def test_check_version():
assert check_version("sparseml",
alternate_package_names=["sparseml-nightly"])
assert not check_version(
"sparseml",
min_version="10.0.0",
raise_on_error=False,
alternate_package_names=["sparseml-nightly"],
)
with pytest.raises(ImportError):
check_version(
"sparseml",
min_version="10.0.0",
alternate_package_names=["sparseml-nightly"],
)
assert not check_version(
"sparseml",
max_version="0.0.1",
raise_on_error=False,
alternate_package_names=["sparseml-nightly"],
)
with pytest.raises(ImportError):
check_version(
"sparseml",
max_version="0.0.1",
alternate_package_names=["sparseml-nightly"],
)
assert not check_version("unknown", raise_on_error=False)
with pytest.raises(ImportError):
check_version("unknown")
def check_keras_install(
min_tf_version: Optional[str] = _DEF_TF_MIN_VERSION,
max_tf_version: Optional[str] = None,
min_native_version: Optional[str] = _DEF_KERAS_MIN_VERSION,
require_tensorflow_backend: bool = True,
raise_on_error: bool = True,
) -> bool:
"""
Check that the keras package is installed.
If raise_on_error, will raise an ImportError if it is not installed or
the required version range, if set, is not installed.
If not raise_on_error, will return True if installed with required version
and False otherwise.
:param min_tf_version: The minimum version for keras that it must be greater than
or equal to, if unset will require no minimum version
:type min_tf_version: str
:param max_tf_version: The maximum version for keras that it must be less than
or equal to, if unset will require no maximum version.
:type max_tf_version: str
:param min_native_version: The minimum version for native keras that it must be
greater than or equal to if installed
:type min_native_version: str
:param require_tensorflow_backend: True to require keras to use the tensorflow
backend, False otherwise.
:type require_tensorflow_backend: bool
:param raise_on_error: True to raise any issues such as not installed,
minimum version, or maximum version as ImportError. False to return the result.
:type raise_on_error: bool
:return: If raise_on_error, will return False if keras is not installed
or the version is outside the accepted bounds and True if everything is correct.
:rtype: bool
"""
if keras_err is not None:
if raise_on_error:
raise keras_err
return False
if tensorflow_err is not None and require_tensorflow_backend:
if raise_on_error:
raise tensorflow_err
return False
if require_tensorflow_backend and not check_version(
"tensorflow", min_tf_version, max_tf_version, raise_on_error):
return False
if is_native_keras and not check_version("keras", min_native_version, None,
raise_on_error):
return False
return True
def check_torchvision_install(
min_version: Optional[str] = None,
max_version: Optional[str] = None,
raise_on_error: bool = True,
) -> bool:
"""
Check that the torchvision package is installed.
If raise_on_error, will raise an ImportError if it is not installed or
the required version range, if set, is not installed.
If not raise_on_error, will return True if installed with required version
and False otherwise.
:param min_version: The minimum version for torchvision that it must be greater than
or equal to, if unset will require no minimum version
:type min_version: str
:param max_version: The maximum version for torchvision that it must be less than
or equal to, if unset will require no maximum version.
:type max_version: str
:param raise_on_error: True to raise any issues such as not installed,
minimum version, or maximum version as ImportError. False to return the result.
:type raise_on_error: bool
:return: If raise_on_error, will return False if torchvision is not installed
or the version is outside the accepted bounds and True if everything is correct.
:rtype: bool
"""
if torchvision_err is not None:
if raise_on_error:
raise torchvision_err
return False
return check_version("torchvision", min_version, max_version,
raise_on_error)
def test_check_version():
assert check_version("sparseml")
assert not check_version(
"sparseml", min_version="10.0.0", raise_on_error=False)
with pytest.raises(ImportError):
check_version("sparseml", min_version="10.0.0")
assert not check_version(
"sparseml", max_version="0.0.1", raise_on_error=False)
with pytest.raises(ImportError):
check_version("sparseml", max_version="0.0.1")
assert not check_version("unknown", raise_on_error=False)
with pytest.raises(ImportError):
check_version("unknown")
def check_tensorflow_install(
min_version: Optional[str] = _TENSORFLOW_MIN_VERSION,
max_version: Optional[str] = _TENSORFLOW_MAX_VERSION,
raise_on_error: bool = True,
allow_env_ignore_flag: bool = True,
) -> bool:
"""
Check that the tensorflow package is installed.
If raise_on_error, will raise an ImportError if it is not installed or
the required version range, if set, is not installed.
If not raise_on_error, will return True if installed with required version
and False otherwise.
:param min_version: The minimum version for tensorflow that it must be greater than
or equal to, if unset will require no minimum version
:type min_version: str
:param max_version: The maximum version for tensorflow that it must be less than
or equal to, if unset will require no maximum version.
:type max_version: str
:param raise_on_error: True to raise any issues such as not installed,
minimum version, or maximum version as ImportError. False to return the result.
:type raise_on_error: bool
:param allow_env_ignore_flag: True to allow the env variable SPARSEML_IGNORE_TFV1
to ignore the tensorflow install and version checks.
False to ignore the ignore flag.
:type allow_env_ignore_flag: bool
:return: If raise_on_error, will return False if tensorflow is not installed
or the version is outside the accepted bounds and True if everything is correct.
:rtype: bool
"""
if allow_env_ignore_flag and os.getenv("SPARSEML_IGNORE_TFV1", False):
return True
if tensorflow_err is not None:
if raise_on_error:
raise tensorflow_err
return False
return check_version(
"tensorflow",
min_version,
max_version,
raise_on_error,
alternate_package_names=["tensorflow-gpu"],
)
