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Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
--- using zero snr---
/home/harshad/Downloads/CRM/imagedream/ldm/interface.py:117: RuntimeWarning: divide by zero encountered in divide
"sqrt_recip_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod))
/home/harshad/Downloads/CRM/imagedream/ldm/interface.py:120: RuntimeWarning: divide by zero encountered in divide
"sqrt_recipm1_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod - 1))
Killed
After some time, while running the code, I encountered a 'divide by zero' error. It seems to occur during a division operation, which is likely causing the program to terminate unexpectedly. I suspect there might be an issue with the calculations or data processing logic in the code. The error message indicates that a division by zero was encountered, which is mathematically undefined. Could you please provide guidance on how to resolve this issue?
The text was updated successfully, but these errors were encountered:
We use Zero SNR trick, which means that at maximum timestep the noise to signal ratio will be 1.0/0.0. However, in general the maximum step will not be used. How do you set the sampling timesteps of DDIM? Do you set as the default 50 steps?
We use Zero SNR trick, which means that at maximum timestep the noise to signal ratio will be 1.0/0.0. However, in general the maximum step will not be used. How do you set the sampling timesteps of DDIM? Do you set as the default 50 steps?
I did not made any changes to the parameters, so I believe the default value for the sampling timesteps is being used.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
--- using zero snr---
/home/harshad/Downloads/CRM/imagedream/ldm/interface.py:117: RuntimeWarning: divide by zero encountered in divide
"sqrt_recip_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod))
/home/harshad/Downloads/CRM/imagedream/ldm/interface.py:120: RuntimeWarning: divide by zero encountered in divide
"sqrt_recipm1_alphas_cumprod", to_torch(np.sqrt(1.0 / alphas_cumprod - 1))
Killed
After some time, while running the code, I encountered a 'divide by zero' error. It seems to occur during a division operation, which is likely causing the program to terminate unexpectedly. I suspect there might be an issue with the calculations or data processing logic in the code. The error message indicates that a division by zero was encountered, which is mathematically undefined. Could you please provide guidance on how to resolve this issue?
The text was updated successfully, but these errors were encountered: