Add Adaptive Projected Guidance (APG) support to denoising functions. Introduce apg_delta function for stable guidance by decomposing into parallel and orthogonal components. Update denoise_dev and generate_video functions to accept APG parameters, enhancing flexibility in video generation. Modify command-line arguments for APG integration.

mlx_video/generate.py

@@ -75,6 +75,59 @@ def cfg_delta(cond: mx.array, uncond: mx.array, scale: float) -> mx.array:
     return (scale - 1.0) * (cond - uncond)
 
 
+def apg_delta(
+    cond: mx.array,
+    uncond: mx.array,
+    scale: float,
+    eta: float = 1.0,
+    norm_threshold: float = 0.0,
+) -> mx.array:
+    """Compute APG (Adaptive Projected Guidance) delta.
+
+    Decomposes guidance into parallel and orthogonal components relative to
+    the conditional prediction, providing more stable guidance for I2V.
+
+    Based on: https://arxiv.org/abs/2407.12173
+
+    Args:
+        cond: Conditional prediction (x0_pos)
+        uncond: Unconditional prediction (x0_neg)
+        scale: Guidance strength (same as CFG scale)
+        eta: Weight for parallel component (1.0 = keep full parallel)
+        norm_threshold: Clamp guidance norm to this value (0 = no clamping)
+
+    Returns:
+        Delta to add to unconditional for APG guidance
+    """
+    guidance = cond - uncond
+
+    # Optionally clamp guidance norm for stability
+    if norm_threshold > 0:
+        guidance_norm = mx.sqrt(mx.sum(guidance ** 2, axis=(-1, -2, -3), keepdims=True) + 1e-8)
+        scale_factor = mx.minimum(mx.ones_like(guidance_norm), norm_threshold / guidance_norm)
+        guidance = guidance * scale_factor
+
+    # Project guidance onto cond direction
+    batch_size = cond.shape[0]
+    cond_flat = mx.reshape(cond, (batch_size, -1))
+    guidance_flat = mx.reshape(guidance, (batch_size, -1))
+
+    # Projection coefficient: (guidance · cond) / (cond · cond)
+    dot_product = mx.sum(guidance_flat * cond_flat, axis=1, keepdims=True)
+    squared_norm = mx.sum(cond_flat ** 2, axis=1, keepdims=True) + 1e-8
+    proj_coeff = dot_product / squared_norm
+
+    # Reshape back and compute parallel/orthogonal components
+    proj_coeff = mx.reshape(proj_coeff, (batch_size,) + (1,) * (cond.ndim - 1))
+    g_parallel = proj_coeff * cond
+    g_orth = guidance - g_parallel
+
+    # Combine with eta weighting parallel component
+    g_apg = g_parallel * eta + g_orth
+
+    return g_apg * (scale - 1.0)
+
+
 def ltx2_scheduler(
     steps: int,
     num_tokens: Optional[int] = None,
@@ -371,8 +424,19 @@ def denoise_dev(
     cfg_scale: float = 4.0,
     verbose: bool = True,
     state: Optional[LatentState] = None,
+    use_apg: bool = False,
+    apg_eta: float = 1.0,
+    apg_norm_threshold: float = 0.0,
 ) -> mx.array:
-    """Run denoising loop for dev pipeline with CFG."""
+    """Run denoising loop for dev pipeline with CFG or APG guidance.
+
+    Args:
+        use_apg: Use Adaptive Projected Guidance instead of standard CFG.
+                 APG decomposes guidance into parallel/orthogonal components
+                 for more stable I2V generation.
+        apg_eta: APG parallel component weight (1.0 = keep full parallel)
+        apg_norm_threshold: APG guidance norm clamp (0 = no clamping)
+    """
     from mlx_video.models.ltx.rope import precompute_freqs_cis
 
     dtype = latents.dtype
@@ -465,8 +529,16 @@ def denoise_dev(
                 # Convert negative velocity to x0 using per-token timesteps
                 x0_neg_f32 = latents_flat_f32 - timesteps_f32 * velocity_neg.astype(mx.float32)
 
-                # Apply CFG to x0 predictions (matches PyTorch CFGGuider)
+                # Apply guidance to x0 predictions
                 # For conditioned tokens: x0_pos = x0_neg = latent, so delta = 0
+                if use_apg:
+                    # APG: decompose into parallel/orthogonal components for stability
+                    x0_guided_f32 = x0_pos_f32 + apg_delta(
+                        x0_pos_f32, x0_neg_f32, cfg_scale,
+                        eta=apg_eta, norm_threshold=apg_norm_threshold
+                    )
+                else:
+                    # Standard CFG
                     x0_guided_f32 = x0_pos_f32 + (cfg_scale - 1.0) * (x0_pos_f32 - x0_neg_f32)
             else:
                 x0_guided_f32 = x0_pos_f32
@@ -507,13 +579,19 @@ def denoise_dev_av(
     cfg_rescale: float = 0.0,
     verbose: bool = True,
     video_state: Optional[LatentState] = None,
+    use_apg: bool = False,
+    apg_eta: float = 1.0,
+    apg_norm_threshold: float = 0.0,
 ) -> tuple[mx.array, mx.array]:
-    """Run denoising loop for dev pipeline with CFG and audio.
+    """Run denoising loop for dev pipeline with CFG/APG and audio.
 
     Args:
         cfg_rescale: Rescale factor for CFG (0.0-1.0). Higher values blend the CFG result
                      towards the positive-only prediction, helping reduce artifacts.
                      Default 0.0 means no rescaling (standard CFG).
+        use_apg: Use Adaptive Projected Guidance instead of standard CFG for video.
+        apg_eta: APG parallel component weight (1.0 = keep full parallel)
+        apg_norm_threshold: APG guidance norm clamp (0 = no clamping)
     """
     from mlx_video.models.ltx.rope import precompute_freqs_cis
 
@@ -638,10 +716,17 @@ def denoise_dev_av(
                 video_x0_neg_f32 = video_flat_f32 - video_timesteps_f32 * video_vel_neg.astype(mx.float32)
                 audio_x0_neg_f32 = audio_flat_f32 - audio_timesteps_f32 * audio_vel_neg.astype(mx.float32)
 
-                # Apply CFG to x0 (denoised) predictions - matches PyTorch CFGGuider
+                # Apply guidance to x0 (denoised) predictions
-                # delta = (scale - 1) * (x0_pos - x0_neg)
+                # For conditioned tokens: x0_pos = x0_neg = latent, so delta = 0 (no effect)
-                # For conditioned tokens: x0_pos = x0_neg = latent, so delta = 0 (no CFG effect)
+                if use_apg:
+                    # APG for video (more stable for I2V), standard CFG for audio
+                    video_x0_guided_f32 = video_x0_pos_f32 + apg_delta(
+                        video_x0_pos_f32, video_x0_neg_f32, cfg_scale,
+                        eta=apg_eta, norm_threshold=apg_norm_threshold
+                    )
+                else:
                     video_x0_guided_f32 = video_x0_pos_f32 + (cfg_scale - 1.0) * (video_x0_pos_f32 - video_x0_neg_f32)
+                # Always use standard CFG for audio
                 audio_x0_guided_f32 = audio_x0_pos_f32 + (cfg_scale - 1.0) * (audio_x0_pos_f32 - audio_x0_neg_f32)
 
                 # Apply CFG rescale if enabled
@@ -788,6 +873,9 @@ def generate_video(
     stream: bool = False,
     audio: bool = False,
     output_audio_path: Optional[str] = None,
+    use_apg: bool = False,
+    apg_eta: float = 1.0,
+    apg_norm_threshold: float = 0.0,
 ):
     """Generate video using LTX-2 models.
 
@@ -821,6 +909,9 @@ def generate_video(
         stream: Stream frames to output as they're decoded
         audio: Enable synchronized audio generation
         output_audio_path: Path to save audio file
+        use_apg: Use Adaptive Projected Guidance instead of CFG (more stable for I2V)
+        apg_eta: APG parallel component weight (1.0 = keep full parallel)
+        apg_norm_threshold: APG guidance norm clamp (0 = no clamping)
     """
     start_time = time.time()
 
@@ -1080,9 +1171,9 @@ def generate_video(
                 mx.clear_cache()
             console.print("[green]✓[/] VAE encoder loaded and image encoded")
 
-        # Generate sigma schedule (uses MAX_SHIFT_ANCHOR=4096 like the reference implementation)
+        # Generate sigma schedule with token-count-dependent shifting
         num_tokens = latent_frames * latent_h * latent_w
-        sigmas = ltx2_scheduler(steps=num_inference_steps)
+        sigmas = ltx2_scheduler(steps=num_inference_steps, num_tokens=num_tokens)
         mx.eval(sigmas)
         console.print(f"[dim]Sigma schedule: {sigmas[0].item():.4f} → {sigmas[-2].item():.4f} → {sigmas[-1].item():.4f}[/]")
 
@@ -1125,7 +1216,7 @@ def generate_video(
             latents = mx.random.normal(video_latent_shape, dtype=model_dtype)
             mx.eval(latents)
 
-        # Denoise with CFG
+        # Denoise with CFG/APG
         if audio:
             latents, audio_latents = denoise_dev_av(
                 latents, audio_latents,
@@ -1133,7 +1224,8 @@ def generate_video(
                 video_embeddings_pos, video_embeddings_neg,
                 audio_embeddings_pos, audio_embeddings_neg,
                 transformer, sigmas, cfg_scale=cfg_scale,
-                cfg_rescale=cfg_rescale, verbose=verbose, video_state=video_state
+                cfg_rescale=cfg_rescale, verbose=verbose, video_state=video_state,
+                use_apg=use_apg, apg_eta=apg_eta, apg_norm_threshold=apg_norm_threshold
             )
         else:
             # Use original denoise_dev with computed sigmas
@@ -1141,7 +1233,8 @@ def generate_video(
                 latents, video_positions,
                 video_embeddings_pos, video_embeddings_neg,
                 transformer, sigmas, cfg_scale=cfg_scale,
-                verbose=verbose, state=video_state
+                verbose=verbose, state=video_state,
+                use_apg=use_apg, apg_eta=apg_eta, apg_norm_threshold=apg_norm_threshold
             )
 
         # Load VAE decoder (for dev pipeline, loaded here instead of during upsampling)
@@ -1371,6 +1464,9 @@ Examples:
     parser.add_argument("--stream", action="store_true", help="Stream frames to output as they're decoded")
     parser.add_argument("--audio", "-a", action="store_true", help="Enable synchronized audio generation")
     parser.add_argument("--output-audio", type=str, default=None, help="Output audio path")
+    parser.add_argument("--apg", action="store_true", help="Use Adaptive Projected Guidance instead of CFG (more stable for I2V)")
+    parser.add_argument("--apg-eta", type=float, default=1.0, help="APG parallel component weight (1.0 = keep full parallel)")
+    parser.add_argument("--apg-norm-threshold", type=float, default=0.0, help="APG guidance norm clamp (0 = no clamping)")
     args = parser.parse_args()
 
     pipeline = PipelineType.DEV if args.pipeline == "dev" else PipelineType.DISTILLED
@@ -1402,6 +1498,9 @@ Examples:
         stream=args.stream,
         audio=args.audio,
         output_audio_path=args.output_audio,
+        use_apg=args.apg,
+        apg_eta=args.apg_eta,
+        apg_norm_threshold=args.apg_norm_threshold,
     )