(self, num_inference_steps=100, num_train_timesteps=1000, shift=3.0, sigma_max=1.0, sigma_min=0.003/1.002, inverse_timesteps=False, extra_one_step=False, reverse_sigmas=False)
| 5 | class FlowMatchScheduler(): |
| 6 | |
| 7 | def __init__(self, num_inference_steps=100, num_train_timesteps=1000, shift=3.0, sigma_max=1.0, sigma_min=0.003/1.002, inverse_timesteps=False, extra_one_step=False, reverse_sigmas=False): |
| 8 | self.num_train_timesteps = num_train_timesteps |
| 9 | self.shift = shift |
| 10 | self.sigma_max = sigma_max |
| 11 | self.sigma_min = sigma_min |
| 12 | self.inverse_timesteps = inverse_timesteps |
| 13 | self.extra_one_step = extra_one_step |
| 14 | self.reverse_sigmas = reverse_sigmas |
| 15 | self.set_timesteps(num_inference_steps) |
| 16 | |
| 17 | |
| 18 | def set_timesteps(self, num_inference_steps=100, denoising_strength=1.0, training=False, shift=None): |
nothing calls this directly
no test coverage detected