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f5d2dd3 7965430 f5d2dd3 7965430 f5d2dd3 7965430 f5d2dd3 7965430 f5d2dd3 7965430 f5d2dd3 7965430 f5d2dd3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 | # Copyright (c) 2025, NVIDIA CORPORATION. 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.
"""
Module with guards for optional libraries, that cannot be listed in `requirements.txt`.
Provides helper constants and decorators to check if the library is available in the system.
"""
__all__ = [
# kenlm
"KENLM_AVAILABLE",
"kenlm_required",
# k2
"K2_AVAILABLE",
"k2_required",
# triton
"TRITON_AVAILABLE",
"triton_required",
# cuda-python
"CUDA_PYTHON_AVAILABLE",
"cuda_python_required",
# numba
"NUMBA_AVAILABLE",
"numba_required",
# numba-cuda
"NUMBA_CUDA_AVAILABLE",
"numba_cuda_required",
]
import importlib.util
from functools import wraps
from packaging.version import Version
from nemo.core.utils.k2_utils import K2_INSTALLATION_MESSAGE
from nemo.core.utils.numba_utils import __NUMBA_MINIMUM_VERSION__, numba_cpu_is_supported, numba_cuda_is_supported
def is_lib_available(name: str) -> bool:
"""
Checks if the library/package with `name` is available in the system
NB: try/catch with importlib.import_module(name) requires importing the library, which can be slow.
So, `find_spec` should be preferred
"""
return importlib.util.find_spec(name) is not None
KENLM_AVAILABLE = is_lib_available("kenlm")
KENLM_INSTALLATION_MESSAGE = "Try installing kenlm with `pip install kenlm`"
TRITON_AVAILABLE = is_lib_available("triton")
TRITON_INSTALLATION_MESSAGE = "Try installing triton with `pip install triton`"
NUMBA_AVAILABLE = numba_cpu_is_supported(__NUMBA_MINIMUM_VERSION__)
NUMBA_INSTALLATION_MESSAGE = (
"Numba is not found. Install with `pip install numba`. "
"For GPU support install with `pip install numba-cuda[cu12]` or `pip install numba-cuda[cu13]`"
)
NUMBA_CUDA_AVAILABLE = numba_cuda_is_supported(__NUMBA_MINIMUM_VERSION__)
NUMBA_CUDA_INSTALLATION_MESSAGE = (
"Numba with GPU support is not available. "
"For GPU support install with `pip install numba-cuda[cu12]` or `pip install numba-cuda[cu13]`"
)
try:
from nemo.core.utils.k2_guard import k2 as _ # noqa: F401
K2_AVAILABLE = True
except (ImportError, ModuleNotFoundError):
K2_AVAILABLE = False
try:
from cuda.bindings import __version__ as cuda_python_version
if Version(cuda_python_version) >= Version("12.6.0"):
CUDA_PYTHON_AVAILABLE = True
else:
CUDA_PYTHON_AVAILABLE = False
except (ImportError, ModuleNotFoundError):
CUDA_PYTHON_AVAILABLE = False
CUDA_PYTHON_INSTALLATION_MESSAGE = "Try installing cuda-python with `pip install cuda-python>=12.6.0`"
def identity_decorator(f):
"""Identity decorator for further using in conditional decorators"""
return f
def _lib_required(is_available: bool, name: str, message: str | None = None):
"""
Decorator factory. Returns identity decorator if lib `is_available`,
otherwise returns a decorator which returns a function that raises an error when called.
Such decorator can be used for conditional checks for optional libraries in functions and methods
with zero computational overhead.
"""
if is_available:
return identity_decorator
# return wrapper that will raise an error when the function is called
def function_stub_with_error_decorator(f):
"""Decorator that replaces the function and raises an error when called"""
@wraps(f)
def wrapper(*args, **kwargs):
error_msg = f"Module {name} required for the function {f.__name__} is not found."
if message:
error_msg += f" {message}"
raise ModuleNotFoundError(error_msg)
return wrapper
return function_stub_with_error_decorator
kenlm_required = _lib_required(is_available=KENLM_AVAILABLE, name="kenlm", message=KENLM_INSTALLATION_MESSAGE)
triton_required = _lib_required(is_available=TRITON_AVAILABLE, name="triton", message=TRITON_INSTALLATION_MESSAGE)
k2_required = _lib_required(is_available=K2_AVAILABLE, name="k2", message=K2_INSTALLATION_MESSAGE)
cuda_python_required = _lib_required(
is_available=CUDA_PYTHON_AVAILABLE, name="cuda_python", message=CUDA_PYTHON_INSTALLATION_MESSAGE
)
numba_required = _lib_required(is_available=NUMBA_AVAILABLE, name="numba", message=NUMBA_INSTALLATION_MESSAGE)
numba_cuda_required = _lib_required(
is_available=NUMBA_CUDA_AVAILABLE, name="numba-cuda", message=NUMBA_CUDA_INSTALLATION_MESSAGE
)
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