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Refac docstrings in training_utils.py #9724

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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
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Merge branch 'huggingface:main' into refac_training_utils
RogerSinghChugh Oct 30, 2024
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17 changes: 15 additions & 2 deletions src/diffusers/training_utils.py
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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
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