Merge pull request #4098 from jn-jairo/load-model

Unload sd_model before loading the other to solve the issue #3449

5 files changed, 34 insertions, 10 deletions

diff --git a/modules/lowvram.py b/modules/lowvram.py
index f327c3df..a4652cb1 100644
--- a/modules/lowvram.py
+++ b/modules/lowvram.py
@@ -38,13 +38,18 @@ def setup_for_low_vram(sd_model, use_medvram):
     # see below for register_forward_pre_hook;

     # first_stage_model does not use forward(), it uses encode/decode, so register_forward_pre_hook is

     # useless here, and we just replace those methods

-    def first_stage_model_encode_wrap(self, encoder, x):

-        send_me_to_gpu(self, None)

-        return encoder(x)

 

-    def first_stage_model_decode_wrap(self, decoder, z):

-        send_me_to_gpu(self, None)

-        return decoder(z)

+    first_stage_model = sd_model.first_stage_model

+    first_stage_model_encode = sd_model.first_stage_model.encode

+    first_stage_model_decode = sd_model.first_stage_model.decode

+

+    def first_stage_model_encode_wrap(x):

+        send_me_to_gpu(first_stage_model, None)

+        return first_stage_model_encode(x)

+

+    def first_stage_model_decode_wrap(z):

+        send_me_to_gpu(first_stage_model, None)

+        return first_stage_model_decode(z)

 

     # remove three big modules, cond, first_stage, and unet from the model and then

     # send the model to GPU. Then put modules back. the modules will be in CPU.

@@ -56,8 +61,8 @@ def setup_for_low_vram(sd_model, use_medvram):
     # register hooks for those the first two models

     sd_model.cond_stage_model.transformer.register_forward_pre_hook(send_me_to_gpu)

     sd_model.first_stage_model.register_forward_pre_hook(send_me_to_gpu)

-    sd_model.first_stage_model.encode = lambda x, en=sd_model.first_stage_model.encode: first_stage_model_encode_wrap(sd_model.first_stage_model, en, x)

-    sd_model.first_stage_model.decode = lambda z, de=sd_model.first_stage_model.decode: first_stage_model_decode_wrap(sd_model.first_stage_model, de, z)

+    sd_model.first_stage_model.encode = first_stage_model_encode_wrap

+    sd_model.first_stage_model.decode = first_stage_model_decode_wrap

     parents[sd_model.cond_stage_model.transformer] = sd_model.cond_stage_model

 

     if use_medvram:

diff --git a/modules/processing.py b/modules/processing.py
index b1df4918..57d3a523 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -597,6 +597,9 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     if p.scripts is not None:

         p.scripts.postprocess(p, res)

 

+    p.sd_model = None

+    p.sampler = None

+

     return res

 

 

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index 0f10828e..bc49d235 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -94,6 +94,10 @@ class StableDiffusionModelHijack:
         if type(model_embeddings.token_embedding) == EmbeddingsWithFixes:

             model_embeddings.token_embedding = model_embeddings.token_embedding.wrapped

 

+        self.layers = None

+        self.circular_enabled = False

+        self.clip = None

+

     def apply_circular(self, enable):

         if self.circular_enabled == enable:

             return

diff --git a/modules/sd_models.py b/modules/sd_models.py
index f86dc3ed..90007da3 100644
--- a/modules/sd_models.py
+++ b/modules/sd_models.py
@@ -1,6 +1,7 @@
 import collections

 import os.path

 import sys

+import gc

 from collections import namedtuple

 import torch

 import re

@@ -220,6 +221,12 @@ def load_model(checkpoint_info=None):
     if checkpoint_info.config != shared.cmd_opts.config:

         print(f"Loading config from: {checkpoint_info.config}")

 

+    if shared.sd_model:

+        sd_hijack.model_hijack.undo_hijack(shared.sd_model)

+        shared.sd_model = None

+        gc.collect()

+        devices.torch_gc()

+

     sd_config = OmegaConf.load(checkpoint_info.config)

     

     if should_hijack_inpainting(checkpoint_info):

@@ -233,6 +240,7 @@ def load_model(checkpoint_info=None):
         checkpoint_info = checkpoint_info._replace(config=checkpoint_info.config.replace(".yaml", "-inpainting.yaml"))

 

     do_inpainting_hijack()

+

     sd_model = instantiate_from_config(sd_config.model)

     load_model_weights(sd_model, checkpoint_info)

 

@@ -252,14 +260,18 @@ def load_model(checkpoint_info=None):
     return sd_model

 

 

-def reload_model_weights(sd_model, info=None):

+def reload_model_weights(sd_model=None, info=None):

     from modules import lowvram, devices, sd_hijack

     checkpoint_info = info or select_checkpoint()

 

+    if not sd_model:

+        sd_model = shared.sd_model

+

     if sd_model.sd_model_checkpoint == checkpoint_info.filename:

         return

 

     if sd_model.sd_checkpoint_info.config != checkpoint_info.config or should_hijack_inpainting(checkpoint_info) != should_hijack_inpainting(sd_model.sd_checkpoint_info):

+        del sd_model

         checkpoints_loaded.clear()

         load_model(checkpoint_info)

         return shared.sd_model

diff --git a/webui.py b/webui.py
index 8d8479f1..84e5c1fd 100644
--- a/webui.py
+++ b/webui.py
@@ -78,7 +78,7 @@ def initialize():
     modules.scripts.load_scripts()

 

     modules.sd_models.load_model()

-    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))

+    shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights()))

     shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))

     shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)