noise_offset * torch.randn(
(latents.shape[0], latents.shape[1], 1, 1), device=latents.device
)

bsz = latents.shape[0]
# Sample a random timestep for each image
timesteps = torch.randint(0, noise_scheduler.num_train_timesteps, (bsz,), device=latents.device)
Expand Down
7 changes: 7 additions & 0 deletions examples/text_to_image/train_text_to_image_lora.py
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Original file line number Diff line number Diff line change
Expand Up @@ -333,6 +333,7 @@ def parse_args():
parser.add_argument(
"--enable_xformers_memory_efficient_attention", action="store_true", help="Whether or not to use xformers."
)
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset.")
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Suggested change
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset.")
parser.add_argument("--noise_offset", type=float, default=0, help="The scale of noise offset. See: https://www.crosslabs.org//blog/diffusion-with-offset-noise for more information.")


args = parser.parse_args()
env_local_rank = int(os.environ.get("LOCAL_RANK", -1))
Expand Down Expand Up @@ -718,6 +719,12 @@ def collate_fn(examples):

# Sample noise that we'll add to the latents
noise = torch.randn_like(latents)
if args.noise_offset:
# https://www.crosslabs.org//blog/diffusion-with-offset-noise
noise += args.noise_offset * torch.randn(
(latents.shape[0], latents.shape[1], 1, 1), device=latents.device
)

bsz = latents.shape[0]
# Sample a random timestep for each image
timesteps = torch.randint(0, noise_scheduler.num_train_timesteps, (bsz,), device=latents.device)
Expand Down