Loading modules/script_callbacks.py +5 −5 Original line number Original line Diff line number Diff line Loading @@ -29,7 +29,7 @@ class ImageSaveParams: class CFGDenoiserParams: class CFGDenoiserParams: def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, tensor, uncond): def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond): self.x = x self.x = x """Latent image representation in the process of being denoised""" """Latent image representation in the process of being denoised""" Loading @@ -45,11 +45,11 @@ class CFGDenoiserParams: self.total_sampling_steps = total_sampling_steps self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" """Total number of sampling steps planned""" self.tensor = tensor self.text_cond = text_cond """ Encoder hidden states of conditioning""" """ Encoder hidden states of text conditioning from prompt""" self.uncond = uncond self.text_uncond = text_uncond """ Encoder hidden states of unconditioning""" """ Encoder hidden states of text conditioning from negative prompt""" class CFGDenoisedParams: class CFGDenoisedParams: Loading modules/sd_samplers_kdiffusion.py +2 −2 Original line number Original line Diff line number Diff line Loading @@ -106,8 +106,8 @@ class CFGDenoiser(torch.nn.Module): x_in = denoiser_params.x x_in = denoiser_params.x image_cond_in = denoiser_params.image_cond image_cond_in = denoiser_params.image_cond sigma_in = denoiser_params.sigma sigma_in = denoiser_params.sigma tensor = denoiser_params.tensor tensor = denoiser_params.text_cond uncond = denoiser_params.uncond uncond = denoiser_params.text_uncond if tensor.shape[1] == uncond.shape[1]: if tensor.shape[1] == uncond.shape[1]: if not is_edit_model: if not is_edit_model: Loading Loading
modules/script_callbacks.py +5 −5 Original line number Original line Diff line number Diff line Loading @@ -29,7 +29,7 @@ class ImageSaveParams: class CFGDenoiserParams: class CFGDenoiserParams: def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, tensor, uncond): def __init__(self, x, image_cond, sigma, sampling_step, total_sampling_steps, text_cond, text_uncond): self.x = x self.x = x """Latent image representation in the process of being denoised""" """Latent image representation in the process of being denoised""" Loading @@ -45,11 +45,11 @@ class CFGDenoiserParams: self.total_sampling_steps = total_sampling_steps self.total_sampling_steps = total_sampling_steps """Total number of sampling steps planned""" """Total number of sampling steps planned""" self.tensor = tensor self.text_cond = text_cond """ Encoder hidden states of conditioning""" """ Encoder hidden states of text conditioning from prompt""" self.uncond = uncond self.text_uncond = text_uncond """ Encoder hidden states of unconditioning""" """ Encoder hidden states of text conditioning from negative prompt""" class CFGDenoisedParams: class CFGDenoisedParams: Loading
modules/sd_samplers_kdiffusion.py +2 −2 Original line number Original line Diff line number Diff line Loading @@ -106,8 +106,8 @@ class CFGDenoiser(torch.nn.Module): x_in = denoiser_params.x x_in = denoiser_params.x image_cond_in = denoiser_params.image_cond image_cond_in = denoiser_params.image_cond sigma_in = denoiser_params.sigma sigma_in = denoiser_params.sigma tensor = denoiser_params.tensor tensor = denoiser_params.text_cond uncond = denoiser_params.uncond uncond = denoiser_params.text_uncond if tensor.shape[1] == uncond.shape[1]: if tensor.shape[1] == uncond.shape[1]: if not is_edit_model: if not is_edit_model: Loading
