From ba70a220e3176153ba2a559acb9e5aa692dce7ca Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 5 Jun 2023 22:20:29 +0300 Subject: Remove a bunch of unused/vestigial code As found by Vulture and some eyes --- modules/generation_parameters_copypaste.py | 29 ----------------------------- 1 file changed, 29 deletions(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 1d02ffae..699b1a81 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -174,31 +174,6 @@ def send_image_and_dimensions(x): return img, w, h - -def find_hypernetwork_key(hypernet_name, hypernet_hash=None): - """Determines the config parameter name to use for the hypernet based on the parameters in the infotext. - - Example: an infotext provides "Hypernet: ke-ta" and "Hypernet hash: 1234abcd". For the "Hypernet" config - parameter this means there should be an entry that looks like "ke-ta-10000(1234abcd)" to set it to. - - If the infotext has no hash, then a hypernet with the same name will be selected instead. - """ - hypernet_name = hypernet_name.lower() - if hypernet_hash is not None: - # Try to match the hash in the name - for hypernet_key in shared.hypernetworks.keys(): - result = re_hypernet_hash.search(hypernet_key) - if result is not None and result[1] == hypernet_hash: - return hypernet_key - else: - # Fall back to a hypernet with the same name - for hypernet_key in shared.hypernetworks.keys(): - if hypernet_key.lower().startswith(hypernet_name): - return hypernet_key - - return None - - def restore_old_hires_fix_params(res): """for infotexts that specify old First pass size parameter, convert it into width, height, and hr scale""" @@ -329,10 +304,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model return res -settings_map = {} - - - infotext_to_setting_name_mapping = [ ('Clip skip', 'CLIP_stop_at_last_layers', ), ('Conditional mask weight', 'inpainting_mask_weight'), -- cgit v1.2.3 From 4bd490c28dd8f17b7df943eb3963c34d725084fc Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 27 Jun 2023 06:18:43 +0300 Subject: add missing infotext entry for the pad cond/uncond option --- modules/generation_parameters_copypaste.py | 1 + modules/sd_samplers_kdiffusion.py | 11 ++++++++++- 2 files changed, 11 insertions(+), 1 deletion(-) (limited to 'modules/generation_parameters_copypaste.py') diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index a638f912..dd30a1b5 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -357,6 +357,7 @@ infotext_to_setting_name_mapping = [ ('Token merging ratio hr', 'token_merging_ratio_hr'), ('RNG', 'randn_source'), ('NGMS', 's_min_uncond'), + ('Pad conds', 'pad_cond_uncond'), ] diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index f8a0c7ba..71581b76 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -69,6 +69,7 @@ class CFGDenoiser(torch.nn.Module): self.init_latent = None self.step = 0 self.image_cfg_scale = None + self.padded_cond_uncond = False def combine_denoised(self, x_out, conds_list, uncond, cond_scale): denoised_uncond = x_out[-uncond.shape[0]:] @@ -133,15 +134,17 @@ class CFGDenoiser(torch.nn.Module): x_in = x_in[:-batch_size] sigma_in = sigma_in[:-batch_size] - # TODO add infotext entry + self.padded_cond_uncond = False if shared.opts.pad_cond_uncond and tensor.shape[1] != uncond.shape[1]: empty = shared.sd_model.cond_stage_model_empty_prompt num_repeats = (tensor.shape[1] - uncond.shape[1]) // empty.shape[1] if num_repeats < 0: tensor = torch.cat([tensor, empty.repeat((tensor.shape[0], -num_repeats, 1))], axis=1) + self.padded_cond_uncond = True elif num_repeats > 0: uncond = torch.cat([uncond, empty.repeat((uncond.shape[0], num_repeats, 1))], axis=1) + self.padded_cond_uncond = True if tensor.shape[1] == uncond.shape[1] or skip_uncond: if is_edit_model: @@ -405,6 +408,9 @@ class KDiffusionSampler: samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs)) + if self.model_wrap_cfg.padded_cond_uncond: + p.extra_generation_params["Pad conds"] = True + return samples def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None): @@ -438,5 +444,8 @@ class KDiffusionSampler: 's_min_uncond': self.s_min_uncond }, disable=False, callback=self.callback_state, **extra_params_kwargs)) + if self.model_wrap_cfg.padded_cond_uncond: + p.extra_generation_params["Pad conds"] = True + return samples -- cgit v1.2.3