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lkwq007 / stablediffusion-infinity

Outpainting with Stable Diffusion on an infinite canvas
Apache License 2.0
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Error: Cannot copy out of meta tensor; no data! #156

Open abartholet opened 1 year ago

abartholet commented 1 year ago

I am able to run stable diffusion using the web gui so I know there is nothing generally wrong with my setup. I followed the Linux install instructions for stablediffusion-infinity (running Debian 11) and everything went smoothly. I am able to start the application using my local sd-1.5 model. I am able to upload an image. I have Init Mode set to 'patchmode' and Photometric Correction Mode set to 'mask_mode' (just following along with the video). But if my select box overlaps with the uploaded image I get the error 'Cannot copy out of meta tensor; no data!' If I select a blank spot on the canvas it will happy generate a random image based on my prompt.
Am I missing a dependency or a configuration step somewhere?

lkwq007 commented 1 year ago

I cannot reproduce this error. Could you please check the detailed error messages from the terminal?

abartholet commented 1 year ago 
Traceback (most recent call last):
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/gradio/routes.py", line 292, in run_predict
    output = await app.blocks.process_api(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/gradio/blocks.py", line 1007, in process_api
    result = await self.call_function(fn_index, inputs, iterator, request)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/gradio/blocks.py", line 848, in call_function
    prediction = await anyio.to_thread.run_sync(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/anyio/to_thread.py", line 31, in run_sync
    return await get_asynclib().run_sync_in_worker_thread(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
    return await future
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 867, in run
    result = context.run(func, *args)
  File "/home/abartholet/Projects/stablediffusion-infinity/app.py", line 809, in run_outpaint
    images = cur_model.run(
  File "/home/abartholet/Projects/stablediffusion-infinity/app.py", line 700, in run
    images = inpaint_func(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py", line 586, in __call__
    latents, init_latents_orig, noise = self.prepare_latents(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py", line 464, in prepare_latents
    init_latent_dist = self.vae.encode(init_image).latent_dist
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/diffusers/models/vae.py", line 570, in encode
    h = self.encoder(x)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/diffusers/models/vae.py", line 130, in forward
    sample = self.conv_in(sample)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/hooks.py", line 151, in new_forward
    args, kwargs = module._hf_hook.pre_forward(module, *args, **kwargs)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/hooks.py", line 266, in pre_forward
    return send_to_device(args, self.execution_device), send_to_device(kwargs, self.execution_device)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 130, in send_to_device
    return recursively_apply(_send_to_device, tensor, device, non_blocking, test_type=_has_to_method)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 79, in recursively_apply
    return honor_type(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 50, in honor_type
    return type(obj)(generator)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 82, in <genexpr>
    recursively_apply(
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 98, in recursively_apply
    return func(data, *args, **kwargs)
  File "/home/abartholet/miniconda3/envs/sd-inf/lib/python3.10/site-packages/accelerate/utils/operations.py", line 123, in _send_to_device
    return t.to(device, non_blocking=non_blocking)
NotImplementedError: Cannot copy out of meta tensor; no data!
lkwq007 commented 1 year ago

Try adding these two lines at Line 10 of app.py (after import diffusers), perhaps it will help

import contextlib
autocast = contextlib.nullcontext

If not, I think it might be an upstream/dependency issue

abartholet commented 1 year ago

Unfortunately I now get a "Connection errored out" message in the gui while it's doing the setup and a rather unhelpful "Killed" message on the command line. There is also a lengthy message about weights of the model checkpoint, which I was also getting previously, I'm guessing that it doesn't have any bearing on this issue though.

Using local_model: ../sd_models/v1-5-pruned-emaonly.ckpt
Converting & Loading ../sd_models/v1-5-pruned-emaonly.ckpt
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPTextModel: ['vision_model.encoder.layers.14.mlp.fc1.weight', 'vision_model.encoder.layers.9.mlp.fc2.bias', 'vision_model.encoder.layers.23.layer_norm1.weight', 'vision_model.encoder.layers.7.self_attn.v_proj.weight', 'vision_model.encoder.layers.6.layer_norm2.bias', 'vision_model.encoder.layers.22.self_attn.q_proj.bias', 'vision_model.encoder.layers.20.layer_norm1.bias', 'vision_model.encoder.layers.15.self_attn.v_proj.bias', 'vision_model.encoder.layers.6.mlp.fc1.bias', 'vision_model.encoder.layers.13.self_attn.out_proj.weight', 'vision_model.encoder.layers.4.mlp.fc1.weight', 'vision_model.encoder.layers.19.self_attn.v_proj.bias', 'vision_model.encoder.layers.15.self_attn.q_proj.bias', 'vision_model.encoder.layers.10.mlp.fc2.weight', 'vision_model.encoder.layers.20.self_attn.q_proj.weight', 'vision_model.encoder.layers.2.mlp.fc2.weight', 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- This IS expected if you are initializing CLIPTextModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPTextModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Killed

Should I downgrade the version of some of the dependencies?

viperyl commented 1 year ago

I think you need to check the weights file, iterate all of keys and check value device to find does device("meta") exists. Pytorch introduce "meta" device in 1.9.0 version, it is a 'fake' data