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I'm using a few generated scripts on an EC2 instance of type g4dn.xlarge, with Tesla T4 GPU
When running the workflow from the ComfyUI interface, I see traced in logs: Device: cuda:0 Tesla T4 : cudaMallocAsync
while if I run the generated python script I see: Device: cuda:0 Tesla T4 : native
The script produces similar result, but it's a lot slower. I tryied to add --cuda-malloc to the command line, but nothing changes. Any clue?
btw: great extension!
The text was updated successfully, but these errors were encountered:
Found a solution: in the python script generated by this extension you need to add import cuda_malloc at the beginning (with some code to verify if it is supported) and move the import torch statement from the beginning to the first line after def main():
It would be useful to generate code already in this form
Found a solution: in the python script generated by this extension you need to add import cuda_malloc at the beginning (with some code to verify if it is supported) and move the import torch statement from the beginning to the first line after def main():
It would be useful to generate code already in this form
i add the code,but the cost time is same with not add
I'm using a few generated scripts on an EC2 instance of type g4dn.xlarge, with Tesla T4 GPU
When running the workflow from the ComfyUI interface, I see traced in logs:
Device: cuda:0 Tesla T4 : cudaMallocAsync
while if I run the generated python script I see:
Device: cuda:0 Tesla T4 : native
The script produces similar result, but it's a lot slower. I tryied to add
--cuda-malloc
to the command line, but nothing changes. Any clue?btw: great extension!
The text was updated successfully, but these errors were encountered: