Avoid bc-breaking of importing `MultiScaleDeformableAttention` (#1100)

* avoid bc-breaking

* fix function name

* fix typo

* fix import

* add import warning

* remove wapper

* remove unitest

* add dep warning

* add dep warning

mmcv/cnn/bricks/transformer.py

@@ -12,6 +12,22 @@ from .drop import build_dropout
 from .registry import (ATTENTION, FEEDFORWARD_NETWORK, POSITIONAL_ENCODING,
                        TRANSFORMER_LAYER, TRANSFORMER_LAYER_SEQUENCE)
 
+# Avoid BC-breaking of importing MultiScaleDeformableAttention from this file
+try:
+    from mmcv.ops.multi_scale_deform_attn import MultiScaleDeformableAttention  # noqa F401
+    warnings.warn(
+        ImportWarning(
+            '``MultiScaleDeformableAttention`` has been moved to '
+            '``mmcv.ops.multi_scale_deform_attn``, please change original path '  # noqa E501
+            '``from mmcv.cnn.bricks.transformer import MultiScaleDeformableAttention`` '  # noqa E501
+            'to ``from mmcv.ops.multi_scale_deform_attn import MultiScaleDeformableAttention`` '  # noqa E501
+        ))
+
+except ImportError:
+    warnings.warn('Fail to import ``MultiScaleDeformableAttention`` from '
+                  '``mmcv.ops.multi_scale_deform_attn``, '
+                  'You should install ``mmcv-full`` if you need this module. ')
+
 
 def build_positional_encoding(cfg, default_args=None):
     """Builder for Position Encoding."""
@@ -56,9 +72,9 @@ class MultiheadAttention(BaseModule):
             when adding the shortcut.
         init_cfg (obj:`mmcv.ConfigDict`): The Config for initialization.
             Default: None.
-        batch_first (bool): Key, Query and Value are shape of
-            (batch, n, embed_dim)
-            or (n, batch, embed_dim). Default to False.
+        batch_first (bool): When it is True,  Key, Query and Value are shape of
+            (batch, n, embed_dim), otherwise (n, batch, embed_dim).
+             Default to False.
     """
 
     def __init__(self,
@@ -88,10 +104,12 @@ class MultiheadAttention(BaseModule):
         if self.batch_first:
 
             def _bnc_to_nbc(forward):
-                """This function can adjust the shape of dataflow('key',
-                'query', 'value') from batch_first (batch, num_query,
-                embed_dims) to num_query_first (num_query ,batch,
-                embed_dims)."""
+                """Because the dataflow('key', 'query', 'value') of
+                ``torch.nn.MultiheadAttention`` is (num_query, batch,
+                embed_dims), We should adjust the shape of dataflow from
+                batch_first (batch, num_query, embed_dims) to num_query_first
+                (num_query ,batch, embed_dims), and recover ``attn_output``
+                from num_query_first to batch_first."""
 
                 def forward_wrapper(**kwargs):
                     convert_keys = ('key', 'query', 'value')