Unable to load SD 2.0

[darth2602]

Hello, I'm reluctant to use SD 2.0 but I would like to test it a bit (before going back to 1.5 ^_^) but it doesn't work .... (on google colab)

I choose the 2.0 model (redownload)

and at the Start stable-diffusion step (choice V2-512) I have this message :
Checkpoint model.ckpt [a2a802b2] not found; loading fallback classic disney style - v1.ckpt [be7ddafc]
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 865.91 M params.
Loading weights [be7ddafc] from /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/classic disney style - v1.ckpt
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 191, in
webui()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 131, in webui
initialize()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/webui.py", line 61, in initialize
modules.sd_models.load_model()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 261, in load_model
load_model_weights(sd_model, checkpoint_info)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models.py", line 192, in load_model_weights
model.load_state_dict(sd, strict=False)
File "/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py", line 1605, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for LatentDiffusion:
size mismatch for model.diffusion_model.input_blocks.1.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.1.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.1.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.2.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.2.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.input_blocks.2.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.input_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.input_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.input_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.input_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.middle_block.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.middle_block.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.3.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.3.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.3.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.4.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.4.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.4.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.5.1.proj_in.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.5.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([1280, 768]) from checkpoint, the shape in current model is torch.Size([1280, 1024]).
size mismatch for model.diffusion_model.output_blocks.5.1.proj_out.weight: copying a param with shape torch.Size([1280, 1280, 1, 1]) from checkpoint, the shape in current model is torch.Size([1280, 1280]).
size mismatch for model.diffusion_model.output_blocks.6.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.6.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.6.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.7.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.7.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.7.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.8.1.proj_in.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.8.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([640, 768]) from checkpoint, the shape in current model is torch.Size([640, 1024]).
size mismatch for model.diffusion_model.output_blocks.8.1.proj_out.weight: copying a param with shape torch.Size([640, 640, 1, 1]) from checkpoint, the shape in current model is torch.Size([640, 640]).
size mismatch for model.diffusion_model.output_blocks.9.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.9.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.9.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.10.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.10.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.10.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.11.1.proj_in.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).
size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_k.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.11.1.transformer_blocks.0.attn2.to_v.weight: copying a param with shape torch.Size([320, 768]) from checkpoint, the shape in current model is torch.Size([320, 1024]).
size mismatch for model.diffusion_model.output_blocks.11.1.proj_out.weight: copying a param with shape torch.Size([320, 320, 1, 1]) from checkpoint, the shape in current model is torch.Size([320, 320]).

[TheLastBen]

remove the folder sd and do a clean run with the latest colab

[shyt47]

I was able to train a 2.0 model but get this type of error in the Automatic webui when trying to load the 2.0 model.

[brian-tam]

I am encountering the same problem. but I was training to train a trained 2.0 model. This error is shown after loading a previous session.

[darth2602]

Error loading script: swinir_model.py
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/scripts.py", line 184, in load_scripts
module = script_loading.load_module(scriptfile.path)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/script_loading.py", line 13, in load_module
exec(compiled, module.dict)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions-builtin/SwinIR/scripts/swinir_model.py", line 102, in
tile=opts.SWIN_tile,
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/shared.py", line 458, in getattr
return super(Options, self).getattribute(item)
AttributeError: 'Options' object has no attribute 'SWIN_tile'

LatentDiffusion: Running in v-prediction mode
DiffusionWrapper has 865.91 M params.
^C

[darth2602]

I dropped version 2.0 which never worked on my google colab, the problem is that now since 2-3 days I get error messages on a zero install (after overwriting the SD folder) - but SD works

Error loading script: swinir_model.py
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/scripts.py", line 184, in load_scripts
module = script_loading.load_module(scriptfile.path)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/script_loading.py", line 13, in load_module
exec(compiled, module.dict)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions-builtin/SwinIR/scripts/swinir_model.py", line 102, in
tile=opts.SWIN_tile,
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/shared.py", line 458, in getattr
return super(Options, self).getattribute(item)
AttributeError: 'Options' object has no attribute 'SWIN_tile'

LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 859.52 M params.
Downloading100% 961k/961k [00:00<00:00, 1.87MB/s]
Downloading100% 525k/525k [00:00<00:00, 1.22MB/s]
Downloading100% 389/389 [00:00<00:00, 326kB/s]
Downloading100% 905/905 [00:00<00:00, 718kB/s]
Downloading100% 4.52k/4.52k [00:00<00:00, 3.01MB/s]
Downloading100% 1.71G/1.71G [00:38<00:00, 43.9MB/s]
Loading weights [a2a802b2] from /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/model.ckpt
Applying xformers cross attention optimization.
Model loaded.
Loaded a total of 0 textual inversion embeddings.
Embeddings:
Running on local URL: [https://xxxx-xxxxx-xxxx-xxx)
Connected

[TheLastBen]

update the repo to avoid those errors

[darth2602]

my version is from this morning (10am)

[TheLastBen]

A1111 pushed a commit after 10am

[darth2602]

ho...ok.... it's Done ;-)

[darth2602]

at extension installation (colab):

Error running install.py for extension /content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/stable-diffusion-webui-depthmap-script.
Command: "/usr/bin/python3" "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/stable-diffusion-webui-depthmap-script/install.py"
Error code: 1
stdout:
stderr: Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/stable-diffusion-webui-depthmap-script/install.py", line 1, in
import launch
ModuleNotFoundError: No module named 'launch'

Error running install.py for extension /content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/multi-subject-render.
Command: "/usr/bin/python3" "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/multi-subject-render/install.py"
Error code: 1
stdout:
stderr: Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/multi-subject-render/install.py", line 1, in
import launch
ModuleNotFoundError: No module named 'launch'

after restarting

Error loading script: simple_depthmap.py
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/scripts.py", line 184, in load_scripts
module = script_loading.load_module(scriptfile.path)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/script_loading.py", line 13, in load_module
exec(compiled, module.dict)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/multi-subject-render/scripts/simple_depthmap.py", line 11, in
from repositories.midas.midas.dpt_depth import DPTDepthModel
ModuleNotFoundError: No module named 'repositories.midas'

Error loading script: depthmap.py
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/scripts.py", line 184, in load_scripts
module = script_loading.load_module(scriptfile.path)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/script_loading.py", line 13, in load_module
exec(compiled, module.dict)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/extensions/stable-diffusion-webui-depthmap-script/scripts/depthmap.py", line 27, in
from lib.multi_depth_model_woauxi import RelDepthModel
ModuleNotFoundError: No module named 'lib'

[TheLastBen]

I'll check it out

[darth2602]

well.... (on COLAB) I deleted the SD folder and downloaded the last A1111, it starts if I select the 768 model, if I add my old models, none of them work (error), if I quit having another model than model.ckpt selected, it doesn't start anymore, I have to delete the json config, if I start having selected the 1.5 model everything works fine, but I have from time to time freeze at the time of rendering

[TheLastBen]

You can't switch from V2 to V1 from the webui, you need to restart the last cell if you want to change, unless you put the yaml files in a correct way

[darth2602]

regularly I take the last version of A1111, with the version that I have just had nothing starts anymore:

Model Download/Load (SD version 1.5)

Converting to CKPT ...
Traceback (most recent call last):
File "/content/convertosd.py", line 228, in
torch.save(state_dict, checkpoint_path)
File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 422, in save
with _open_zipfile_writer(f) as opened_zipfile:
File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 309, in _open_zipfile_writer
return container(name_or_buffer)
File "/usr/local/lib/python3.8/dist-packages/torch/serialization.py", line 287, in init
super(_open_zipfile_writer_file, self).init(torch._C.PyTorchFileWriter(str(name)))
RuntimeError: Parent directory /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion does not exist.
Something went wrong, try again

I deleted the SD folder from google drive but it doesn't change anything

[darth2602]

When it works I have a crash afterwards (Start stable-diffusion)

---

NameError Traceback (most recent call last)
in
51 get_ipython().system("grep -o 'https[^ ]*' /content/srv.txt >srvr.txt")
52 time.sleep(2)
---> 53 srv= getoutput('cat /content/srvr.txt')
54
55 for line in fileinput.input('/usr/local/lib/python3.8/dist-packages/gradio/blocks.py', inplace=True):

NameError: name 'getoutput' is not defined

[TheLastBen]

getoutput is fixed, 89e55dc