Repository: stable-diffusion-webui
Issue: error LDSR upscale x4 at first DDIM step
Labels: bug-report

**Describe the bug**
rror at first DDIM step of LDSRupscale (x4)

**To Reproduce**
try to x4 upscale using LDSR

**Expected behavior**
image upscaled x4

**Screenshots**
If applicable, add screenshots to help explain your problem.

**Desktop (please complete the following information):**
 - OS: Windows
 - Browser chrome
 - Commit revision 6be32b31d181e42c639dad3451229aa7b9cfd1cf

**Additional context**
Loading model from C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\models\LDSR\model.ckpt
LatentDiffusion: Running in eps-prediction mode
DiffusionWrapper has 113.62 M params.
Keeping EMAs of 308.
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 3, 64, 64) = 12288 dimensions.
making attention of type 'vanilla' with 512 in_channels
Down sample rate is 1 from 4 / 4 (Not downsampling)
reducing Kernel
Plotting: Switched to EMA weights
Sampling with eta = 1.0; steps: 100
Data shape for DDIM sampling is (1, 3, 70, 70), eta 1.0
Running DDIM Sampling with 100 timesteps
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**Error completing request**
Arguments: (0, <PIL.Image.Image image mode=RGB size=70x70 at 0x1B052E32BF0>, None, 0, 1, 0, 4, 2, 0, 1) {}
Traceback (most recent call last):
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ui.py", line 182, in f
    res = list(func(*args, **kwargs))
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\webui.py", line 69, in f
    res = func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\extras.py", line 85, in run_extras
    res = upscale(image, extras_upscaler_1, upscaling_resize)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\extras.py", line 79, in upscale
    c = upscaler.scaler.upscale(image, resize, upscaler.data_path)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\upscaler.py", line 62, in upscale
    img = self.do_upscale(img, selected_model)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ldsr_model.py", line 54, in do_upscale
    return ldsr.super_resolution(img, ddim_steps, self.scale)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ldsr_model_arch.py", line 113, in super_resolution
    logs = self.run(model["model"], im_og, diffusion_steps, eta)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ldsr_model_arch.py", line 76, in run
    logs = make_convolutional_sample(example, model,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ldsr_model_arch.py", line 200, in make_convolutional_sample
    sample, intermediates = convsample_ddim(model, c, steps=custom_steps, shape=z.shape,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\modules\ldsr_model_arch.py", line 156, in convsample_ddim
    samples, intermediates = ddim.sample(steps, batch_size=bs, shape=shape, conditioning=cond, callback=callback,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\repositories\stable-diffusion\ldm\models\diffusion\ddim.py", line 96, in sample
    samples, intermediates = self.ddim_sampling(conditioning, size,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\repositories\stable-diffusion\ldm\models\diffusion\ddim.py", line 149, in ddim_sampling
    outs = self.p_sample_ddim(img, cond, ts, index=index, use_original_steps=ddim_use_original_steps,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\repositories\stable-diffusion\ldm\models\diffusion\ddim.py", line 172, in p_sample_ddim
    e_t = self.model.apply_model(x, t, c)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\repositories\stable-diffusion\ldm\models\diffusion\ddpm.py", line 910, in apply_model
    fold, unfold, normalization, weighting = self.get_fold_unfold(x_noisy, ks, stride)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\repositories\stable-diffusion\ldm\models\diffusion\ddpm.py", line 619, in get_fold_unfold
    normalization = fold(weighting).view(1, 1, h, w)  # normalizes the overlap
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\fold.py", line 144, in forward
    return F.fold(input, self.output_size, self.kernel_size, self.dilation,
  File "C:\AI\SD\AUTOMATIC1111\stable-diffusion-webui\venv\lib\site-packages\torch\nn\functional.py", line 4696, in fold
    return torch._C._nn.col2im(
RuntimeError: Expected 2D or 3D (batch mode) tensor for input with possibly 0 batch size and non-zero dimensions for input, but got: [1, 16384, 0]

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and... freeze