[Improvement] Improve digit_version & use it for version_checking (#1185)

* improve digit_version & use it for version_checking

* more testing for digit_version

* setuptools >= 50 is needed

* fix CI

* add debuging log

* >= to ==

* fix lint

* remove

* add failure case

* replace

* fix

* consider TORCH_VERSION == 'parrots'

* add unittest

* digit_version do not deal with the case if 'parrots' in version name.

.github/workflows/build.yml

@@ -41,6 +41,8 @@ jobs:
           python-version: ${{ matrix.python-version }}
       - name: Install system dependencies
         run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Validate the installation
@@ -75,6 +77,8 @@ jobs:
         run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg
       - name: Install PyTorch
         run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Validate the installation
@@ -118,6 +122,8 @@ jobs:
         if: ${{matrix.torchvision == '0.4.2'}}
       - name: Install PyTorch
         run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Validate the installation
@@ -188,6 +194,8 @@ jobs:
         run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
       - name: Install system dependencies
         run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Validate the installation
@@ -258,6 +266,8 @@ jobs:
         run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
       - name: Install system dependencies
         run: sudo apt-get update && sudo apt-get install -y ffmpeg libturbojpeg
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: rm -rf .eggs && pip install -e .
       - name: Validate the installation
@@ -310,6 +320,8 @@ jobs:
         if: ${{matrix.torchvision == '0.4.2'}}
       - name: Install PyTorch
         run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} --no-cache-dir
+      - name: Upgrade Setuptools
+        run: pip install setuptools==52
       - name: Build and install
         run: |
           rm -rf .eggs

mmcv/cnn/bricks/activation.py

-from distutils.version import LooseVersion
-
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
-from mmcv.utils import TORCH_VERSION, build_from_cfg
+from mmcv.utils import TORCH_VERSION, build_from_cfg, digit_version
 from .registry import ACTIVATION_LAYERS
 
 for module in [
@@ -73,7 +71,7 @@ class GELU(nn.Module):
 
 
 if (TORCH_VERSION == 'parrots'
-        or LooseVersion(TORCH_VERSION) < LooseVersion('1.4')):
+        or digit_version(TORCH_VERSION) < digit_version('1.4')):
     ACTIVATION_LAYERS.register_module(module=GELU)
 else:
     ACTIVATION_LAYERS.register_module(module=nn.GELU)

mmcv/ops/saconv.py

-from distutils.version import LooseVersion
-
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
 from mmcv.cnn import CONV_LAYERS, ConvAWS2d, constant_init
 from mmcv.ops.deform_conv import deform_conv2d
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 
 
 @CONV_LAYERS.register_module(name='SAC')
@@ -108,10 +106,10 @@ class SAConv2d(ConvAWS2d):
             out_s = deform_conv2d(x, offset, weight, self.stride, self.padding,
                                   self.dilation, self.groups, 1)
         else:
-            if (LooseVersion(TORCH_VERSION) < LooseVersion('1.5.0')
-                    or TORCH_VERSION == 'parrots'):
+            if (TORCH_VERSION == 'parrots'
+                    or digit_version(TORCH_VERSION) < digit_version('1.5.0')):
                 out_s = super().conv2d_forward(x, weight)
-            elif LooseVersion(TORCH_VERSION) >= LooseVersion('1.8.0'):
+            elif digit_version(TORCH_VERSION) >= digit_version('1.8.0'):
                 # bias is a required argument of _conv_forward in torch 1.8.0
                 out_s = super()._conv_forward(x, weight, zero_bias)
             else:
@@ -126,10 +124,10 @@ class SAConv2d(ConvAWS2d):
             out_l = deform_conv2d(x, offset, weight, self.stride, self.padding,
                                   self.dilation, self.groups, 1)
         else:
-            if (LooseVersion(TORCH_VERSION) < LooseVersion('1.5.0')
-                    or TORCH_VERSION == 'parrots'):
+            if (TORCH_VERSION == 'parrots'
+                    or digit_version(TORCH_VERSION) < digit_version('1.5.0')):
                 out_l = super().conv2d_forward(x, weight)
-            elif LooseVersion(TORCH_VERSION) >= LooseVersion('1.8.0'):
+            elif digit_version(TORCH_VERSION) >= digit_version('1.8.0'):
                 # bias is a required argument of _conv_forward in torch 1.8.0
                 out_l = super()._conv_forward(x, weight, zero_bias)
             else:

mmcv/parallel/distributed.py

 # Copyright (c) Open-MMLab. All rights reserved.
-from distutils.version import LooseVersion
-
 import torch
 from torch.nn.parallel.distributed import (DistributedDataParallel,
                                            _find_tensors)
 
 from mmcv import print_log
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 from .scatter_gather import scatter_kwargs
 
 
@@ -39,8 +37,9 @@ class MMDistributedDataParallel(DistributedDataParallel):
 
         # In PyTorch >= 1.7, ``reducer._rebuild_buckets()`` is moved from the
         # end of backward to the beginning of forward.
-        if (LooseVersion(TORCH_VERSION) >= LooseVersion('1.7') and 'parrots'
-                not in TORCH_VERSION) and self.reducer._rebuild_buckets():
+        if ('parrots' not in TORCH_VERSION
+                and digit_version(TORCH_VERSION) >= digit_version('1.7')
+                and self.reducer._rebuild_buckets()):
             print_log(
                 'Reducer buckets have been rebuilt in this iteration.',
                 logger='mmcv')
@@ -65,7 +64,8 @@ class MMDistributedDataParallel(DistributedDataParallel):
             else:
                 self.reducer.prepare_for_backward([])
         else:
-            if LooseVersion(TORCH_VERSION) > LooseVersion('1.2'):
+            if ('parrots' not in TORCH_VERSION
+                    and digit_version(TORCH_VERSION) > digit_version('1.2')):
                 self.require_forward_param_sync = False
         return output
 
@@ -79,8 +79,9 @@ class MMDistributedDataParallel(DistributedDataParallel):
         """
         # In PyTorch >= 1.7, ``reducer._rebuild_buckets()`` is moved from the
         # end of backward to the beginning of forward.
-        if (LooseVersion(TORCH_VERSION) >= LooseVersion('1.7') and 'parrots'
-                not in TORCH_VERSION) and self.reducer._rebuild_buckets():
+        if ('parrots' not in TORCH_VERSION
+                and digit_version(TORCH_VERSION) >= digit_version('1.7')
+                and self.reducer._rebuild_buckets()):
             print_log(
                 'Reducer buckets have been rebuilt in this iteration.',
                 logger='mmcv')
@@ -105,6 +106,7 @@ class MMDistributedDataParallel(DistributedDataParallel):
             else:
                 self.reducer.prepare_for_backward([])
         else:
-            if LooseVersion(TORCH_VERSION) > LooseVersion('1.2'):
+            if ('parrots' not in TORCH_VERSION
+                    and digit_version(TORCH_VERSION) > digit_version('1.2')):
                 self.require_forward_param_sync = False
         return output

mmcv/parallel/distributed_deprecated.py

 # Copyright (c) Open-MMLab. All rights reserved.
-from distutils.version import LooseVersion
-
 import torch
 import torch.distributed as dist
 import torch.nn as nn
 from torch._utils import (_flatten_dense_tensors, _take_tensors,
                           _unflatten_dense_tensors)
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 from .registry import MODULE_WRAPPERS
 from .scatter_gather import scatter_kwargs
 
@@ -42,7 +40,8 @@ class MMDistributedDataParallel(nn.Module):
             self._dist_broadcast_coalesced(module_states,
                                            self.broadcast_bucket_size)
         if self.broadcast_buffers:
-            if LooseVersion(TORCH_VERSION) < LooseVersion('1.0'):
+            if (TORCH_VERSION != 'parrots'
+                    and digit_version(TORCH_VERSION) < digit_version('1.0')):
                 buffers = [b.data for b in self.module._all_buffers()]
             else:
                 buffers = [b.data for b in self.module.buffers()]

mmcv/runner/dist_utils.py

@@ -3,7 +3,6 @@ import functools
 import os
 import subprocess
 from collections import OrderedDict
-from distutils.version import LooseVersion
 
 import torch
 import torch.multiprocessing as mp
@@ -11,7 +10,7 @@ from torch import distributed as dist
 from torch._utils import (_flatten_dense_tensors, _take_tensors,
                           _unflatten_dense_tensors)
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 
 
 def init_dist(launcher, backend='nccl', **kwargs):
@@ -79,7 +78,8 @@ def _init_dist_slurm(backend, port=None):
 
 
 def get_dist_info():
-    if LooseVersion(TORCH_VERSION) < LooseVersion('1.0'):
+    if (TORCH_VERSION != 'parrots'
+            and digit_version(TORCH_VERSION) < digit_version('1.0')):
         initialized = dist._initialized
     else:
         if dist.is_available():

mmcv/runner/fp16_utils.py

 import functools
 import warnings
 from collections import abc
-from distutils.version import LooseVersion
 from inspect import getfullargspec
 
 import numpy as np
 import torch
 import torch.nn as nn
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 from .dist_utils import allreduce_grads as _allreduce_grads
 
 try:
@@ -122,8 +121,8 @@ def auto_fp16(apply_to=None, out_fp32=False):
                     else:
                         new_kwargs[arg_name] = arg_value
             # apply converted arguments to the decorated method
-            if (TORCH_VERSION != 'parrots'
-                    and LooseVersion(TORCH_VERSION) >= LooseVersion('1.6.0')):
+            if (TORCH_VERSION != 'parrots' and
+                    digit_version(TORCH_VERSION) >= digit_version('1.6.0')):
                 with autocast(enabled=True):
                     output = old_func(*new_args, **new_kwargs)
             else:
@@ -208,8 +207,8 @@ def force_fp32(apply_to=None, out_fp16=False):
                     else:
                         new_kwargs[arg_name] = arg_value
             # apply converted arguments to the decorated method
-            if (TORCH_VERSION != 'parrots'
-                    and LooseVersion(TORCH_VERSION) >= LooseVersion('1.6.0')):
+            if (TORCH_VERSION != 'parrots' and
+                    digit_version(TORCH_VERSION) >= digit_version('1.6.0')):
                 with autocast(enabled=False):
                     output = old_func(*new_args, **new_kwargs)
             else:
@@ -249,7 +248,7 @@ def wrap_fp16_model(model):
         model (nn.Module): Model in FP32.
     """
     if (TORCH_VERSION == 'parrots'
-            or LooseVersion(TORCH_VERSION) < LooseVersion('1.6.0')):
+            or digit_version(TORCH_VERSION) < digit_version('1.6.0')):
         # convert model to fp16
         model.half()
         # patch the normalization layers to make it work in fp32 mode

mmcv/runner/hooks/logger/tensorboard.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import os.path as osp
-from distutils.version import LooseVersion
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 from ...dist_utils import master_only
 from ..hook import HOOKS
 from .base import LoggerHook
@@ -24,8 +23,8 @@ class TensorboardLoggerHook(LoggerHook):
     @master_only
     def before_run(self, runner):
         super(TensorboardLoggerHook, self).before_run(runner)
-        if (LooseVersion(TORCH_VERSION) < LooseVersion('1.1')
-                or TORCH_VERSION == 'parrots'):
+        if (TORCH_VERSION == 'parrots'
+                or digit_version(TORCH_VERSION) < digit_version('1.1')):
             try:
                 from tensorboardX import SummaryWriter
             except ImportError:

mmcv/runner/hooks/optimizer.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import copy
 from collections import defaultdict
-from distutils.version import LooseVersion
 from itertools import chain
 
 from torch.nn.utils import clip_grad
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 from ..dist_utils import allreduce_grads
 from ..fp16_utils import LossScaler, wrap_fp16_model
 from .hook import HOOKS, Hook
@@ -44,7 +43,7 @@ class OptimizerHook(Hook):
 
 
 if (TORCH_VERSION != 'parrots'
-        and LooseVersion(TORCH_VERSION) >= LooseVersion('1.6.0')):
+        and digit_version(TORCH_VERSION) >= digit_version('1.6.0')):
 
     @HOOKS.register_module()
     class Fp16OptimizerHook(OptimizerHook):

mmcv/utils/parrots_wrapper.py

 from functools import partial
-from pkg_resources import parse_version
 
 import torch
 
+from mmcv.utils import digit_version
+
 TORCH_VERSION = torch.__version__
 
 is_rocm_pytorch = False
-if parse_version(TORCH_VERSION) >= parse_version('1.5'):
+if (TORCH_VERSION != 'parrots'
+        and digit_version(TORCH_VERSION) >= digit_version('1.5')):
     from torch.utils.cpp_extension import ROCM_HOME
     is_rocm_pytorch = True if ((torch.version.hip is not None) and
                                (ROCM_HOME is not None)) else False

mmcv/utils/trace.py

 import warnings
-from distutils.version import LooseVersion
 
 import torch
 
+from mmcv.utils import digit_version
+
 
 def is_jit_tracing() -> bool:
-    if LooseVersion(torch.__version__) >= LooseVersion('1.6.0'):
+    if (torch.__version__ != 'parrots'
+            and digit_version(torch.__version__) >= digit_version('1.6.0')):
         on_trace = torch.jit.is_tracing()
         # In PyTorch 1.6, torch.jit.is_tracing has a bug.
         # Refers to https://github.com/pytorch/pytorch/issues/42448

mmcv/utils/version_utils.py

 import os
 import subprocess
+import warnings
+from pkg_resources import parse_version
 
 
-def digit_version(version_str):
+def digit_version(version_str: str, length: int = 4):
     """Convert a version string into a tuple of integers.
 
-    This method is usually used for comparing two versions.
+    This method is usually used for comparing two versions. For pre-release
+    versions: alpha < beta < rc.
 
     Args:
         version_str (str): The version string.
+        length (int): The maximum number of version levels. Default: 4.
 
     Returns:
         tuple[int]: The version info in digits (integers).
     """
-    digit_version = []
-    for x in version_str.split('.'):
-        if x.isdigit():
-            digit_version.append(int(x))
-        elif x.find('rc') != -1:
-            patch_version = x.split('rc')
-            digit_version.append(int(patch_version[0]) - 1)
-            digit_version.append(int(patch_version[1]))
-    return tuple(digit_version)
+    assert 'parrots' not in version_str
+    version = parse_version(version_str)
+    assert version.release, f'failed to parse version {version_str}'
+    release = list(version.release)
+    release = release[:length]
+    if len(release) < length:
+        release = release + [0] * (length - len(release))
+    if version.is_prerelease:
+        mapping = {'a': -3, 'b': -2, 'rc': -1}
+        val = -4
+        # version.pre can be None
+        if version.pre:
+            if version.pre[0] not in mapping:
+                warnings.warn(f'unknown prerelease version {version.pre[0]}, '
+                              'version checking may go wrong')
+            else:
+                val = mapping[version.pre[0]]
+            release.extend([val, version.pre[-1]])
+        else:
+            release.extend([val, 0])
+
+    elif version.is_postrelease:
+        release.extend([1, version.post])
+    else:
+        release.extend([0, 0])
+    return tuple(release)
 
 
 def _minimal_ext_cmd(cmd):

mmcv/version.py

 # Copyright (c) Open-MMLab. All rights reserved.
 
+from pkg_resources import parse_version
+
 __version__ = '1.3.9'
 
 
-def parse_version_info(version_str: str) -> tuple:
+def parse_version_info(version_str: str, length: int = 4) -> tuple:
     """Parse a version string into a tuple.
 
     Args:
         version_str (str): The version string.
+        length (int): The maximum number of version levels. Default: 4.
 
     Returns:
         tuple[int | str]: The version info, e.g., "1.3.0" is parsed into
-            (1, 3, 0), and "2.0.0rc1" is parsed into (2, 0, 0, 'rc1').
+            (1, 3, 0, 0, 0, 0), and "2.0.0rc1" is parsed into
+            (2, 0, 0, 0, 'rc', 1) (when length is set to 4).
     """
-    version_info = []
-    for x in version_str.split('.'):
-        if x.isdigit():
-            version_info.append(int(x))
-        elif x.find('rc') != -1:
-            patch_version = x.split('rc')
-            version_info.append(int(patch_version[0]))
-            version_info.append(f'rc{patch_version[1]}')
-    return tuple(version_info)
+    version = parse_version(version_str)
+    assert version.release, f'failed to parse version {version_str}'
+    release = list(version.release)
+    release = release[:length]
+    if len(release) < length:
+        release = release + [0] * (length - len(release))
+    if version.is_prerelease:
+        release.extend(list(version.pre))
+    elif version.is_postrelease:
+        release.extend(list(version.post))
+    else:
+        release.extend([0, 0])
+    return tuple(release)
 
 
 version_info = parse_version_info(__version__)

requirements/runtime.txt

@@ -3,4 +3,5 @@ numpy
 Pillow
 pyyaml
 regex;sys_platform=='win32'
+setuptools>=52
 yapf

requirements/test.txt

@@ -6,4 +6,5 @@ onnxruntime==1.4.0
 pytest
 PyTurboJPEG
 scipy
+setuptools>=52
 tiffile

tests/test_ops/test_deform_conv.py

-from distutils.version import LooseVersion
-
 import numpy as np
 import pytest
 import torch
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 
 try:
     # If PyTorch version >= 1.6.0 and fp16 is enabled, torch.cuda.amp.autocast
@@ -144,7 +142,7 @@ class TestDeformconv(object):
         # test amp when torch version >= '1.6.0', the type of
         # input data for deformconv might be torch.float or torch.half
         if (TORCH_VERSION != 'parrots'
-                and LooseVersion(TORCH_VERSION) >= LooseVersion('1.6.0')):
+                and digit_version(TORCH_VERSION) >= digit_version('1.6.0')):
             with autocast(enabled=True):
                 self._test_amp_deformconv(torch.float, 1e-1)
                 self._test_amp_deformconv(torch.half, 1e-1)

tests/test_ops/test_modulated_deform_conv.py

 import os
-from distutils.version import LooseVersion
 
 import numpy
 import torch
 
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 
 try:
     # If PyTorch version >= 1.6.0 and fp16 is enabled, torch.cuda.amp.autocast
@@ -114,7 +113,7 @@ class TestMdconv(object):
         # test amp when torch version >= '1.6.0', the type of
         # input data for mdconv might be torch.float or torch.half
         if (TORCH_VERSION != 'parrots'
-                and LooseVersion(TORCH_VERSION) >= LooseVersion('1.6.0')):
+                and digit_version(TORCH_VERSION) >= digit_version('1.6.0')):
             with autocast(enabled=True):
                 self._test_amp_mdconv(torch.float)
                 self._test_amp_mdconv(torch.half)

tests/test_runner/test_utils.py

 import os
 import random
-from pkg_resources import parse_version
 
 import numpy as np
 import torch
 
 from mmcv.runner import set_random_seed
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import TORCH_VERSION, digit_version
 
 is_rocm_pytorch = False
-if parse_version(TORCH_VERSION) >= parse_version('1.5'):
+if digit_version(TORCH_VERSION) >= digit_version('1.5'):
     from torch.utils.cpp_extension import ROCM_HOME
     is_rocm_pytorch = True if ((torch.version.hip is not None) and
                                (ROCM_HOME is not None)) else False

tests/test_utils/test_trace.py

-from distutils.version import LooseVersion
-
 import pytest
 import torch
 
-from mmcv.utils import is_jit_tracing
+from mmcv.utils import digit_version, is_jit_tracing
 
 
 @pytest.mark.skipif(
-    LooseVersion(torch.__version__) < LooseVersion('1.6.0'),
+    digit_version(torch.__version__) < digit_version('1.6.0'),
     reason='torch.jit.is_tracing is not available before 1.6.0')
 def test_is_jit_tracing():
 

tests/test_utils/test_version_utils.py

 from unittest.mock import patch
 
-from mmcv import digit_version, get_git_hash, parse_version_info
+import pytest
+
+from mmcv import get_git_hash, parse_version_info
+from mmcv.utils import digit_version
 
 
 def test_digit_version():
-    assert digit_version('0.2.16') == (0, 2, 16)
-    assert digit_version('1.2.3') == (1, 2, 3)
-    assert digit_version('1.2.3rc0') == (1, 2, 2, 0)
-    assert digit_version('1.2.3rc1') == (1, 2, 2, 1)
-    assert digit_version('1.0rc0') == (1, -1, 0)
+    assert digit_version('0.2.16') == (0, 2, 16, 0, 0, 0)
+    assert digit_version('1.2.3') == (1, 2, 3, 0, 0, 0)
+    assert digit_version('1.2.3rc0') == (1, 2, 3, 0, -1, 0)
+    assert digit_version('1.2.3rc1') == (1, 2, 3, 0, -1, 1)
+    assert digit_version('1.0rc0') == (1, 0, 0, 0, -1, 0)
+    assert digit_version('1.0') == digit_version('1.0.0')
+    assert digit_version('1.5.0+cuda90_cudnn7.6.3_lms') == digit_version('1.5')
+    assert digit_version('1.0.0dev') < digit_version('1.0.0a')
+    assert digit_version('1.0.0a') < digit_version('1.0.0a1')
+    assert digit_version('1.0.0a') < digit_version('1.0.0b')
+    assert digit_version('1.0.0b') < digit_version('1.0.0rc')
+    assert digit_version('1.0.0rc1') < digit_version('1.0.0')
+    assert digit_version('1.0.0') < digit_version('1.0.0post')
+    assert digit_version('1.0.0post') < digit_version('1.0.0post1')
+    assert digit_version('v1') == (1, 0, 0, 0, 0, 0)
+    assert digit_version('v1.1.5') == (1, 1, 5, 0, 0, 0)
+    with pytest.raises(AssertionError):
+        digit_version('a')
+    with pytest.raises(AssertionError):
+        digit_version('1x')
+    with pytest.raises(AssertionError):
+        digit_version('1.x')
 
 
 def test_parse_version_info():
-    assert parse_version_info('0.2.16') == (0, 2, 16)
-    assert parse_version_info('1.2.3') == (1, 2, 3)
-    assert parse_version_info('1.2.3rc0') == (1, 2, 3, 'rc0')
-    assert parse_version_info('1.2.3rc1') == (1, 2, 3, 'rc1')
-    assert parse_version_info('1.0rc0') == (1, 0, 'rc0')
+    assert parse_version_info('0.2.16') == (0, 2, 16, 0, 0, 0)
+    assert parse_version_info('1.2.3') == (1, 2, 3, 0, 0, 0)
+    assert parse_version_info('1.2.3rc0') == (1, 2, 3, 0, 'rc', 0)
+    assert parse_version_info('1.2.3rc1') == (1, 2, 3, 0, 'rc', 1)
+    assert parse_version_info('1.0rc0') == (1, 0, 0, 0, 'rc', 0)
 
 
 def _mock_cmd_success(cmd):