From 06f167da37cd00ea8241bd2a6a3c12d8c5fb9eaf Mon Sep 17 00:00:00 2001 From: Aarni Koskela Date: Mon, 6 Mar 2023 21:14:06 +0200 Subject: Extra networks: support .txt description sidecar file --- html/extra-networks-card.html | 1 + 1 file changed, 1 insertion(+) (limited to 'html') diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html index 8a5e2fbd..8612396d 100644 --- a/html/extra-networks-card.html +++ b/html/extra-networks-card.html @@ -7,6 +7,7 @@ {name} + {description} -- cgit v1.2.3 From fec0a895119a124a295e3dad5205de5766031dc7 Mon Sep 17 00:00:00 2001 From: Pam Date: Tue, 7 Mar 2023 00:33:13 +0500 Subject: scaled dot product attention --- html/licenses.html | 219 +++++++++++++++++++++++++++++++++++++ modules/sd_hijack.py | 4 + modules/sd_hijack_optimizations.py | 42 +++++++ modules/shared.py | 1 + 4 files changed, 266 insertions(+) (limited to 'html') diff --git a/html/licenses.html b/html/licenses.html index 570630eb..bddbf466 100644 --- a/html/licenses.html +++ b/html/licenses.html @@ -417,3 +417,222 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. +

Scaled Dot Product Attention

+Some small amounts of code borrowed and reworked. +
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\ No newline at end of file diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py index 79476783..76cb9120 100644 --- a/modules/sd_hijack.py +++ b/modules/sd_hijack.py @@ -42,6 +42,10 @@ def apply_optimizations(): ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.xformers_attention_forward ldm.modules.diffusionmodules.model.AttnBlock.forward = sd_hijack_optimizations.xformers_attnblock_forward optimization_method = 'xformers' + elif cmd_opts.opt_sdp_attention and (hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(getattr(torch.nn.functional, "scaled_dot_product_attention"))): + print("Applying scaled dot product cross attention optimization.") + ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.scaled_dot_product_attention_forward + optimization_method = 'sdp' elif cmd_opts.opt_sub_quad_attention: print("Applying sub-quadratic cross attention optimization.") ldm.modules.attention.CrossAttention.forward = sd_hijack_optimizations.sub_quad_attention_forward diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py index c02d954c..a324a592 100644 --- a/modules/sd_hijack_optimizations.py +++ b/modules/sd_hijack_optimizations.py @@ -346,6 +346,48 @@ def xformers_attention_forward(self, x, context=None, mask=None): out = rearrange(out, 'b n h d -> b n (h d)', h=h) return self.to_out(out) +# Based on Diffusers usage of scaled dot product attention from https://github.com/huggingface/diffusers/blob/c7da8fd23359a22d0df2741688b5b4f33c26df21/src/diffusers/models/cross_attention.py +# The scaled_dot_product_attention_forward function contains parts of code under Apache-2.0 license listed under Scaled Dot Product Attention in the Licenses section of the web UI interface +def scaled_dot_product_attention_forward(self, x, context=None, mask=None): + batch_size, sequence_length, inner_dim = x.shape + + if mask is not None: + mask = self.prepare_attention_mask(mask, sequence_length, batch_size) + mask = mask.view(batch_size, self.heads, -1, mask.shape[-1]) + + h = self.heads + q_in = self.to_q(x) + context = default(context, x) + + context_k, context_v = hypernetwork.apply_hypernetworks(shared.loaded_hypernetworks, context) + k_in = self.to_k(context_k) + v_in = self.to_v(context_v) + + head_dim = inner_dim // h + q = q_in.view(batch_size, -1, h, head_dim).transpose(1, 2) + k = k_in.view(batch_size, -1, h, head_dim).transpose(1, 2) + v = v_in.view(batch_size, -1, h, head_dim).transpose(1, 2) + + del q_in, k_in, v_in + + dtype = q.dtype + if shared.opts.upcast_attn: + q, k = q.float(), k.float() + + # the output of sdp = (batch, num_heads, seq_len, head_dim) + hidden_states = torch.nn.functional.scaled_dot_product_attention( + q, k, v, attn_mask=mask, dropout_p=0.0, is_causal=False + ) + + hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, h * head_dim) + hidden_states = hidden_states.to(dtype) + + # linear proj + hidden_states = self.to_out[0](hidden_states) + # dropout + hidden_states = self.to_out[1](hidden_states) + return hidden_states + def cross_attention_attnblock_forward(self, x): h_ = x h_ = self.norm(h_) diff --git a/modules/shared.py b/modules/shared.py index 805f9cc1..12d0756b 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -69,6 +69,7 @@ parser.add_argument("--sub-quad-kv-chunk-size", type=int, help="kv chunk size fo parser.add_argument("--sub-quad-chunk-threshold", type=int, help="the percentage of VRAM threshold for the sub-quadratic cross-attention layer optimization to use chunking", default=None) parser.add_argument("--opt-split-attention-invokeai", action='store_true', help="force-enables InvokeAI's cross-attention layer optimization. By default, it's on when cuda is unavailable.") parser.add_argument("--opt-split-attention-v1", action='store_true', help="enable older version of split attention optimization that does not consume all the VRAM it can find") +parser.add_argument("--opt-sdp-attention", action='store_true', help="enable scaled dot product cross-attention layer optimization; requires PyTorch 2.*") parser.add_argument("--disable-opt-split-attention", action='store_true', help="force-disables cross-attention layer optimization") parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI") parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower) -- cgit v1.2.3 From c19530f1a590d758463f84523dd4c48c34d723e6 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Tue, 14 Mar 2023 09:10:26 +0300 Subject: Add view metadata button for Lora cards. --- extensions-builtin/Lora/lora.py | 21 +++++++- extensions-builtin/Lora/ui_extra_networks_lora.py | 1 + html/extra-networks-card.html | 2 + javascript/extraNetworks.js | 38 +++++++++++++- modules/sd_models.py | 24 +++++++++ modules/ui_extra_networks.py | 7 +++ style.css | 61 +++++++++++++++++++++++ 7 files changed, 152 insertions(+), 2 deletions(-) (limited to 'html') diff --git a/extensions-builtin/Lora/lora.py b/extensions-builtin/Lora/lora.py index cb8f1d36..8937b585 100644 --- a/extensions-builtin/Lora/lora.py +++ b/extensions-builtin/Lora/lora.py @@ -3,7 +3,9 @@ import os import re import torch -from modules import shared, devices, sd_models +from modules import shared, devices, sd_models, errors + +metadata_tags_order = {"ss_sd_model_name": 1, "ss_resolution": 2, "ss_clip_skip": 3, "ss_num_train_images": 10, "ss_tag_frequency": 20} re_digits = re.compile(r"\d+") re_unet_down_blocks = re.compile(r"lora_unet_down_blocks_(\d+)_attentions_(\d+)_(.+)") @@ -43,6 +45,23 @@ class LoraOnDisk: def __init__(self, name, filename): self.name = name self.filename = filename + self.metadata = {} + + _, ext = os.path.splitext(filename) + if ext.lower() == ".safetensors": + try: + self.metadata = sd_models.read_metadata_from_safetensors(filename) + except Exception as e: + errors.display(e, f"reading lora {filename}") + + if self.metadata: + m = {} + for k, v in sorted(self.metadata.items(), key=lambda x: metadata_tags_order.get(x[0], 999)): + m[k] = v + + self.metadata = m + + self.ssmd_cover_images = self.metadata.pop('ssmd_cover_images', None) # those are cover images and they are too big to display in UI as text class LoraModule: diff --git a/extensions-builtin/Lora/ui_extra_networks_lora.py b/extensions-builtin/Lora/ui_extra_networks_lora.py index 8d32052e..68b11332 100644 --- a/extensions-builtin/Lora/ui_extra_networks_lora.py +++ b/extensions-builtin/Lora/ui_extra_networks_lora.py @@ -23,6 +23,7 @@ class ExtraNetworksPageLora(ui_extra_networks.ExtraNetworksPage): "search_term": self.search_terms_from_path(lora_on_disk.filename), "prompt": json.dumps(f""), "local_preview": f"{path}.{shared.opts.samples_format}", + "metadata": json.dumps(lora_on_disk.metadata, indent=4) if lora_on_disk.metadata else None, } def allowed_directories_for_previews(self): diff --git a/html/extra-networks-card.html b/html/extra-networks-card.html index 8612396d..1bf3fc30 100644 --- a/html/extra-networks-card.html +++ b/html/extra-networks-card.html @@ -1,4 +1,6 @@
+ {metadata_button} +
    diff --git a/javascript/extraNetworks.js b/javascript/extraNetworks.js index d0177ad6..2fb87cd5 100644 --- a/javascript/extraNetworks.js +++ b/javascript/extraNetworks.js @@ -102,4 +102,40 @@ function extraNetworksSearchButton(tabs_id, event){ searchTextarea.value = text updateInput(searchTextarea) -} \ No newline at end of file +} + +var globalPopup = null; +var globalPopupInner = null; +function popup(contents){ + if(! globalPopup){ + globalPopup = document.createElement('div') + globalPopup.onclick = function(){ globalPopup.style.display = "none"; }; + globalPopup.classList.add('global-popup'); + + var close = document.createElement('div') + close.classList.add('global-popup-close'); + close.onclick = function(){ globalPopup.style.display = "none"; }; + close.title = "Close"; + globalPopup.appendChild(close) + + globalPopupInner = document.createElement('div') + globalPopupInner.onclick = function(event){ event.stopPropagation(); return false; }; + globalPopupInner.classList.add('global-popup-inner'); + globalPopup.appendChild(globalPopupInner) + + gradioApp().appendChild(globalPopup); + } + + globalPopupInner.innerHTML = ''; + globalPopupInner.appendChild(contents); + + globalPopup.style.display = "flex"; +} + +function extraNetworksShowMetadata(text){ + elem = document.createElement('pre') + elem.classList.add('popup-metadata'); + elem.textContent = text; + + popup(elem); +} diff --git a/modules/sd_models.py b/modules/sd_models.py index 93959f55..5f57ec0c 100644 --- a/modules/sd_models.py +++ b/modules/sd_models.py @@ -210,6 +210,30 @@ def get_state_dict_from_checkpoint(pl_sd): return pl_sd +def read_metadata_from_safetensors(filename): + import json + + with open(filename, mode="rb") as file: + metadata_len = file.read(8) + metadata_len = int.from_bytes(metadata_len, "little") + json_start = file.read(2) + + assert metadata_len > 2 and json_start in (b'{"', b"{'"), f"{filename} is not a safetensors file" + json_data = json_start + file.read(metadata_len-2) + json_obj = json.loads(json_data) + + res = {} + for k, v in json_obj.get("__metadata__", {}).items(): + res[k] = v + if isinstance(v, str) and v[0] == '{': + try: + res[k] = json.loads(v) + except Exception as e: + pass + + return res + + def read_state_dict(checkpoint_file, print_global_state=False, map_location=None): _, extension = os.path.splitext(checkpoint_file) if extension.lower() == ".safetensors": diff --git a/modules/ui_extra_networks.py b/modules/ui_extra_networks.py index 01df5e90..b5847299 100644 --- a/modules/ui_extra_networks.py +++ b/modules/ui_extra_networks.py @@ -124,6 +124,12 @@ class ExtraNetworksPage: if onclick is None: onclick = '"' + html.escape(f"""return cardClicked({json.dumps(tabname)}, {item["prompt"]}, {"true" if self.allow_negative_prompt else "false"})""") + '"' + metadata_button = "" + metadata = item.get("metadata") + if metadata: + metadata_onclick = '"' + html.escape(f"""extraNetworksShowMetadata({json.dumps(metadata)}); return false;""") + '"' + metadata_button = f"
    " + args = { "preview_html": "style='background-image: url(\"" + html.escape(preview) + "\")'" if preview else '', "prompt": item.get("prompt", None), @@ -134,6 +140,7 @@ class ExtraNetworksPage: "card_clicked": onclick, "save_card_preview": '"' + html.escape(f"""return saveCardPreview(event, {json.dumps(tabname)}, {json.dumps(item["local_preview"])})""") + '"', "search_term": item.get("search_term", ""), + "metadata_button": metadata_button, } return self.card_page.format(**args) diff --git a/style.css b/style.css index 2f26ad02..3eac2b17 100644 --- a/style.css +++ b/style.css @@ -362,6 +362,46 @@ input[type="range"]{ height: 100%; } +.popup-metadata{ + color: black; + background: white; + display: inline-block; + padding: 1em; + white-space: pre-wrap; +} + +.global-popup{ + display: flex; + position: fixed; + z-index: 1001; + left: 0; + top: 0; + width: 100%; + height: 100%; + overflow: auto; + background-color: rgba(20, 20, 20, 0.95); +} + + +.global-popup-close:before { + content: "×"; +} + +.global-popup-close{ + position: fixed; + right: 0.25em; + top: 0; + cursor: pointer; + color: white; + font-size: 32pt; +} + +.global-popup-inner{ + display: inline-block; + margin: auto; + padding: 2em; +} + #lightboxModal{ display: none; position: fixed; @@ -837,6 +877,27 @@ footer { margin-left: 0.5em; } + +.extra-network-cards .card .metadata-button:before, .extra-network-thumbs .card .metadata-button:before{ + content: "🛈"; +} +.extra-network-cards .card .metadata-button, .extra-network-thumbs .card .metadata-button{ + display: none; + position: absolute; + right: 0; + color: white; + text-shadow: 2px 2px 3px black; + padding: 0.25em; + font-size: 22pt; +} +.extra-network-cards .card:hover .metadata-button, .extra-network-thumbs .card:hover .metadata-button{ + display: inline-block; +} +.extra-network-cards .card .metadata-button:hover, .extra-network-thumbs .card .metadata-button:hover{ + color: red; +} + + .extra-network-thumbs { display: flex; flex-flow: row wrap; -- cgit v1.2.3 From c5142e2fbecb50531a55aa804ea132c5d870858c Mon Sep 17 00:00:00 2001 From: brkirch Date: Fri, 24 Mar 2023 02:58:18 -0400 Subject: Add workaround for broken nn.Linear on macOS 13.2 Credit to danieldk (https://github.com/explosion/curated-transformers/pull/124) for the workaround this is based on. --- html/licenses.html | 26 ++++++++++++++++++++++++++ modules/mac_specific.py | 5 +++++ 2 files changed, 31 insertions(+) (limited to 'html') diff --git a/html/licenses.html b/html/licenses.html index bddbf466..bc995aa0 100644 --- a/html/licenses.html +++ b/html/licenses.html @@ -635,4 +635,30 @@ SOFTWARE. WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. + + +

    Curated transformers

    +The MPS workaround for nn.Linear on macOS 13.2.X is based on the MPS workaround for nn.Linear created by danieldk for Curated transformers +
    +The MIT License (MIT)
+
+Copyright (C) 2021 ExplosionAI GmbH
+
+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.
    \ No newline at end of file diff --git a/modules/mac_specific.py b/modules/mac_specific.py index 18e6ff72..3a170f60 100644 --- a/modules/mac_specific.py +++ b/modules/mac_specific.py @@ -1,4 +1,5 @@ import torch +import platform from modules import paths from modules.sd_hijack_utils import CondFunc from packaging import version @@ -32,6 +33,10 @@ if has_mps: # MPS fix for randn in torchsde CondFunc('torchsde._brownian.brownian_interval._randn', lambda _, size, dtype, device, seed: torch.randn(size, dtype=dtype, device=torch.device("cpu"), generator=torch.Generator(torch.device("cpu")).manual_seed(int(seed))).to(device), lambda _, size, dtype, device, seed: device.type == 'mps') + if platform.mac_ver()[0].startswith("13.2."): + # MPS workaround for https://github.com/pytorch/pytorch/issues/95188, thanks to danieldk (https://github.com/explosion/curated-transformers/pull/124) + CondFunc('torch.nn.functional.linear', lambda _, input, weight, bias: (torch.matmul(input, weight.t()) + bias) if bias is not None else torch.matmul(input, weight.t()), lambda _, input, weight, bias: input.numel() > 10485760) + if version.parse(torch.__version__) < version.parse("1.13"): # PyTorch 1.13 doesn't need these fixes but unfortunately is slower and has regressions that prevent training from working -- cgit v1.2.3