fred-dev/comfy_ui_ali

1import torch2import comfy.model_management3import comfy.samplers4import comfy.utils5import numpy as np6import logging7 8def prepare_noise(latent_image, seed, noise_inds=None):9    """10    creates random noise given a latent image and a seed.11    optional arg skip can be used to skip and discard x number of noise generations for a given seed12    """13    generator = torch.manual_seed(seed)14    if noise_inds is None:15        return torch.randn(latent_image.size(), dtype=latent_image.dtype, layout=latent_image.layout, generator=generator, device="cpu")16 17    unique_inds, inverse = np.unique(noise_inds, return_inverse=True)18    noises = []19    for i in range(unique_inds[-1]+1):20        noise = torch.randn([1] + list(latent_image.size())[1:], dtype=latent_image.dtype, layout=latent_image.layout, generator=generator, device="cpu")21        if i in unique_inds:22            noises.append(noise)23    noises = [noises[i] for i in inverse]24    noises = torch.cat(noises, axis=0)25    return noises26 27def fix_empty_latent_channels(model, latent_image):28    latent_format = model.get_model_object("latent_format") #Resize the empty latent image so it has the right number of channels29    if latent_format.latent_channels != latent_image.shape[1] and torch.count_nonzero(latent_image) == 0:30        latent_image = comfy.utils.repeat_to_batch_size(latent_image, latent_format.latent_channels, dim=1)31    if latent_format.latent_dimensions == 3 and latent_image.ndim == 4:32        latent_image = latent_image.unsqueeze(2)33    return latent_image34 35def prepare_sampling(model, noise_shape, positive, negative, noise_mask):36    logging.warning("Warning: comfy.sample.prepare_sampling isn't used anymore and can be removed")37    return model, positive, negative, noise_mask, []38 39def cleanup_additional_models(models):40    logging.warning("Warning: comfy.sample.cleanup_additional_models isn't used anymore and can be removed")41 42def sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False, noise_mask=None, sigmas=None, callback=None, disable_pbar=False, seed=None):43    sampler = comfy.samplers.KSampler(model, steps=steps, device=model.load_device, sampler=sampler_name, scheduler=scheduler, denoise=denoise, model_options=model.model_options)44 45    samples = sampler.sample(noise, positive, negative, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed)46    samples = samples.to(comfy.model_management.intermediate_device())47    return samples48 49def sample_custom(model, noise, cfg, sampler, sigmas, positive, negative, latent_image, noise_mask=None, callback=None, disable_pbar=False, seed=None):50    samples = comfy.samplers.sample(model, noise, positive, negative, cfg, model.load_device, sampler, sigmas, model_options=model.model_options, latent_image=latent_image, denoise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)51    samples = samples.to(comfy.model_management.intermediate_device())52    return samples53