Method sample

easy_samplers.py:376–624

(
        self,
        model,
        vae,
        latents,
        num_new_frames,
        frame_overlap,
        guider,
        sampler,
        sigmas,
        noise,
        strength=0.5,
        guiding_strength=1.0,
        cond_image_strength=1.0,
        optional_guiding_latents=None,
        optional_cond_images=None,
        optional_cond_indices=None,
        optional_reference_latents=None,
        optional_initialization_latents=None,
        adain_factor=0.0,
        optional_negative_index_latents=None,
        optional_negative_index=-1,
        optional_negative_index_strength=1.0,
        guiding_start_step=0,
        guiding_end_step=1000,
        normalize_per_frame=False,
    )

    CATEGORY = "sampling"

    def sample(
        self,
        model,
        vae,
        latents,
        num_new_frames,
        frame_overlap,
        guider,
        sampler,
        sigmas,
        noise,
        strength=0.5,
        guiding_strength=1.0,
        cond_image_strength=1.0,
        optional_guiding_latents=None,
        optional_cond_images=None,
        optional_cond_indices=None,
        optional_reference_latents=None,
        optional_initialization_latents=None,
        adain_factor=0.0,
        optional_negative_index_latents=None,
        optional_negative_index=-1,
        optional_negative_index_strength=1.0,
        guiding_start_step=0,
        guiding_end_step=1000,
        normalize_per_frame=False,
    ):
        guider = copy.copy(guider)
        guider.original_conds = copy.deepcopy(guider.original_conds)

        if optional_cond_indices is not None and optional_cond_images is not None:
            optional_cond_indices = optional_cond_indices.split(",")
            optional_cond_indices = [int(i) for i in optional_cond_indices]
            assert len(optional_cond_indices) == len(
                optional_cond_images
            ), "Number of optional cond images must match number of optional cond indices"

        positive, negative = _get_raw_conds_from_guider(guider)

        samples = latents["samples"]
        batch, channels, frames, height, width = samples.shape
        time_scale_factor, width_scale_factor, height_scale_factor = (
            vae.downscale_index_formula
        )
        overlap = frame_overlap // time_scale_factor

        if num_new_frames == -1 and optional_guiding_latents is not None:
            num_new_frames = (
                optional_guiding_latents["samples"].shape[2] - overlap
            ) * time_scale_factor

        (last_overlap_latents,) = LTXVSelectLatents().select_latents(
            latents, -overlap, -1
        )

        if optional_initialization_latents is None:
            new_latents = EmptyLTXVLatentVideo.execute(
                width=width * width_scale_factor,