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This refers to an unexpected issue when using PyTorch's torch.compile()
function within Hugging Face Spaces and Endpoint API environments. Torch.compile(), designed to optimize PyTorch models for better performance, exhibits strange behavior in these specific setups, potentially leading to errors or suboptimal performance. If you're experiencing this issue, this guide will help you navigate its features, usage, and troubleshooting.
torch.compile()
misuse.import torch
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("your-model-name")
tokenizer = AutoTokenizer.from_pretrained("your-model-name")
torch.compile()
.
model = torch.compile(model)
# Example for Spaces
from huggingface_hub import Repository
repo = Repository(local_dir="./my-app")
repo.push_to_hub(commit_message="Initialize emoji generator")
What is torch.compile()
used for?
torch.compile()
optimizes PyTorch models for inference, improving speed and reducing latency.
Why is torch.compile()
causing issues in Hugging Face?
This could stem from version incompatibilities, incorrect model tracing, or environmental conflicts.
How can I fix the issue?
Temporarily avoid torch.compile()
or use torch.jit.script()
instead. Ensure your PyTorch version is updated.