Solving the “RuntimeError: CUDA Out of memory” error

The "RuntimeError: CUDA Out of memory" error occurs when your GPU runs out of memory while trying to execute a task. To solve this issue, you can try the following:

Reduce the batch size of your input data.
Use a smaller model architecture.
Use a GPU with more memory.
Close other applications that are using the GPU.
Use memory-saving techniques such as gradient accumulation or gradient checkpointing.
If you are using CUDA for parallel computing, try reducing the number of CUDA threads.

[nevalkaraca]

if gpus:
try:

gpus[0],

logical_gpus =
print(len(gpus), "Physical GPUs, ", len(logical_gpus), "Logical GPUs")

except RuntimeError as e:
print(e)

[mech-management]

Explicitly clear GPU memory using the appropriate functions provided by your deep learning framework. For example, in TensorFlow, you can use to release the memory occupied by the model and other TensorFlow objects.
python
Copy code
import tensorflow as tf

# Run this before and/or after your API code

[faejbr]

where do i put this 3 code lines if i am using bark webui? Can you please paste it here to make it easier? thank you.

[스티부잡]

Message : diffusionWrapper has 859.52 M params. loading stable diffusion model: OutOfMemoryError
setup program stop, How can I do that ?

[mubarak_]

A company is setting an assembly line as produce 292 mts per eight hour shaft. The f regarding work clements in terms of times and immediate predecessors are given

Work element

A

C

D

Time (sec)

40

Immediate Predecessors

79 30

23

20

13

A DEF

F G

H

120

133

130

Λ

G

H

CL

1. What is desired cycle time?

2 What is the theorical number of stations" 3. Use largest work element time cale to workout a solution on a proodonce diagram 4. What are the efficiency and balance delay of the solution obtained?

[aashas]

Stable diffusion tells me to use the max_split_size_mb but Im clueless as to where to put this command. The youtube led me to your video. Please comment if you have any tips

[younginnovatorscenterofint]

hey Mech, OutOfMemoryError: CUDA out of memory. Tried to allocate 90.00 MiB (GPU 0; 39.56 GiB total capacity; 37.91 GiB
already allocated; 54.56 MiB free; 37.94 GiB reserved in total by PyTorch) If reserved memory is >> allocated
memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and
PYTORCH_CUDA_ALLOC_CONF.how can i solve