From c1500cb04e0585f18f9e3aae2ec9428bfa015093 Mon Sep 17 00:00:00 2001 From: kijai <40791699+kijai@users.noreply.github.com> Date: Wed, 11 Dec 2024 19:24:04 +0200 Subject: [PATCH] Update nodes_rf_inversion.py --- nodes_rf_inversion.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/nodes_rf_inversion.py b/nodes_rf_inversion.py index 15ce7d7..d1eede1 100644 --- a/nodes_rf_inversion.py +++ b/nodes_rf_inversion.py @@ -20,7 +20,7 @@ def generate_eta_values( ): assert start_step < end_step and start_step >= 0 and end_step <= len(timesteps), "Invalid start_step and end_step" # timesteps are monotonically decreasing, from 1.0 to 0.0 - print("eta timesteps", timesteps) + eta_values = [0.0] * (len(timesteps) - 1) if eta_trend == 'constant': @@ -36,7 +36,7 @@ def generate_eta_values( eta_values[i] = eta * (timesteps[i] - timesteps[end_step - 1]) / total_time else: raise NotImplementedError(f"Unsupported eta_trend: {eta_trend}") - + print("eta_values", eta_values) return eta_values class HyVideoEmptyTextEmbeds: @@ -160,7 +160,7 @@ class HyVideoInverseSampler: int(height) // pipeline.vae_scale_factor, int(width) // pipeline.vae_scale_factor, ) - noise = randn_tensor(shape, generator=generator, device=device, dtype=dtype) + noise = randn_tensor(shape, generator=generator, device=device, dtype=torch.float32) frames_needed = noise.shape[1] current_frames = latents.shape[1] @@ -221,10 +221,13 @@ class HyVideoInverseSampler: )["x"] sigma = t / 1000.0 sigma_prev = t_prev / 1000.0 + latents = latents.to(torch.float32) + noise_pred = noise_pred.to(torch.float32) target_noise_velocity = (noise - latents) / (1.0 - sigma) interpolated_velocity = gamma * target_noise_velocity + (1 - gamma) * noise_pred latents = latents + (sigma_prev - sigma) * interpolated_velocity + latents = latents.to(torch.bfloat16) # compute the previous noisy sample x_t -> x_t-1 #latents = pipeline.scheduler.step(noise_pred, t, latents, return_dict=False)[0]