From 2b1bae0d755c2d5201f6a6aadeadb5588208d43f Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sat, 15 Jul 2023 08:41:22 +0300
Subject: add textual inversion hashes to infotext

---
 modules/textual_inversion/textual_inversion.py | 9 ++++++++-
 1 file changed, 8 insertions(+), 1 deletion(-)

(limited to 'modules/textual_inversion/textual_inversion.py')

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)
-- 
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