From 4b854806d98cf5ccd48e5cd99c172613da7937f0 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Wed, 10 May 2023 09:02:23 +0300 Subject: F401 fixes for ruff --- modules/paths.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'modules/paths.py') diff --git a/modules/paths.py b/modules/paths.py index acf1894b..5f6474c0 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -1,8 +1,8 @@ import os import sys -from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir +from modules.paths_internal import models_path, script_path, data_path, extensions_dir, extensions_builtin_dir # noqa: F401 -import modules.safe +import modules.safe # noqa: F401 # data_path = cmd_opts_pre.data -- cgit v1.2.3 From 5fcdaa6a7f19d083a6393cc0d2b933ff5080f5b3 Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Tue, 30 May 2023 12:36:55 +0300 Subject: Vendor in the single module used from taming_transformers; remove taming_transformers dependency (and fix the two ruff complaints) --- extensions-builtin/LDSR/sd_hijack_autoencoder.py | 2 +- extensions-builtin/LDSR/vqvae_quantize.py | 147 +++++++++++++++++++++++ modules/launch_utils.py | 3 - modules/paths.py | 1 - webui-user.sh | 1 - 5 files changed, 148 insertions(+), 6 deletions(-) create mode 100644 extensions-builtin/LDSR/vqvae_quantize.py (limited to 'modules/paths.py') diff --git a/extensions-builtin/LDSR/sd_hijack_autoencoder.py b/extensions-builtin/LDSR/sd_hijack_autoencoder.py index 81c5101b..27a86e13 100644 --- a/extensions-builtin/LDSR/sd_hijack_autoencoder.py +++ b/extensions-builtin/LDSR/sd_hijack_autoencoder.py @@ -10,7 +10,7 @@ from contextlib import contextmanager from torch.optim.lr_scheduler import LambdaLR from ldm.modules.ema import LitEma -from taming.modules.vqvae.quantize import VectorQuantizer2 as VectorQuantizer +from vqvae_quantize import VectorQuantizer2 as VectorQuantizer from ldm.modules.diffusionmodules.model import Encoder, Decoder from ldm.util import instantiate_from_config diff --git a/extensions-builtin/LDSR/vqvae_quantize.py b/extensions-builtin/LDSR/vqvae_quantize.py new file mode 100644 index 00000000..dd14b8fd --- /dev/null +++ b/extensions-builtin/LDSR/vqvae_quantize.py @@ -0,0 +1,147 @@ +# Vendored from https://raw.githubusercontent.com/CompVis/taming-transformers/24268930bf1dce879235a7fddd0b2355b84d7ea6/taming/modules/vqvae/quantize.py, +# where the license is as follows: +# +# Copyright (c) 2020 Patrick Esser and Robin Rombach and Björn Ommer +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. +# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, +# DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR +# OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE +# OR OTHER DEALINGS IN THE SOFTWARE./ + +import torch +import torch.nn as nn +import numpy as np +from einops import rearrange + + +class VectorQuantizer2(nn.Module): + """ + Improved version over VectorQuantizer, can be used as a drop-in replacement. Mostly + avoids costly matrix multiplications and allows for post-hoc remapping of indices. + """ + + # NOTE: due to a bug the beta term was applied to the wrong term. for + # backwards compatibility we use the buggy version by default, but you can + # specify legacy=False to fix it. + def __init__(self, n_e, e_dim, beta, remap=None, unknown_index="random", + sane_index_shape=False, legacy=True): + super().__init__() + self.n_e = n_e + self.e_dim = e_dim + self.beta = beta + self.legacy = legacy + + self.embedding = nn.Embedding(self.n_e, self.e_dim) + self.embedding.weight.data.uniform_(-1.0 / self.n_e, 1.0 / self.n_e) + + self.remap = remap + if self.remap is not None: + self.register_buffer("used", torch.tensor(np.load(self.remap))) + self.re_embed = self.used.shape[0] + self.unknown_index = unknown_index # "random" or "extra" or integer + if self.unknown_index == "extra": + self.unknown_index = self.re_embed + self.re_embed = self.re_embed + 1 + print(f"Remapping {self.n_e} indices to {self.re_embed} indices. " + f"Using {self.unknown_index} for unknown indices.") + else: + self.re_embed = n_e + + self.sane_index_shape = sane_index_shape + + def remap_to_used(self, inds): + ishape = inds.shape + assert len(ishape) > 1 + inds = inds.reshape(ishape[0], -1) + used = self.used.to(inds) + match = (inds[:, :, None] == used[None, None, ...]).long() + new = match.argmax(-1) + unknown = match.sum(2) < 1 + if self.unknown_index == "random": + new[unknown] = torch.randint(0, self.re_embed, size=new[unknown].shape).to(device=new.device) + else: + new[unknown] = self.unknown_index + return new.reshape(ishape) + + def unmap_to_all(self, inds): + ishape = inds.shape + assert len(ishape) > 1 + inds = inds.reshape(ishape[0], -1) + used = self.used.to(inds) + if self.re_embed > self.used.shape[0]: # extra token + inds[inds >= self.used.shape[0]] = 0 # simply set to zero + back = torch.gather(used[None, :][inds.shape[0] * [0], :], 1, inds) + return back.reshape(ishape) + + def forward(self, z, temp=None, rescale_logits=False, return_logits=False): + assert temp is None or temp == 1.0, "Only for interface compatible with Gumbel" + assert rescale_logits is False, "Only for interface compatible with Gumbel" + assert return_logits is False, "Only for interface compatible with Gumbel" + # reshape z -> (batch, height, width, channel) and flatten + z = rearrange(z, 'b c h w -> b h w c').contiguous() + z_flattened = z.view(-1, self.e_dim) + # distances from z to embeddings e_j (z - e)^2 = z^2 + e^2 - 2 e * z + + d = torch.sum(z_flattened ** 2, dim=1, keepdim=True) + \ + torch.sum(self.embedding.weight ** 2, dim=1) - 2 * \ + torch.einsum('bd,dn->bn', z_flattened, rearrange(self.embedding.weight, 'n d -> d n')) + + min_encoding_indices = torch.argmin(d, dim=1) + z_q = self.embedding(min_encoding_indices).view(z.shape) + perplexity = None + min_encodings = None + + # compute loss for embedding + if not self.legacy: + loss = self.beta * torch.mean((z_q.detach() - z) ** 2) + \ + torch.mean((z_q - z.detach()) ** 2) + else: + loss = torch.mean((z_q.detach() - z) ** 2) + self.beta * \ + torch.mean((z_q - z.detach()) ** 2) + + # preserve gradients + z_q = z + (z_q - z).detach() + + # reshape back to match original input shape + z_q = rearrange(z_q, 'b h w c -> b c h w').contiguous() + + if self.remap is not None: + min_encoding_indices = min_encoding_indices.reshape(z.shape[0], -1) # add batch axis + min_encoding_indices = self.remap_to_used(min_encoding_indices) + min_encoding_indices = min_encoding_indices.reshape(-1, 1) # flatten + + if self.sane_index_shape: + min_encoding_indices = min_encoding_indices.reshape( + z_q.shape[0], z_q.shape[2], z_q.shape[3]) + + return z_q, loss, (perplexity, min_encodings, min_encoding_indices) + + def get_codebook_entry(self, indices, shape): + # shape specifying (batch, height, width, channel) + if self.remap is not None: + indices = indices.reshape(shape[0], -1) # add batch axis + indices = self.unmap_to_all(indices) + indices = indices.reshape(-1) # flatten again + + # get quantized latent vectors + z_q = self.embedding(indices) + + if shape is not None: + z_q = z_q.view(shape) + # reshape back to match original input shape + z_q = z_q.permute(0, 3, 1, 2).contiguous() + + return z_q diff --git a/modules/launch_utils.py b/modules/launch_utils.py index 35a52310..ca089674 100644 --- a/modules/launch_utils.py +++ b/modules/launch_utils.py @@ -229,13 +229,11 @@ def prepare_environment(): openclip_package = os.environ.get('OPENCLIP_PACKAGE', "https://github.com/mlfoundations/open_clip/archive/bb6e834e9c70d9c27d0dc3ecedeebeaeb1ffad6b.zip") stable_diffusion_repo = os.environ.get('STABLE_DIFFUSION_REPO', "https://github.com/Stability-AI/stablediffusion.git") - taming_transformers_repo = os.environ.get('TAMING_TRANSFORMERS_REPO', "https://github.com/CompVis/taming-transformers.git") k_diffusion_repo = os.environ.get('K_DIFFUSION_REPO', 'https://github.com/crowsonkb/k-diffusion.git') codeformer_repo = os.environ.get('CODEFORMER_REPO', 'https://github.com/sczhou/CodeFormer.git') blip_repo = os.environ.get('BLIP_REPO', 'https://github.com/salesforce/BLIP.git') stable_diffusion_commit_hash = os.environ.get('STABLE_DIFFUSION_COMMIT_HASH', "cf1d67a6fd5ea1aa600c4df58e5b47da45f6bdbf") - taming_transformers_commit_hash = os.environ.get('TAMING_TRANSFORMERS_COMMIT_HASH', "24268930bf1dce879235a7fddd0b2355b84d7ea6") k_diffusion_commit_hash = os.environ.get('K_DIFFUSION_COMMIT_HASH', "c9fe758757e022f05ca5a53fa8fac28889e4f1cf") codeformer_commit_hash = os.environ.get('CODEFORMER_COMMIT_HASH', "c5b4593074ba6214284d6acd5f1719b6c5d739af") blip_commit_hash = os.environ.get('BLIP_COMMIT_HASH', "48211a1594f1321b00f14c9f7a5b4813144b2fb9") @@ -286,7 +284,6 @@ def prepare_environment(): os.makedirs(os.path.join(script_path, dir_repos), exist_ok=True) git_clone(stable_diffusion_repo, repo_dir('stable-diffusion-stability-ai'), "Stable Diffusion", stable_diffusion_commit_hash) - git_clone(taming_transformers_repo, repo_dir('taming-transformers'), "Taming Transformers", taming_transformers_commit_hash) git_clone(k_diffusion_repo, repo_dir('k-diffusion'), "K-diffusion", k_diffusion_commit_hash) git_clone(codeformer_repo, repo_dir('CodeFormer'), "CodeFormer", codeformer_commit_hash) git_clone(blip_repo, repo_dir('BLIP'), "BLIP", blip_commit_hash) diff --git a/modules/paths.py b/modules/paths.py index 5f6474c0..5171df4f 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -20,7 +20,6 @@ assert sd_path is not None, f"Couldn't find Stable Diffusion in any of: {possibl path_dirs = [ (sd_path, 'ldm', 'Stable Diffusion', []), - (os.path.join(sd_path, '../taming-transformers'), 'taming', 'Taming Transformers', []), (os.path.join(sd_path, '../CodeFormer'), 'inference_codeformer.py', 'CodeFormer', []), (os.path.join(sd_path, '../BLIP'), 'models/blip.py', 'BLIP', []), (os.path.join(sd_path, '../k-diffusion'), 'k_diffusion/sampling.py', 'k_diffusion', ["atstart"]), diff --git a/webui-user.sh b/webui-user.sh index 49a426ff..70306c60 100644 --- a/webui-user.sh +++ b/webui-user.sh @@ -36,7 +36,6 @@ # Fixed git commits #export STABLE_DIFFUSION_COMMIT_HASH="" -#export TAMING_TRANSFORMERS_COMMIT_HASH="" #export CODEFORMER_COMMIT_HASH="" #export BLIP_COMMIT_HASH="" -- cgit v1.2.3 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/api/api.py | 7 ------- modules/api/models.py | 4 ---- modules/codeformer_model.py | 4 ---- modules/devices.py | 7 ------- modules/generation_parameters_copypaste.py | 29 ----------------------------- modules/hypernetworks/hypernetwork.py | 24 ------------------------ modules/paths.py | 14 -------------- 7 files changed, 89 deletions(-) (limited to 'modules/paths.py') diff --git a/modules/api/api.py b/modules/api/api.py index 2e49526e..41cd7eca 100644 --- a/modules/api/api.py +++ b/modules/api/api.py @@ -32,13 +32,6 @@ import piexif import piexif.helper -def upscaler_to_index(name: str): - try: - return [x.name.lower() for x in shared.sd_upscalers].index(name.lower()) - except Exception as e: - raise HTTPException(status_code=400, detail=f"Invalid upscaler, needs to be one of these: {' , '.join([x.name for x in shared.sd_upscalers])}") from e - - def script_name_to_index(name, scripts): try: return [script.title().lower() for script in scripts].index(name.lower()) diff --git a/modules/api/models.py b/modules/api/models.py index b3a745f0..b5683071 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -274,10 +274,6 @@ class PromptStyleItem(BaseModel): prompt: Optional[str] = Field(title="Prompt") negative_prompt: Optional[str] = Field(title="Negative Prompt") -class ArtistItem(BaseModel): - name: str = Field(title="Name") - score: float = Field(title="Score") - category: str = Field(title="Category") class EmbeddingItem(BaseModel): step: Optional[int] = Field(title="Step", description="The number of steps that were used to train this embedding, if available") diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py index 4260b016..a01fe63d 100644 --- a/modules/codeformer_model.py +++ b/modules/codeformer_model.py @@ -15,7 +15,6 @@ model_dir = "Codeformer" model_path = os.path.join(models_path, model_dir) model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth' -have_codeformer = False codeformer = None @@ -125,9 +124,6 @@ def setup_model(dirname): return restored_img - global have_codeformer - have_codeformer = True - global codeformer codeformer = FaceRestorerCodeFormer(dirname) shared.face_restorers.append(codeformer) diff --git a/modules/devices.py b/modules/devices.py index 1ed6ffdc..620ed1a6 100644 --- a/modules/devices.py +++ b/modules/devices.py @@ -15,13 +15,6 @@ def has_mps() -> bool: else: return mac_specific.has_mps -def extract_device_id(args, name): - for x in range(len(args)): - if name in args[x]: - return args[x + 1] - - return None - def get_cuda_device_string(): from modules import shared 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'), diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 5d12b449..51941c11 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -353,17 +353,6 @@ def load_hypernetworks(names, multipliers=None): shared.loaded_hypernetworks.append(hypernetwork) -def find_closest_hypernetwork_name(search: str): - if not search: - return None - search = search.lower() - applicable = [name for name in shared.hypernetworks if search in name.lower()] - if not applicable: - return None - applicable = sorted(applicable, key=lambda name: len(name)) - return applicable[0] - - def apply_single_hypernetwork(hypernetwork, context_k, context_v, layer=None): hypernetwork_layers = (hypernetwork.layers if hypernetwork is not None else {}).get(context_k.shape[2], None) @@ -446,18 +435,6 @@ def statistics(data): return total_information, recent_information -def report_statistics(loss_info:dict): - keys = sorted(loss_info.keys(), key=lambda x: sum(loss_info[x]) / len(loss_info[x])) - for key in keys: - try: - print("Loss statistics for file " + key) - info, recent = statistics(list(loss_info[key])) - print(info) - print(recent) - except Exception as e: - print(e) - - def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, dropout_structure=None): # Remove illegal characters from name. name = "".join( x for x in name if (x.isalnum() or x in "._- ")) @@ -770,7 +747,6 @@ Last saved image: {html.escape(last_saved_image)}
pbar.leave = False pbar.close() hypernetwork.eval() - #report_statistics(loss_dict) sd_hijack_checkpoint.remove() diff --git a/modules/paths.py b/modules/paths.py index 5171df4f..bada804e 100644 --- a/modules/paths.py +++ b/modules/paths.py @@ -38,17 +38,3 @@ for d, must_exist, what, options in path_dirs: else: sys.path.append(d) paths[what] = d - - -class Prioritize: - def __init__(self, name): - self.name = name - self.path = None - - def __enter__(self): - self.path = sys.path.copy() - sys.path = [paths[self.name]] + sys.path - - def __exit__(self, exc_type, exc_val, exc_tb): - sys.path = self.path - self.path = None -- cgit v1.2.3