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Running
on
Zero
| # utilities.py | |
| import torch | |
| from typing import Optional, Union, List, Any, Dict | |
| import numpy as np | |
| from diffusers.utils import load_image | |
| import random | |
| import time | |
| def calculate_shift( | |
| image_seq_len, | |
| base_seq_len: int = 256, | |
| max_seq_len: int = 4096, | |
| base_shift: float = 0.5, | |
| max_shift: float = 1.16, | |
| ): | |
| m = (max_shift - base_shift) / (max_seq_len - base_seq_len) | |
| b = base_shift - m * base_seq_len | |
| mu = image_seq_len * m + b | |
| return mu | |
| def retrieve_timesteps( | |
| scheduler, | |
| num_inference_steps: Optional[int] = None, | |
| device: Optional[Union[str, torch.device]] = None, | |
| timesteps: Optional[List[int]] = None, | |
| sigmas: Optional[List[float]] = None, | |
| **kwargs, | |
| ): | |
| if timesteps is not None and sigmas is not None: | |
| raise ValueError("Only one of `timesteps` or `sigmas` can be passed. Please choose one to set custom values") | |
| if timesteps is not None: | |
| scheduler.set_timesteps(timesteps=timesteps, device=device, **kwargs) | |
| timesteps = scheduler.timesteps | |
| num_inference_steps = len(timesteps) | |
| elif sigmas is not None: | |
| scheduler.set_timesteps(sigmas=sigmas, device=device, **kwargs) | |
| timesteps = scheduler.timesteps | |
| num_inference_steps = len(timesteps) | |
| else: | |
| scheduler.set_timesteps(num_inference_steps, device=device, **kwargs) | |
| timesteps = scheduler.timesteps | |
| return timesteps, num_inference_steps | |
| def load_image_from_path(image_path: str): | |
| """Loads an image from a given file path.""" | |
| return load_image(image_path) | |
| def randomize_seed_if_needed(randomize_seed: bool, seed: int, max_seed: int) -> int: | |
| """Randomizes the seed if requested.""" | |
| if randomize_seed: | |
| return random.randint(0, max_seed) | |
| return seed | |
| class calculateDuration: | |
| def __init__(self, activity_name=""): | |
| self.activity_name = activity_name | |
| def __enter__(self): | |
| self.start_time = time.time() | |
| return self | |
| def __exit__(self, exc_type, exc_value, traceback): | |
| self.end_time = time.time() | |
| self.elapsed_time = self.end_time - self.start_time | |
| if self.activity_name: | |
| print(f"Elapsed time for {self.activity_name}: {self.elapsed_time:.6f} seconds") | |
| else: | |
| print(f"Elapsed time: {self.elapsed_time:.6f} seconds") |