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chore: import upstream snapshot with attribution
2026-07-13 13:22:06 +08:00

53 lines
2.4 KiB
Python

import logging
import os
import sys
def configure_torch_cuda_allocator(pytorch_cuda_alloc_conf: str, logger: logging.Logger):
"""Configure the PyTorch CUDA memory allocator. See
https://pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf for supported
configurations.
"""
if "torch" in sys.modules:
raise RuntimeError("configure_torch_cuda_allocator() must be called before importing torch.")
# Log a warning if the PYTORCH_CUDA_ALLOC_CONF environment variable is already set.
prev_cuda_alloc_conf = os.environ.get("PYTORCH_CUDA_ALLOC_CONF", None)
if prev_cuda_alloc_conf is not None:
if prev_cuda_alloc_conf == pytorch_cuda_alloc_conf:
logger.info(
f"PYTORCH_CUDA_ALLOC_CONF is already set to '{pytorch_cuda_alloc_conf}'. Skipping configuration."
)
return
else:
logger.warning(
f"Attempted to configure the PyTorch CUDA memory allocator with '{pytorch_cuda_alloc_conf}', but PYTORCH_CUDA_ALLOC_CONF is already set to "
f"'{prev_cuda_alloc_conf}'. Skipping configuration."
)
return
# Configure the PyTorch CUDA memory allocator.
# NOTE: It is important that this happens before torch is imported.
os.environ["PYTORCH_CUDA_ALLOC_CONF"] = pytorch_cuda_alloc_conf
import torch
# Relevant docs: https://pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf
if not torch.cuda.is_available():
raise RuntimeError(
"Attempted to configure the PyTorch CUDA memory allocator, but no CUDA devices are available."
)
# Verify that the torch allocator was properly configured.
allocator_backend = torch.cuda.get_allocator_backend()
expected_backend = "cudaMallocAsync" if "cudaMallocAsync" in pytorch_cuda_alloc_conf else "native"
if allocator_backend != expected_backend:
raise RuntimeError(
f"Failed to configure the PyTorch CUDA memory allocator. Expected backend: '{expected_backend}', but got "
f"'{allocator_backend}'. Verify that 1) the pytorch_cuda_alloc_conf is set correctly, and 2) that torch is "
"not imported before calling configure_torch_cuda_allocator()."
)
logger.info(f"PyTorch CUDA memory allocator: {torch.cuda.get_allocator_backend()}")