Add new parrots extension implementation for all ops (#794)

* delete all parrots file
add bbox_overlaps new parrots op impl

* support first new impl parrts op (bbox_overlaps)(success test)

* add box_iou_rotated op, test succeed

* add carafe and carafe_naive op, test succeed (one parrots bug need fix)

* add cc_attention op, test success

* add corner_pool op, test success

* add parrots op deform_conv, test success

* add deform_roi_pool op, test success (but has question)

* add focal loss op, test success (gradcheck)

* add masked_conv2d op, test success

* add modulated_deform_conv op, test success

* add nms and nms_rotated op, test success

* add psamask op, test success

* add roi_align op, test_success

* add roi_pool op, test success

* add sync_bn op, test success

* add tin_shift op, test success

* fix test_deform_roi_pool, add parrots test

* skip test_onnx because parrots does not support onnx

* fix c++ lint

* fix python lint

* fix python lint

tests/test_ops/test_nms.py

@@ -140,20 +140,20 @@ class Testnms(object):
 
         nms_cfg = dict(type='nms', iou_threshold=0.7)
         boxes, keep = batched_nms(
-            results['boxes'],
-            results['scores'],
-            results['idxs'],
+            torch.from_numpy(results['boxes']),
+            torch.from_numpy(results['scores']),
+            torch.from_numpy(results['idxs']),
             nms_cfg,
             class_agnostic=False)
 
         nms_cfg.update(split_thr=100)
         seq_boxes, seq_keep = batched_nms(
-            results['boxes'],
-            results['scores'],
-            results['idxs'],
+            torch.from_numpy(results['boxes']),
+            torch.from_numpy(results['scores']),
+            torch.from_numpy(results['idxs']),
             nms_cfg,
             class_agnostic=False)
 
         assert torch.equal(keep, seq_keep)
         assert torch.equal(boxes, seq_boxes)
-        assert torch.equal(keep, results['keep'])
+        assert torch.equal(keep, torch.from_numpy(results['keep']))

tests/test_ops/test_onnx.py

@@ -24,6 +24,8 @@ class WrapFunction(nn.Module):
 
 
 def test_nms():
+    if torch.__version__ == 'parrots':
+        pytest.skip('onnx is not supported in parrots directly')
     from mmcv.ops import get_onnxruntime_op_path, nms
     np_boxes = np.array([[6.0, 3.0, 8.0, 7.0], [3.0, 6.0, 9.0, 11.0],
                          [3.0, 7.0, 10.0, 12.0], [1.0, 4.0, 13.0, 7.0]],
@@ -70,6 +72,8 @@ def test_nms():
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason='test requires GPU')
 def test_softnms():
+    if torch.__version__ == 'parrots':
+        pytest.skip('onnx is not supported in parrots directly')
     from mmcv.ops import get_onnxruntime_op_path, soft_nms
 
     # only support pytorch >= 1.7.0
@@ -144,6 +148,8 @@ def test_softnms():
 
 
 def test_roialign():
+    if torch.__version__ == 'parrots':
+        pytest.skip('onnx is not supported in parrots directly')
     try:
         from mmcv.ops import roi_align
         from mmcv.ops import get_onnxruntime_op_path
@@ -216,6 +222,8 @@ def test_roialign():
 
 @pytest.mark.skipif(not torch.cuda.is_available(), reason='test requires GPU')
 def test_roipool():
+    if torch.__version__ == 'parrots':
+        pytest.skip('onnx is not supported in parrots directly')
     from mmcv.ops import roi_pool
 
     # roi pool config
@@ -278,6 +286,8 @@ def test_roipool():
 
 
 def test_simplify():
+    if torch.__version__ == 'parrots':
+        pytest.skip('onnx is not supported in parrots directly')
     from mmcv.onnx.simplify import simplify
 
     # only support PyTorch >= 1.5.0