fix mmcv ci for parrots (#782)

* fix mmcv ci for parrots

* fix mmcv ci

* fix lint

mmcv/ops/roi_align.py

@@ -4,7 +4,6 @@ from torch.autograd import Function
 from torch.autograd.function import once_differentiable
 from torch.nn.modules.utils import _pair
 
-from ..onnx import is_custom_op_loaded
 from ..utils import deprecated_api_warning, ext_loader
 
 ext_module = ext_loader.load_ext('_ext',
@@ -16,6 +15,7 @@ class RoIAlignFunction(Function):
     @staticmethod
     def symbolic(g, input, rois, output_size, spatial_scale, sampling_ratio,
                  pool_mode, aligned):
+        from ..onnx import is_custom_op_loaded
         has_custom_op = is_custom_op_loaded()
         if has_custom_op:
             return g.op(

tests/test_runner/test_checkpoint.py

@@ -3,6 +3,7 @@ from collections import OrderedDict
 from unittest.mock import MagicMock
 
 import pytest
+import torch
 import torch.nn as nn
 from torch.nn.parallel import DataParallel
 
@@ -47,11 +48,19 @@ def assert_tensor_equal(tensor_a, tensor_b):
 
 
 def test_get_state_dict():
-    state_dict_keys = set([
-        'block.conv.weight', 'block.conv.bias', 'block.norm.weight',
-        'block.norm.bias', 'block.norm.running_mean', 'block.norm.running_var',
-        'block.norm.num_batches_tracked', 'conv.weight', 'conv.bias'
-    ])
+    if torch.__version__ == 'parrots':
+        state_dict_keys = set([
+            'block.conv.weight', 'block.conv.bias', 'block.norm.weight',
+            'block.norm.bias', 'block.norm.running_mean',
+            'block.norm.running_var', 'conv.weight', 'conv.bias'
+        ])
+    else:
+        state_dict_keys = set([
+            'block.conv.weight', 'block.conv.bias', 'block.norm.weight',
+            'block.norm.bias', 'block.norm.running_mean',
+            'block.norm.running_var', 'block.norm.num_batches_tracked',
+            'conv.weight', 'conv.bias'
+        ])
 
     model = Model()
     state_dict = get_state_dict(model)
@@ -68,8 +77,9 @@ def test_get_state_dict():
                         model.block.norm.running_mean)
     assert_tensor_equal(state_dict['block.norm.running_var'],
                         model.block.norm.running_var)
-    assert_tensor_equal(state_dict['block.norm.num_batches_tracked'],
-                        model.block.norm.num_batches_tracked)
+    if torch.__version__ != 'parrots':
+        assert_tensor_equal(state_dict['block.norm.num_batches_tracked'],
+                            model.block.norm.num_batches_tracked)
     assert_tensor_equal(state_dict['conv.weight'], model.conv.weight)
     assert_tensor_equal(state_dict['conv.bias'], model.conv.bias)
 
@@ -89,8 +99,10 @@ def test_get_state_dict():
                         wrapped_model.module.block.norm.running_mean)
     assert_tensor_equal(state_dict['block.norm.running_var'],
                         wrapped_model.module.block.norm.running_var)
-    assert_tensor_equal(state_dict['block.norm.num_batches_tracked'],
-                        wrapped_model.module.block.norm.num_batches_tracked)
+    if torch.__version__ != 'parrots':
+        assert_tensor_equal(
+            state_dict['block.norm.num_batches_tracked'],
+            wrapped_model.module.block.norm.num_batches_tracked)
     assert_tensor_equal(state_dict['conv.weight'],
                         wrapped_model.module.conv.weight)
     assert_tensor_equal(state_dict['conv.bias'],
@@ -115,9 +127,10 @@ def test_get_state_dict():
                         wrapped_model.module.block.module.norm.running_mean)
     assert_tensor_equal(state_dict['block.norm.running_var'],
                         wrapped_model.module.block.module.norm.running_var)
-    assert_tensor_equal(
-        state_dict['block.norm.num_batches_tracked'],
-        wrapped_model.module.block.module.norm.num_batches_tracked)
+    if torch.__version__ != 'parrots':
+        assert_tensor_equal(
+            state_dict['block.norm.num_batches_tracked'],
+            wrapped_model.module.block.module.norm.num_batches_tracked)
     assert_tensor_equal(state_dict['conv.weight'],
                         wrapped_model.module.conv.module.weight)
     assert_tensor_equal(state_dict['conv.bias'],