Move from deprecated distutils to packaging (#5687)

- converts all calls from distutils to packaging as distutils
  is deprecated and will be removed sooner or later

Signed-off-by: Janusz Lisiecki <jlisiecki@nvidia.com>

Acknowledgements.txt

@@ -4410,3 +4410,37 @@ products or services of Licensee, or any third party.
 8. By copying, installing or otherwise using Python, Licensee
 agrees to be bound by the terms and conditions of this License
 Agreement.
+
+==============================================================================
+str2bool
+
+
+BSD 3-Clause License
+
+Copyright (c) 2017, SymonSoft
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+
+* Redistributions of source code must retain the above copyright notice, this
+  list of conditions and the following disclaimer.
+
+* Redistributions in binary form must reproduce the above copyright notice,
+  this list of conditions and the following disclaimer in the documentation
+  and/or other materials provided with the distribution.
+
+* Neither the name of the copyright holder nor the names of its
+  contributors may be used to endorse or promote products derived from
+  this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

conda/dali_python_bindings/recipe/meta.yaml

@@ -81,6 +81,7 @@ requirements:
     - astunparse >=1.6.0
     - gast >=0.3.3
     - dm-tree >=0.1.8
+    - packaging
     - nvidia-dali-core{% if environ.get('NVIDIA_DALI_BUILD_FLAVOR', '')|length %}{{"-" + environ.get('NVIDIA_DALI_BUILD_FLAVOR', '')}}{% endif %}-cuda{{ environ.get('CUDA_VERSION', '') | replace(".","") }} ={{ environ.get('DALI_CONDA_BUILD_VERSION', '') }}
     - nvidia-nvimagecodec-cuda{{ environ.get('CUDA_VERSION', '') | replace(".","") }}
   run:
@@ -94,6 +95,7 @@ requirements:
     - astunparse >=1.6.0
     - gast >=0.3.3
     - dm-tree >=0.1.8
+    - packaging
     - nvidia-dali-core{% if environ.get('NVIDIA_DALI_BUILD_FLAVOR', '')|length %}{{"-" + environ.get('NVIDIA_DALI_BUILD_FLAVOR', '')}}{% endif %}-cuda{{ environ.get('CUDA_VERSION', '') | replace(".","") }} ={{ environ.get('DALI_CONDA_BUILD_VERSION', '') }}
     - nvidia-nvimagecodec-cuda{{ environ.get('CUDA_VERSION', '') | replace(".","") }}
 about:

dali/python/nvidia/dali/_autograph/pyct/gast_util.py

@@ -18,9 +18,19 @@
 import functools
 import gast
 
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 
+def convert_to_version(function):
+    """Makes sure that returned function value is a Version object"""
+
+    def wrap_function(*args, **kwargs):
+        return Version(function(*args, **kwargs))
+
+    return wrap_function
+
+
+@convert_to_version
 def get_gast_version():
     """Gast exports `__version__` from 0.5.3 onwards, we need to look it up in a different way."""
     if hasattr(gast, "__version__"):
@@ -76,7 +86,7 @@ def _compat_assign_gast_5(targets, value, type_comment):
     return gast.Assign(targets=targets, value=value, type_comment=type_comment)
 
 
-if get_gast_version() < LooseVersion("0.5"):
+if get_gast_version() < Version("0.5"):
     compat_assign = _compat_assign_gast_4
 else:
     compat_assign = _compat_assign_gast_5

dali/python/nvidia/dali/plugin/jax/__init__.py

@@ -16,15 +16,15 @@
 
 from . import fn  # noqa: F401
 
-from distutils.version import LooseVersion
+from packaging.version import Version
 from .iterator import DALIGenericIterator, data_iterator
 
 assert (
     sys.version_info.major == 3 and sys.version_info.minor >= 8
 ), "DALI JAX support requires Python 3.8 or above"
 
 
-assert LooseVersion(jax.__version__) >= LooseVersion(
+assert Version(jax.__version__) >= Version(
     "0.4.11"
 ), "DALI JAX support requires JAX 0.4.11 or above"
 

dali/python/nvidia/dali/plugin/jax/fn/_jax_function_impl.py

@@ -14,7 +14,7 @@
 
 from typing import Optional, Protocol, Tuple, Union
 
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 import jax
 import jax.dlpack
@@ -170,7 +170,7 @@ def flip_horizontal(image: jax.Array):
         The transformed function that processes DALI-traced batches (DataNodes).
     """
 
-    if LooseVersion(jax.__version__) < LooseVersion("0.4.16"):
+    if Version(jax.__version__) < Version("0.4.16"):
         raise RuntimeError("DALI `jax_function` requires JAX 0.4.16 or above.")
 
     def decorator(function):

dali/python/nvidia/dali/plugin/numba/experimental/__init__.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 from nvidia.dali.pipeline import Pipeline
 from nvidia.dali.data_node import DataNode as _DataNode
@@ -57,8 +57,8 @@
 
 # Minimal version of Numba that is required for Numba GPU operator to work
 minimal_numba_version = {
-    11: LooseVersion("0.55.2"),
-    12: LooseVersion("0.57.0"),
+    11: Version("0.55.2"),
+    12: Version("0.57.0"),
 }
 
 
@@ -196,7 +196,7 @@ def _get_run_fn_gpu(self, run_fn, types, dims):
         for dali_type, ndim in zip(types, dims):
             cuda_arguments.append(numba_types.Array(_to_numba[dali_type], ndim, "C"))
 
-        if LooseVersion(nb.__version__) < LooseVersion("0.57.0"):
+        if Version(nb.__version__) < Version("0.57.0"):
             cres = cuda.compiler.compile_cuda(run_fn, numba_types.void, cuda_arguments)
         else:
             pipeline = Pipeline.current()
@@ -210,7 +210,7 @@ def _get_run_fn_gpu(self, run_fn, types, dims):
         code = run_fn.__code__
         filename = code.co_filename
         linenum = code.co_firstlineno
-        if LooseVersion(nb.__version__) < LooseVersion("0.57.0"):
+        if Version(nb.__version__) < Version("0.57.0"):
             nvvm_options["debug"] = False
             nvvm_options["lineinfo"] = False
             lib, _ = tgt_ctx.prepare_cuda_kernel(
@@ -509,7 +509,7 @@ def __init__(
 
     @staticmethod
     def _check_minimal_numba_version(throw: bool = True):
-        current_version = LooseVersion(nb.__version__)
+        current_version = Version(nb.__version__)
         toolkit_version = cuda.runtime.get_version()
         if toolkit_version[0] not in minimal_numba_version:
             if throw:
@@ -522,7 +522,7 @@ def _check_minimal_numba_version(throw: bool = True):
                 raise RuntimeError(
                     f"Insufficient Numba version. Numba GPU operator "
                     f"requires Numba {str(min_ver)} or higher. "
-                    f"Detected version: {str(LooseVersion(nb.__version__))}."
+                    f"Detected version: {str(Version(nb.__version__))}."
                 )
             else:
                 return False

dali/python/nvidia/dali/plugin/paddle.py

@@ -18,19 +18,17 @@
 
 import numpy as np
 import paddle
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 from nvidia.dali import types
 from nvidia.dali.backend import TensorListCPU, TensorGPU, TensorListGPU
 from nvidia.dali.plugin.base_iterator import _DaliBaseIterator
 from nvidia.dali.plugin.base_iterator import LastBatchPolicy
 
 if isinstance(paddle.__version__, str):
-    assert LooseVersion(paddle.__version__) == LooseVersion("0.0.0") or LooseVersion(
+    assert Version(paddle.__version__) == Version("0.0.0") or Version(
         paddle.__version__
-    ) >= LooseVersion(
-        "2.0.0"
-    ), "DALI PaddlePaddle support requires Paddle develop or release >= 2.0.0"
+    ) >= Version("2.0.0"), "DALI PaddlePaddle support requires Paddle develop or release >= 2.0.0"
 
 
 dtype_map = {

dali/python/nvidia/dali/plugin/tf.py

@@ -26,7 +26,7 @@
 from nvidia.dali._utils.external_source_impl import _get_generator_from_source_desc
 from nvidia.dali._utils.external_source_impl import _cycle_enabled
 
-from distutils.version import LooseVersion
+from packaging.version import Version
 import warnings
 
 from nvidia.dali_tf_plugin import dali_tf_plugin
@@ -307,29 +307,29 @@ def DALIRawIterator():
 
 
 def _get_tf_version():
-    return LooseVersion(tf.__version__)
+    return Version(tf.__version__)
 
 
-MIN_TENSORFLOW_VERSION = LooseVersion("1.15")
+MIN_TENSORFLOW_VERSION = Version("1.15")
 
 
 def dataset_compatible_tensorflow():
     """Returns ``True`` if current TensorFlow version is compatible with DALIDataset."""
-    return LooseVersion(tf.__version__) >= MIN_TENSORFLOW_VERSION
+    return Version(tf.__version__) >= MIN_TENSORFLOW_VERSION
 
 
 def dataset_inputs_compatible_tensorflow():
     """Returns ``True`` if the current TensorFlow version is compatible with
     experimental.DALIDatasetWithInputs and input Datasets can be used with DALI.
     """
-    return LooseVersion(tf.__version__) >= LooseVersion("2.4.1")
+    return Version(tf.__version__) >= Version("2.4.1")
 
 
 def dataset_distributed_compatible_tensorflow():
     """Returns ``True`` if the tf.distribute APIs for current TensorFlow version are compatible
     with DALIDataset.
     """
-    return LooseVersion(tf.__version__) >= LooseVersion("2.5.0")
+    return Version(tf.__version__) >= Version("2.5.0")
 
 
 def _get_experimental():
@@ -813,7 +813,7 @@ def _as_variant_tensor(self):
                 fail_on_device_mismatch=self._fail_on_device_mismatch,
             )
 
-    if _get_tf_version() < LooseVersion("2.0"):
+    if _get_tf_version() < Version("2.0"):
 
         class _DALIDatasetImpl(dataset_ops.DatasetV1Adapter):
             @functools.wraps(_DALIDatasetV2.__init__)

dali/python/setup.py.in

@@ -87,6 +87,7 @@ For more details please check the
           # 1.16 on python 3.12 due to import six.moves
           'six >= 1.16',
           'dm-tree',
+          'packaging',
           @DALI_INSTALL_REQUIRES_NVIMGCODEC@
           ],
      )

dali/test/python/autograph/pyct/test_loader.py

@@ -21,7 +21,7 @@
 import unittest
 
 import gast
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 from nvidia.dali._autograph.pyct import ast_util
 from nvidia.dali._autograph.pyct import gast_util
@@ -79,7 +79,7 @@ def test_load_ast(self):
             decorator_list=[],
             returns=None,
             type_comment=None,
-            **{"type_params": []} if gast_util.get_gast_version() >= LooseVersion("0.5.5") else {},
+            **{"type_params": []} if gast_util.get_gast_version() >= Version("0.5.5") else {},
         )
 
         module, source, _ = loader.load_ast(node)

dali/test/python/test_dali_tf_dataset_mnist.py

@@ -21,7 +21,7 @@
 from shutil import rmtree as remove_directory
 import tensorflow as tf
 import tensorflow.compat.v1 as tf_v1
-from distutils.version import StrictVersion
+from packaging.version import Version
 from nose import SkipTest
 
 
@@ -116,7 +116,7 @@ def run_keras_single_device(device="cpu", device_id=0):
 
 
 def graph_model(images, reuse, is_training):
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     with tf_v1.variable_scope("mnist_net", reuse=reuse):
         images = tf_v1.layers.flatten(images)
@@ -196,7 +196,7 @@ def _run_config(device="cpu", device_id=0):
 
 
 def run_estimators_single_device(device="cpu", device_id=0):
-    if StrictVersion(tf.__version__) < StrictVersion("2.16"):
+    if Version(tf.__version__) < Version("2.16"):
         with tf.device("/{0}:{1}".format(device, device_id)):
             model = keras_model()
         model = tf.keras.estimator.model_to_estimator(

dali/test/python/test_dali_tf_dataset_mnist_eager.py

@@ -19,7 +19,7 @@
 from test_utils_tensorflow import skip_for_incompatible_tf, available_gpus
 from nose_utils import raises
 from nose import SkipTest
-from distutils.version import LooseVersion
+from packaging.version import Version
 
 tf.compat.v1.enable_eager_execution()
 
@@ -60,7 +60,7 @@ def test_keras_wrong_placement_cpu():
 def test_keras_multi_gpu_mirrored_strategy():
     # due to compatibility problems between the driver, cuda version and
     # TensorFlow 2.12 test_keras_multi_gpu_mirrored_strategy doesn't work.
-    if LooseVersion(tf.__version__) >= LooseVersion("2.12.0"):
+    if Version(tf.__version__) >= Version("2.12.0"):
         raise SkipTest("This test is not supported for TensorFlow 2.12")
     strategy = tf.distribute.MirroredStrategy(devices=available_gpus())
 

dali/test/python/test_dali_tf_dataset_mnist_graph.py

@@ -16,35 +16,35 @@
 import tensorflow.compat.v1 as tf_v1
 from nose_utils import with_setup, SkipTest, raises
 import test_dali_tf_dataset_mnist as mnist
-from distutils.version import StrictVersion
+from packaging.version import Version
 
 mnist.tf.compat.v1.disable_eager_execution()
 
 
 @with_setup(tf.keras.backend.clear_session)
 def test_keras_single_gpu():
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     mnist.run_keras_single_device("gpu", 0)
 
 
 @with_setup(tf.keras.backend.clear_session)
 def test_keras_single_other_gpu():
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     mnist.run_keras_single_device("gpu", 1)
 
 
 @with_setup(tf.keras.backend.clear_session)
 def test_keras_single_cpu():
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     mnist.run_keras_single_device("cpu", 0)
 
 
 @raises(tf.errors.OpError, "TF device and DALI device mismatch. TF*: CPU, DALI*: GPU for output")
 def test_keras_wrong_placement_gpu():
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     with tf.device("cpu:0"):
         model = mnist.keras_model()
@@ -55,7 +55,7 @@ def test_keras_wrong_placement_gpu():
 
 @raises(tf.errors.OpError, "TF device and DALI device mismatch. TF*: GPU, DALI*: CPU for output")
 def test_keras_wrong_placement_cpu():
-    if StrictVersion(tf.__version__) >= StrictVersion("2.16"):
+    if Version(tf.__version__) >= Version("2.16"):
         raise SkipTest("TF < 2.16 is required for this test")
     with tf.device("gpu:0"):
         model = mnist.keras_model()

dali/test/python/test_utils.py

@@ -26,7 +26,7 @@
 import subprocess
 import sys
 import tempfile
-from distutils.version import LooseVersion
+from packaging.version import Version
 from nose_utils import SkipTest
 
 
@@ -945,8 +945,8 @@ def check_numba_compatibility_cpu(if_skip=True):
     # Numba bug:
     # https://github.com/numba/numba/issues/8567
     if platform.processor().lower() in ("arm64", "aarch64", "armv8") and (
-        LooseVersion(numba.__version__) >= LooseVersion("0.57.0")
-        and LooseVersion(numba.__version__) < LooseVersion("0.59.0")
+        Version(numba.__version__) >= Version("0.57.0")
+        and Version(numba.__version__) < Version("0.59.0")
     ):
         if if_skip:
             raise SkipTest()