HI, would like to ask about this issue for bxclib2 / flux_img2img

[deapi]

Sorry I have no idea how to contact or bug for help on https://replicate.com/bxclib2/flux_img2img
As I tried it but error with any input image, can you help to have a look?

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Traceback (most recent call last):
File "/usr/local/lib/python3.10/site-packages/einops/einops.py", line 523, in reduce
return _apply_recipe(
File "/usr/local/lib/python3.10/site-packages/einops/einops.py", line 234, in _apply_recipe
init_shapes, axes_reordering, reduced_axes, added_axes, final_shapes, n_axes_w_added = _reconstruct_from_shape(
File "/usr/local/lib/python3.10/site-packages/einops/einops.py", line 187, in _reconstruct_from_shape_uncached
raise EinopsError(f"Shape mismatch, can't divide axis of length {length} in chunks of {known_product}")
einops.EinopsError: Shape mismatch, can't divide axis of length 169 in chunks of 2
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.10/site-packages/cog/server/worker.py", line 352, in _predict
result = predict(**payload)
File "/src/predict.py", line 70, in predict
sample, sample_denoised = SamplerCustomAdvanced.sample(noise, guider, sampler, sigmas, latent_image)
File "/src/totoro_extras/nodes_custom_sampler.py", line 612, in sample
samples = guider.sample(noise.generate_noise(latent), latent_image, sampler, sigmas, denoise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=noise.seed)
File "/src/totoro/samplers.py", line 716, in sample
output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "/src/totoro/samplers.py", line 695, in inner_sample
samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "/src/totoro/samplers.py", line 600, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "/usr/local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "/src/totoro/k_diffusion/sampling.py", line 143, in sample_euler
denoised = model(x, sigma_hat * s_in, **extra_args)
File "/src/totoro/samplers.py", line 299, in __call__
out = self.inner_model(x, sigma, model_options=model_options, seed=seed)
File "/src/totoro/samplers.py", line 682, in __call__
return self.predict_noise(*args, **kwargs)
File "/src/totoro/samplers.py", line 685, in predict_noise
return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed)
File "/src/totoro/samplers.py", line 279, in sampling_function
out = calc_cond_batch(model, conds, x, timestep, model_options)
File "/src/totoro/samplers.py", line 228, in calc_cond_batch
output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
File "/src/totoro/model_base.py", line 121, in apply_model
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/src/totoro/ldm/flux/model.py", line 127, in forward
img = rearrange(x, "b c (h ph) (w pw) -> b (h w) (c ph pw)", ph=2, pw=2)
File "/usr/local/lib/python3.10/site-packages/einops/einops.py", line 591, in rearrange
return reduce(tensor, pattern, reduction="rearrange", **axes_lengths)
File "/usr/local/lib/python3.10/site-packages/einops/einops.py", line 533, in reduce
raise EinopsError(message + "\n {}".format(e))
einops.EinopsError:  Error while processing rearrange-reduction pattern "b c (h ph) (w pw) -> b (h w) (c ph pw)".
Input tensor shape: torch.Size([1, 16, 96, 169]). Additional info: {'ph': 2, 'pw': 2}.
Shape mismatch, can't divide axis of length 169 in chunks of 2