部署VQGAN+CLIP代码至Hugging Face Spaces后出现KeyError: 'allocated_bytes.all.current'问题求助

Hey there! Let's break down this error and get your VQGAN+CLIP Space up and running smoothly.

What Does This Error Mean? #

This KeyError pops up because your code is trying to access a specific CUDA memory statistic field (allocated_bytes.all.current) that doesn't exist in your Hugging Face Spaces environment. Most often, this happens for one of two reasons:

• Your Space is running on CPU only, but the code assumes CUDA (GPU) is available and tries to read GPU memory stats.
• There's a mismatch between the PyTorch version in your Space and the version the original VQGAN+CLIP code was written for—older or newer PyTorch versions might rename or remove this memory tracking field.

Fixes to Try #

1. Check Your Space's Hardware Configuration #

First, head to your Space's Settings tab and make sure you've enabled GPU acceleration (if you have access to it). If you're stuck on CPU mode, the code's CUDA memory monitoring logic is irrelevant and needs to be disabled.

2. Guard Against CUDA Unavailability #

Find the section in your code where it calls torch.cuda.memory_stats() and tries to fetch allocated_bytes.all.current. It might look something like this:

memory_stats = torch.cuda.memory_stats()
current_usage = memory_stats['allocated_bytes.all.current']

Wrap this logic in a check for CUDA availability, and use get() to avoid KeyErrors even if the field is missing:

if torch.cuda.is_available():
    memory_stats = torch.cuda.memory_stats()
    # Use get() to return a default value if the key doesn't exist
    current_usage = memory_stats.get('allocated_bytes.all.current', 0)
else:
    # Skip memory tracking entirely on CPU
    current_usage = 0

If the memory tracking code isn't critical to the model's function, you can even comment out the entire block when running on CPU.

3. Align Your PyTorch Version #

The allocated_bytes.all.current field is specific to certain PyTorch versions. Try adjusting your requirements.txt to pin a version that's known to work with VQGAN+CLIP. For example:

torch==1.13.1
torchvision==0.14.1

Older versions (pre-1.10) might not have this field, while newer versions might have renamed it—testing a mid-range stable version often resolves this.

4. Reduce Memory Pressure (If Using GPU) #

If you are using a GPU, sometimes memory constraints can cause unexpected errors in memory tracking. Try using a smaller VQGAN checkpoint (like vqgan_imagenet_f16_16384 instead of larger variants) or reduce the batch size/image resolution in your code to lighten the GPU load.

内容的提问来源于stack exchange，提问作者Bernardo Olisan