add textual inversion hashes to infotext

5 files changed, 29 insertions, 8 deletions

diff --git a/modules/processing.py b/modules/processing.py
index cd568a20..49441e77 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -732,9 +732,10 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
 

             p.setup_conds()

 

-            if len(model_hijack.comments) > 0:

-                for comment in model_hijack.comments:

-                    comments[comment] = 1

+            for comment in model_hijack.comments:

+                comments[comment] = 1

+

+            p.extra_generation_params.update(model_hijack.extra_generation_params)

 

             if p.n_iter > 1:

                 shared.state.job = f"Batch {n+1} out of {p.n_iter}"

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 3b6f95ce..6b5aae4b 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -147,7 +147,6 @@ def undo_weighted_forward(sd_model):
 

 class StableDiffusionModelHijack:

     fixes = None

-    comments = []

     layers = None

     circular_enabled = False

     clip = None

@@ -156,6 +155,9 @@ class StableDiffusionModelHijack:
     embedding_db = modules.textual_inversion.textual_inversion.EmbeddingDatabase()

 

     def __init__(self):

+        self.extra_generation_params = {}

+        self.comments = []

+

         self.embedding_db.add_embedding_dir(cmd_opts.embeddings_dir)

 

     def apply_optimizations(self, option=None):

@@ -236,6 +238,7 @@ class StableDiffusionModelHijack:
 

     def clear_comments(self):

         self.comments = []

+        self.extra_generation_params = {}

 

     def get_prompt_lengths(self, text):

         if self.clip is None:

diff --git a/modules/sd_hijack_clip.py b/modules/sd_hijack_clip.py
index 3b5a7666..c1d780a3 100644
--- a/modules/sd_hijack_clip.py
+++ b/modules/sd_hijack_clip.py
@@ -229,9 +229,18 @@ class FrozenCLIPEmbedderWithCustomWordsBase(torch.nn.Module):
             z = self.process_tokens(tokens, multipliers)

             zs.append(z)

 

-        if len(used_embeddings) > 0:

-            embeddings_list = ", ".join([f'{name} [{embedding.checksum()}]' for name, embedding in used_embeddings.items()])

-            self.hijack.comments.append(f"Used embeddings: {embeddings_list}")

+        if opts.textual_inversion_add_hashes_to_infotext and used_embeddings:

+            hashes = []

+            for name, embedding in used_embeddings.items():

+                shorthash = embedding.shorthash

+                if not shorthash:

+                    continue

+

+                name = name.replace(":", "").replace(",", "")

+                hashes.append(f"{name}: {shorthash}")

+

+            if hashes:

+                self.hijack.extra_generation_params["TI hashes"] = ", ".join(hashes)

 

         return torch.hstack(zs)

 

diff --git a/modules/shared.py b/modules/shared.py
index 48478a68..a32fd4ed 100644
--- a/modules/shared.py
+++ b/modules/shared.py
@@ -472,6 +472,7 @@ options_templates.update(options_section(('extra_networks', "Extra Networks"), {
     "extra_networks_card_height": OptionInfo(0, "Card height for Extra Networks").info("in pixels"),

     "extra_networks_add_text_separator": OptionInfo(" ", "Extra networks separator").info("extra text to add before <...> when adding extra network to prompt"),

     "ui_extra_networks_tab_reorder": OptionInfo("", "Extra networks tab order").needs_restart(),

+    "textual_inversion_add_hashes_to_infotext": OptionInfo(True, "Add Textual Inversion hashes to infotext"),

     "sd_hypernetwork": OptionInfo("None", "Add hypernetwork to prompt", gr.Dropdown, lambda: {"choices": ["None", *hypernetworks]}, refresh=reload_hypernetworks),

 }))

 

diff --git a/modules/textual_inversion/textual_inversion.py b/modules/textual_inversion/textual_inversion.py
index cbe975b7..38e072a8 100644
--- a/modules/textual_inversion/textual_inversion.py
+++ b/modules/textual_inversion/textual_inversion.py
@@ -13,7 +13,7 @@ import numpy as np
 from PIL import Image, PngImagePlugin

 from torch.utils.tensorboard import SummaryWriter

 

-from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors

+from modules import shared, devices, sd_hijack, processing, sd_models, images, sd_samplers, sd_hijack_checkpoint, errors, hashes

 import modules.textual_inversion.dataset

 from modules.textual_inversion.learn_schedule import LearnRateScheduler

 

@@ -49,6 +49,8 @@ class Embedding:
         self.sd_checkpoint_name = None

         self.optimizer_state_dict = None

         self.filename = None

+        self.hash = None

+        self.shorthash = None

 

     def save(self, filename):

         embedding_data = {

@@ -82,6 +84,10 @@ class Embedding:
         self.cached_checksum = f'{const_hash(self.vec.reshape(-1) * 100) & 0xffff:04x}'

         return self.cached_checksum

 

+    def set_hash(self, v):

+        self.hash = v

+        self.shorthash = self.hash[0:12]

+

 

 class DirWithTextualInversionEmbeddings:

     def __init__(self, path):

@@ -199,6 +205,7 @@ class EmbeddingDatabase:
         embedding.vectors = vec.shape[0]

         embedding.shape = vec.shape[-1]

         embedding.filename = path

+        embedding.set_hash(hashes.sha256(embedding.filename, "textual_inversion/" + name) or '')

 

         if self.expected_shape == -1 or self.expected_shape == embedding.shape:

             self.register_embedding(embedding, shared.sd_model)