What condition is used in the first and second round sampling?
DDPM Sampling: 100%|██████████| 1000/1000 [00:52<00:00, 18.87it/s]
DDPM Sampling: 0%| | 0/1000 [00:00<?, ?it/s]
Error executing job with overrides: []
Traceback (most recent call last):
File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 412, in reduce
return _apply_recipe(recipe, tensor, reduction_type=reduction)
File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 235, in _apply_recipe
_reconstruct_from_shape(recipe, backend.shape(tensor))
File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 165, in _reconstruct_from_shape_uncached
raise EinopsError('Expected {} dimensions, got {}'.format(len(self.input_composite_axes), len(shape)))
einops.EinopsError: Expected 2 dimensions, got 1
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/data/IDiff-Face-main/main.py", line 335, in train
trainer.run(cfg)
File "/opt/conda/lib/python3.7/site-packages/lightning_fabric/fabric.py", line 630, in _run_impl
return run_method(*args, kwargs)
File "/opt/conda/lib/python3.7/site-packages/lightning_fabric/fabric.py", line 638, in _run_with_setup
return runfunction(*args, **kwargs)
File "/data/IDiff-Face-main/main.py", line 277, in run
os.getcwd(), 'samples', f"sample{global_step:06d}.png"))
File "/opt/conda/lib/python3.7/site-packages/lightning_utilities/core/rank_zero.py", line 32, in wrapped_fn
return fn(*args, kwargs)
File "/data/IDiff-Face-main/main.py", line 94, in create_and_save_sample_grid
samples_syn_cond = model.sample(N_PER_BLOCK, size, context=syn_context[:N_PER_BLOCK]).cpu()
File "/data/IDiff-Face-main/diffusion/ddpm.py", line 61, in sample
eps = self.eps_model(x_t, t, context, dropout_mask)
File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, kwargs)
File "/data/IDiff-Face-main/models/diffusion/unet.py", line 456, in forward
x = m(x, t, c)
File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, *kwargs)
File "/data/IDiff-Face-main/models/diffusion/unet.py", line 199, in forward
x = self.attn(x, c)
File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(input, kwargs)
File "/data/IDiff-Face-main/models/diffusion/nn.py", line 71, in forward
c = rearrange(c, "b (n d) -> b n d", n=self.context_dim)
File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 483, in rearrange
return reduce(cast(Tensor, tensor), pattern, reduction='rearrange', **axes_lengths)
File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 420, in reduce
raise EinopsError(message + '\n {}'.format(e))
einops.EinopsError: Error while processing rearrange-reduction pattern "b (n d) -> b n d".
Input tensor shape: torch.Size([8192]). Additional info: {'n': 256}.
Expected 2 dimensions, got 1
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
What condition is used in the first and second round sampling?
DDPM Sampling: 100%|██████████| 1000/1000 [00:52<00:00, 18.87it/s] DDPM Sampling: 0%| | 0/1000 [00:00<?, ?it/s] Error executing job with overrides: [] Traceback (most recent call last): File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 412, in reduce return _apply_recipe(recipe, tensor, reduction_type=reduction) File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 235, in _apply_recipe _reconstruct_from_shape(recipe, backend.shape(tensor)) File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 165, in _reconstruct_from_shape_uncached raise EinopsError('Expected {} dimensions, got {}'.format(len(self.input_composite_axes), len(shape))) einops.EinopsError: Expected 2 dimensions, got 1
During handling of the above exception, another exception occurred:
Traceback (most recent call last): File "/data/IDiff-Face-main/main.py", line 335, in train trainer.run(cfg) File "/opt/conda/lib/python3.7/site-packages/lightning_fabric/fabric.py", line 630, in _run_impl return run_method(*args, kwargs) File "/opt/conda/lib/python3.7/site-packages/lightning_fabric/fabric.py", line 638, in _run_with_setup return runfunction(*args, **kwargs) File "/data/IDiff-Face-main/main.py", line 277, in run os.getcwd(), 'samples', f"sample{global_step:06d}.png")) File "/opt/conda/lib/python3.7/site-packages/lightning_utilities/core/rank_zero.py", line 32, in wrapped_fn return fn(*args, kwargs) File "/data/IDiff-Face-main/main.py", line 94, in create_and_save_sample_grid samples_syn_cond = model.sample(N_PER_BLOCK, size, context=syn_context[:N_PER_BLOCK]).cpu() File "/data/IDiff-Face-main/diffusion/ddpm.py", line 61, in sample eps = self.eps_model(x_t, t, context, dropout_mask) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, kwargs) File "/data/IDiff-Face-main/models/diffusion/unet.py", line 456, in forward x = m(x, t, c) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, *kwargs) File "/data/IDiff-Face-main/models/diffusion/unet.py", line 199, in forward x = self.attn(x, c) File "/opt/conda/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(input, kwargs) File "/data/IDiff-Face-main/models/diffusion/nn.py", line 71, in forward c = rearrange(c, "b (n d) -> b n d", n=self.context_dim) File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 483, in rearrange return reduce(cast(Tensor, tensor), pattern, reduction='rearrange', **axes_lengths) File "/opt/conda/lib/python3.7/site-packages/einops/einops.py", line 420, in reduce raise EinopsError(message + '\n {}'.format(e)) einops.EinopsError: Error while processing rearrange-reduction pattern "b (n d) -> b n d". Input tensor shape: torch.Size([8192]). Additional info: {'n': 256}. Expected 2 dimensions, got 1
Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.