share torch version (#343)

mmcv/parallel/distributed.py

@@ -3,6 +3,7 @@ import torch
 from torch.nn.parallel.distributed import (DistributedDataParallel,
                                            _find_tensors)
 
+from mmcv.utils import TORCH_VERSION
 from .scatter_gather import scatter_kwargs
 
 
@@ -47,7 +48,7 @@ class MMDistributedDataParallel(DistributedDataParallel):
             else:
                 self.reducer.prepare_for_backward([])
         else:
-            if torch.__version__ > '1.2':
+            if TORCH_VERSION > '1.2':
                 self.require_forward_param_sync = False
         return output
 
@@ -79,6 +80,6 @@ class MMDistributedDataParallel(DistributedDataParallel):
             else:
                 self.reducer.prepare_for_backward([])
         else:
-            if torch.__version__ > '1.2':
+            if TORCH_VERSION > '1.2':
                 self.require_forward_param_sync = False
         return output

mmcv/parallel/distributed_deprecated.py

@@ -5,6 +5,7 @@ import torch.nn as nn
 from torch._utils import (_flatten_dense_tensors, _take_tensors,
                           _unflatten_dense_tensors)
 
+from mmcv.utils import TORCH_VERSION
 from .scatter_gather import scatter_kwargs
 
 
@@ -37,7 +38,7 @@ class MMDistributedDataParallel(nn.Module):
             self._dist_broadcast_coalesced(module_states,
                                            self.broadcast_bucket_size)
         if self.broadcast_buffers:
-            if torch.__version__ < '1.0':
+            if TORCH_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

@@ -7,6 +7,8 @@ import torch
 import torch.distributed as dist
 import torch.multiprocessing as mp
 
+from mmcv.utils import TORCH_VERSION
+
 
 def init_dist(launcher, backend='nccl', **kwargs):
     if mp.get_start_method(allow_none=True) is None:
@@ -49,7 +51,7 @@ def _init_dist_slurm(backend, port=29500):
 
 
 def get_dist_info():
-    if torch.__version__ < '1.0':
+    if TORCH_VERSION < '1.0':
         initialized = dist._initialized
     else:
         if dist.is_available():

mmcv/runner/hooks/logger/tensorboard.py

 # Copyright (c) Open-MMLab. All rights reserved.
 import os.path as osp
 
-import torch
-
+from mmcv.utils import TORCH_VERSION
 from ...dist_utils import master_only
 from ..hook import HOOKS
 from .base import LoggerHook
@@ -22,7 +21,7 @@ class TensorboardLoggerHook(LoggerHook):
 
     @master_only
     def before_run(self, runner):
-        if torch.__version__ < '1.1' or torch.__version__ == 'parrots':
+        if TORCH_VERSION < '1.1' or TORCH_VERSION == 'parrots':
             try:
                 from tensorboardX import SummaryWriter
             except ImportError:

mmcv/utils/__init__.py

 # Copyright (c) Open-MMLab. All rights reserved.
 from .config import Config, ConfigDict, DictAction
+from .env import TORCH_VERSION
 from .logging import get_logger, print_log
 from .misc import (check_prerequisites, concat_list, is_list_of, is_seq_of,
                    is_str, is_tuple_of, iter_cast, list_cast,
@@ -29,5 +30,6 @@ __all__ = [
     'CUDA_HOME', 'SyncBatchNorm', '_AdaptiveAvgPoolNd', '_AdaptiveMaxPoolNd',
     '_AvgPoolNd', '_BatchNorm', '_ConvNd', '_ConvTransposeMixin',
     '_InstanceNorm', '_MaxPoolNd', 'get_build_config', 'BuildExtension',
-    'CppExtension', 'CUDAExtension', 'DataLoader', 'PoolDataLoader'
+    'CppExtension', 'CUDAExtension', 'DataLoader', 'PoolDataLoader',
+    'TORCH_VERSION'
 ]

mmcv/utils/env.py

+# This file holding some environment constant for sharing by other files
+import torch
+
+TORCH_VERSION = torch.__version__

mmcv/utils/parrots_wrapper.py

@@ -2,9 +2,11 @@ from functools import partial
 
 import torch
 
+from .env import TORCH_VERSION
+
 
 def _get_cuda_home():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.utils.build_extension import CUDA_HOME
     else:
         from torch.utils.cpp_extension import CUDA_HOME
@@ -12,7 +14,7 @@ def _get_cuda_home():
 
 
 def get_build_config():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.config import get_build_info
         return get_build_info()
     else:
@@ -20,7 +22,7 @@ def get_build_config():
 
 
 def _get_conv():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.conv import _ConvNd, _ConvTransposeMixin
     else:
         from torch.nn.modules.conv import _ConvNd, _ConvTransposeMixin
@@ -28,7 +30,7 @@ def _get_conv():
 
 
 def _get_dataloader():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from torch.utils.data import DataLoader, PoolDataLoader
     else:
         from torch.utils.data import DataLoader
@@ -37,7 +39,7 @@ def _get_dataloader():
 
 
 def _get_extension():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.utils.build_extension import BuildExtension, Extension
         CppExtension = partial(Extension, cuda=False)
         CUDAExtension = partial(Extension, cuda=True)
@@ -48,7 +50,7 @@ def _get_extension():
 
 
 def _get_pool():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.pool import (_AdaptiveAvgPoolNd,
                                              _AdaptiveMaxPoolNd, _AvgPoolNd,
                                              _MaxPoolNd)
@@ -60,7 +62,7 @@ def _get_pool():
 
 
 def _get_norm():
-    if torch.__version__ == 'parrots':
+    if TORCH_VERSION == 'parrots':
         from parrots.nn.modules.batchnorm import _BatchNorm, _InstanceNorm
         SyncBatchNorm_ = torch.nn.SyncBatchNorm2d
     else:
@@ -81,11 +83,11 @@ _AdaptiveAvgPoolNd, _AdaptiveMaxPoolNd, _AvgPoolNd, _MaxPoolNd = _get_pool()
 class SyncBatchNorm(SyncBatchNorm_):
 
     def _specify_ddp_gpu_num(self, gpu_size):
-        if torch.__version__ != 'parrots':
+        if TORCH_VERSION != 'parrots':
             super()._specify_ddp_gpu_num(gpu_size)
 
     def _check_input_dim(self, input):
-        if torch.__version__ == 'parrots':
+        if TORCH_VERSION == 'parrots':
             if input.dim() < 2:
                 raise ValueError(
                     f'expected at least 2D input (got {input.dim()}D input)')