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# Copyright (c) MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import annotations
import functools
import os
import warnings
__all__ = ["has_ampere_or_later", "detect_default_tf32"]
@functools.lru_cache(None)
def has_ampere_or_later() -> bool:
"""
Check if there is any Ampere and later GPU.
"""
import torch
from monai.utils.module import optional_import, version_geq
if not (torch.version.cuda and version_geq(f"{torch.version.cuda}", "11.0")):
return False
pynvml, has_pynvml = optional_import("pynvml")
if not has_pynvml: # assuming that the user has Ampere and later GPU
return True
try:
pynvml.nvmlInit()
for i in range(pynvml.nvmlDeviceGetCount()):
handle = pynvml.nvmlDeviceGetHandleByIndex(i)
major, _ = pynvml.nvmlDeviceGetCudaComputeCapability(handle)
if major >= 8:
return True
except BaseException:
pass
finally:
pynvml.nvmlShutdown()
return False
@functools.lru_cache(None)
def detect_default_tf32() -> bool:
"""
Detect if there is anything that may enable TF32 mode by default.
If any, show a warning message.
"""
may_enable_tf32 = False
try:
if not has_ampere_or_later():
return False
from monai.utils.module import pytorch_after
if pytorch_after(1, 7, 0) and not pytorch_after(1, 12, 0):
warnings.warn(
"torch.backends.cuda.matmul.allow_tf32 = True by default.\n"
" This value defaults to True when PyTorch version in [1.7, 1.11] and may affect precision.\n"
" See https://docs.monai.io/en/latest/precision_accelerating.html#precision-and-accelerating"
)
may_enable_tf32 = True
override_tf32_env_vars = {"NVIDIA_TF32_OVERRIDE": "1"} # TORCH_ALLOW_TF32_CUBLAS_OVERRIDE not checked #6907
for name, override_val in override_tf32_env_vars.items():
if os.environ.get(name) == override_val:
warnings.warn(
f"Environment variable `{name} = {override_val}` is set.\n"
f" This environment variable may enable TF32 mode accidentally and affect precision.\n"
f" See https://docs.monai.io/en/latest/precision_accelerating.html#precision-and-accelerating"
)
may_enable_tf32 = True
return may_enable_tf32
except BaseException:
from monai.utils.misc import MONAIEnvVars
if MONAIEnvVars.debug():
raise
return False
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