Using Imagine to generate 360 images is occuring error while running.

[alexd725]

Hello, guies.

Im using imagine to create 360 degree image.

This is my script to create.
imagine --tile-x "Generate a 360-degree panorama of an ancient ruins site, with moss-covered stones and hidden passages." --upscale

But its showing this error.

🖼  1/1 "Generate a 360-degree panorama of an ancient ruins site, with moss-covered stones and hidden passages."
    negative-prompt:DEFAULT-NEGATIVE-PROMPT
    size:512x512px-(1:1) seed:459389406 prompt-strength:7.5 steps:50 solver-type:ddim init-image-strength:0.2 arch:sd15 weights:sd15
Traceback (most recent call last):                                                                                                  
  File "/opt/conda/bin/imagine", line 7, in <module>
    imaginairy.cli.imagine.imagine_cmd()
  File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
    return self.main(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
    rv = self.invoke(ctx)
  File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
    return __callback(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/click/decorators.py", line 33, in new_func
    return f(get_current_context(), *args, **kwargs)
  File "/opt/conda/lib/python3.10/contextlib.py", line 79, in inner
    return func(*args, **kwds)
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/cli/imagine.py", line 189, in imagine_cmd
    return _imagine_cmd(
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/cli/shared.py", line 234, in _imagine_cmd
    filenames = imagine_image_files(
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/api/generate.py", line 89, in imagine_image_files
    for result in imagine(
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/api/generate.py", line 268, in imagine
    result = generate_single_image(
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/api/generate_refiners.py", line 352, in generate_single_image
    x = sd(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/vendored/refiners/foundationals/latent_diffusion/model.py", line 99, in forward
    unconditional_prediction, conditional_prediction = self.unet(latents).chunk(2)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1511, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1520, in _call_impl
    return forward_call(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/vendored/refiners/fluxion/layers/chain.py", line 279, in forward
    result = self._call_layer(layer, name, *intermediate_args)
  File "/opt/conda/lib/python3.10/site-packages/imaginairy/vendored/refiners/fluxion/layers/chain.py", line 273, in _call_layer
    raise ChainError(message) from None
imaginairy.vendored.refiners.fluxion.layers.chain.ChainError: 

AttributeError:
   File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 460, in forward
    return self._conv_forward(input, self.weight, self.bias)
'Conv2d' object has no attribute 'padding_modeX'
---------------
(CHAIN)
    ├── >>> Conv2d(in_channels=4, out_channels=320, kernel_size=(3, 3), padding=(1, 1), device=cuda:0, dtype=float16) | SD1UNet.DownBlocks.Chain_1.Conv2d
    └── (PASS) ResidualAccumulator(n=0)
        ├── (RES) Residual()
        │   └── UseContext(context=unet, key=residuals)
        └── SetContext(context=unet, key=residuals)
0: Tensor(shape=(2, 4, 64, 64), dtype=float16, device=cuda:0, min=-4.26, max=4.61, mean=0.00, std=1.00, norm=180.53, grad=False)
---------------
(CHAIN) DownBlocks(in_channels=4)
    ├── >>> (CHAIN) | SD1UNet.DownBlocks.Chain_1 #1
    │   ├── Conv2d(in_channels=4, out_channels=320, kernel_size=(3, 3), padding=(1, 1), device=cuda:0, dtype=float16)
    │   └── (PASS) ResidualAccumulator(n=0)
    │       ├── (RES) Residual() ...
    │       └── SetContext(context=unet, key=residuals)
    ├── (CHAIN) #2
    │   ├── (SUM) ResidualBlock(in_channels=320, out_channels=320)
    │   │   ├── (CHAIN) ...
    │   │   └── Identity()
    │   ├── (RES) CLIPLCrossAttention(channels=320)
0: Tensor(shape=(2, 4, 64, 64), dtype=float16, device=cuda:0, min=-4.26, max=4.61, mean=0.00, std=1.00, norm=180.53, grad=False)
---------------
(CHAIN) SD1UNet(in_channels=4)
    ├── (PASS) TimestepEncoder()
    │   ├── UseContext(context=diffusion, key=timestep)
    │   ├── (CHAIN) RangeEncoder(sinusoidal_embedding_dim=320, embedding_dim=1280)
    │   │   ├── Lambda(compute_sinusoidal_embedding(x: jaxtyping.Int[Tensor, '*batch 1']) -> jaxtyping.Float[Tensor, '*batch 1 embedding_dim'])
    │   │   ├── Converter(set_device=False)
    │   │   ├── Linear(in_features=320, out_features=1280, device=cuda:0, dtype=float16) #1
    │   │   ├── SiLU()
    │   │   └── Linear(in_features=1280, out_features=1280, device=cuda:0, dtype=float16) #2
    │   └── SetContext(context=range_adapter, key=timestep_embedding)
    ├── >>> (CHAIN) DownBlocks(in_channels=4) | SD1UNet.DownBlocks
0: Tensor(shape=(2, 4, 64, 64), dtype=float16, device=cuda:0, min=-4.26, max=4.61, mean=0.00, std=1.00, norm=180.53, grad=False)

How can i fix this error? Any help would be appreciate. Thanks in advance.