Skip to content

Refac docstrings in training_utils.py #9724

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 5 commits into from
Closed

Refac docstrings in training_utils.py #9724

Changes from 2 commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
0b9f8cc
Additions to docstrings in training_utils.py
RogerSinghChugh Oct 20, 2024
4a1c7d4
Additions to docstrings in training_utils.py continued.
RogerSinghChugh Oct 20, 2024
220e27f
Changes after running make style.
RogerSinghChugh Oct 22, 2024
5ef13c7
Merge branch 'main' into refac_training_utils
RogerSinghChugh Oct 22, 2024
7b52b80
Merge branch 'huggingface:main' into refac_training_utils
RogerSinghChugh Oct 30, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 15 additions & 2 deletions src/diffusers/training_utils.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,6 +43,9 @@ def set_seed(seed: int):

Args:
seed (`int`): The seed to set.

Returns:
`None`
"""
random.seed(seed)
np.random.seed(seed)
Expand All @@ -56,8 +59,18 @@ def set_seed(seed: int):

def compute_snr(noise_scheduler, timesteps):
"""
Computes SNR as per
https://github.com/TiankaiHang/Min-SNR-Diffusion-Training/blob/521b624bd70c67cee4bdf49225915f5945a872e3/guided_diffusion/gaussian_diffusion.py#L847-L849
Computes SNR as per https://github.com/TiankaiHang/Min-SNR-Diffusion-Training/blob/521b624bd70c67cee4bdf49225915f5945a872e3/guided_diffusion/gaussian_diffusion.py#L847-L849
for the given timesteps using the provided noise scheduler.

Args:
noise_scheduler (`NoiseScheduler`):
An object containing the noise schedule parameters, specifically `alphas_cumprod`, which is used
to compute the SNR values.
timesteps (`torch.Tensor`):
A tensor of timesteps for which the SNR is computed.

Returns:
`torch.Tensor`: A tensor containing the computed SNR values for each timestep.
"""
alphas_cumprod = noise_scheduler.alphas_cumprod
sqrt_alphas_cumprod = alphas_cumprod**0.5
Expand Down
Loading