add textual inversion hashes to infotext

This commit is contained in:
AUTOMATIC1111
2023-07-15 08:41:22 +03:00
parent 127635409a
commit 2b1bae0d75
6 changed files with 33 additions and 8 deletions

View File

@@ -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)