def get_default_pip_requirements():
"""
:return: A list of default pip requirements for MLflow Models produced by this flavor.
Calls to :func:`save_model()` and :func:`log_model()` produce a pip environment
that, at minimum, contains these requirements.
"""
return [_get_pinned_requirement("statsmodels")]
def get_default_pip_requirements():
"""
:return: A list of default pip requirements for MLflow Models produced with the ``Diviner``
flavor. Calls to :py:func:`save_model()` and :py:func:`log_model()` produce a pip
environment that, at a minimum, contains these requirements.
"""
return [_get_pinned_requirement("diviner")]
def get_default_pip_requirements():
"""
:return: A list of default pip requirements for MLflow Models produced by this flavor.
Calls to :func:`save_model()` and :func:`log_model()` produce a pip environment
that, at minimum, contains these requirements.
"""
import tensorflow as tf
pip_deps = [_get_pinned_requirement("tensorflow")]
# tensorflow >= 2.6.0 requires keras:
# https://github.com/tensorflow/tensorflow/blob/v2.6.0/tensorflow/tools/pip_package/setup.py#L106
# To prevent a different version of keras from being installed by tensorflow when creating
# a serving environment, add a pinned requirement for keras
if Version(tf.__version__) >= Version("2.6.0"):
pip_deps.append(_get_pinned_requirement("keras"))
return pip_deps
def get_default_pip_requirements():
"""
:return: A list of default pip requirements for MLflow Models produced by this flavor.
Calls to :func:`save_model()` and :func:`log_model()` produce a pip environment
that, at minimum, contains these requirements.
"""
# Strip the suffix from `dev` versions of PySpark, which are not
# available for installation from Anaconda or PyPI
pyspark_req = re.sub(r"(\.?)dev.*$", "", _get_pinned_requirement("pyspark"))
return [pyspark_req]
def get_default_pip_requirements():
"""
:return: A list of default pip requirements for MLflow Models produced by this flavor.
Calls to :func:`save_model()` and :func:`log_model()` produce a pip environment
that, at a minimum, contains these requirements.
"""
# Note: Prophet's whl build process will fail due to missing dependencies, defaulting
# to setup.py installation process.
# If a pystan installation error occurs, ensure gcc>=8 is installed in your environment.
# See: https://gcc.gnu.org/install/
return [_get_pinned_requirement("prophet")]
def test_get_pinned_requirement_local_version_label(tmpdir):
package = tmpdir.join("my_package.py")
lvl = "abc.def.ghi" # Local version label
package.write(f"__version__ = '1.2.3+{lvl}'")
sys.path.insert(0, tmpdir.strpath)
with mock.patch(
"mlflow.utils.requirements_utils._logger.warning") as mock_warning:
req = _get_pinned_requirement("my_package")
mock_warning.assert_called_once()
(first_pos_arg, ) = mock_warning.call_args[0]
assert first_pos_arg.startswith(
f"Found my_package version (1.2.3+{lvl}) contains a local version label (+{lvl})."
)
assert req == "my_package==1.2.3"
