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Class LTXVAddLatentGuide

latents.py:401–495  ·  view source on GitHub ↗

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399
400@comfy_node(name="LTXVAddLatentGuide")
401class LTXVAddLatentGuide:
402 @classmethod
403 def INPUT_TYPES(s):
404 return {
405 "required": {
406 "vae": ("VAE",),
407 "positive": ("CONDITIONING",),
408 "negative": ("CONDITIONING",),
409 "latent": ("LATENT",),
410 "guiding_latent": ("LATENT",),
411 "latent_idx": (
412 "INT",
413 {
414 "default": 0,
415 "min": -9999,
416 "max": 9999,
417 "step": 1,
418 "tooltip": "Latent index to start the conditioning at. Can be negative to"
419 "indicate that the conditioning is on the frames before the latent.",
420 },
421 ),
422 "strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0}),
423 }
424 }
425
426 RETURN_TYPES = ("CONDITIONING", "CONDITIONING", "LATENT")
427 RETURN_NAMES = ("positive", "negative", "latent")
428
429 CATEGORY = "ltxtricks"
430 FUNCTION = "generate"
431
432 DESCRIPTION = "Adds a keyframe or a video segment at a specific frame index."
433
434 def generate(
435 self, vae, positive, negative, latent, guiding_latent, latent_idx, strength
436 ):
437 noise_mask = nodes_lt.get_noise_mask(latent)
438 latent = latent["samples"]
439 guide = guiding_latent["samples"]
440
441 # Record original (pre-dilation) guide latent shape for spatial mask downsampling
442 guide_orig_shape = list(guide.shape[2:]) # [F, H_small, W_small]
443
444 assert (
445 latent.shape[4] % guide.shape[4] == 0
446 and latent.shape[3] % guide.shape[3] == 0
447 ), "The ratio of the height and width of the latents and optional_guiding_latents must be an integer"
448
449 guiding_latent = LTXVDilateLatent().dilate_latent(
450 guiding_latent,
451 horizontal_scale=latent.shape[4] // guide.shape[4],
452 vertical_scale=latent.shape[3] // guide.shape[3],
453 )[0]
454
455 guide = guiding_latent["samples"]
456 guide_mask = guiding_latent.get("noise_mask", None)
457
458 # Pre-filter token count = product of dilated spatial dims

Callers 4

sampleMethod · 0.85
sampleMethod · 0.85
sampleMethod · 0.85
sampleMethod · 0.85

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