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# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# 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.
import os
import sys
from typing import Dict
import torch
def str_to_bool(value) -> int:
"""
Converts a string representation of truth to `True` (1) or `False` (0).
True values are `y`, `yes`, `t`, `true`, `on`, and `1`; False value are `n`, `no`, `f`, `false`, `off`, and `0`;
"""
value = value.lower()
if value in ("y", "yes", "t", "true", "on", "1"):
return 1
elif value in ("n", "no", "f", "false", "off", "0"):
return 0
else:
raise ValueError(f"invalid truth value {value}")
def get_int_from_env(env_keys, default):
"""Returns the first positive env value found in the `env_keys` list or the default."""
for e in env_keys:
val = int(os.environ.get(e, -1))
if val >= 0:
return val
return default
def parse_flag_from_env(key, default=False):
"""Returns truthy value for `key` from the env if available else the default."""
value = os.environ.get(key, str(default))
return str_to_bool(value) == 1 # As its name indicates `str_to_bool` actually returns an int...
def parse_choice_from_env(key, default="no"):
value = os.environ.get(key, str(default))
return value
def are_libraries_initialized(*library_names: str) -> Dict[str, bool]:
"""
Checks if any of `library_names` are imported in the environment. Will return results as a `key:bool` pair.
"""
return [lib_name for lib_name in library_names if lib_name in sys.modules]
def check_cuda_p2p_ib_support():
"""
Checks if the devices being used have issues with P2P and IB communications, namely any consumer GPU hardware after
the 3090.
"""
if torch.cuda.is_available():
# Get the first device/default
device_name = torch.cuda.get_device_name()
device_count = torch.cuda.device_count()
unsupported_devices = ["RTX 3090", "RTX 40"]
if device_count > 1:
if any(device in device_name for device in unsupported_devices):
return False
return True
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