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Running
on
Zero
| from typing import List, Optional, Tuple, Union | |
| import torch | |
| from diffusers.utils.torch_utils import randn_tensor | |
| def random_noise( | |
| tensor: torch.Tensor = None, | |
| shape: Tuple[int] = None, | |
| dtype: torch.dtype = None, | |
| device: torch.device = None, | |
| generator: Optional[Union[List["torch.Generator"], "torch.Generator"]] = None, | |
| noise_offset: Optional[float] = None, # typical value is 0.1 | |
| ) -> torch.Tensor: | |
| if tensor is not None: | |
| shape = tensor.shape | |
| device = tensor.device | |
| dtype = tensor.dtype | |
| if isinstance(device, str): | |
| device = torch.device(device) | |
| noise = randn_tensor(shape, dtype=dtype, device=device, generator=generator) | |
| if noise_offset is not None: | |
| noise += noise_offset * torch.randn( | |
| (tensor.shape[0], tensor.shape[1], 1, 1, 1), device | |
| ) | |
| return noise | |