[Fix]: parse scales of list in PyTorch==1.7.0 (#451 in MMPose) (#815)

* modify symbolic

* add comments

mmcv/onnx/onnx_utils/symbolic_helper.py

@@ -39,6 +39,8 @@ def _parse_arg(value, desc):
             return tval
         elif desc == 'is':
             return [int(v) for v in tval]
+        elif desc == 'fs':
+            return [float(v) for v in tval]
         else:
             raise RuntimeError(
                 "ONNX symbolic doesn't know to interpret Constant node")
@@ -226,21 +228,18 @@ def _interpolate_size_to_scales(g, input, output_size, dim):
 def _interpolate_get_scales_if_available(g, scales):
     if len(scales) == 0:
         return None
-    available_scales = _maybe_get_const(scales[0], 'f') != -1 and not _is_none(
-        scales[0])
+    available_scales = _maybe_get_const(scales[0],
+                                        'fs') != -1 and not _is_none(scales[0])
 
     if not available_scales:
         return None
 
-    scales_list = []
-    for scale in scales:
-        unsqueezed_scale = _unsqueeze_helper(g, scale, 0)
-        # ONNX only supports float for the scales. double -> float.
-        unsqueezed_scale = g.op(
-            'Cast', unsqueezed_scale, to_i=cast_pytorch_to_onnx['Float'])
-        scales_list.append(unsqueezed_scale)
     offsets = g.op('Constant', value_t=torch.ones(2, dtype=torch.float32))
-    scales = g.op('Concat', offsets, *scales_list, axis_i=0)
+    scales_list = g.op(
+        'Constant', value_t=torch.tensor(_maybe_get_const(scales[0], 'fs')))
+    # modify to support PyTorch==1.7.0
+    # https://github.com/pytorch/pytorch/blob/75ee5756715e7161314ce037474843b68f69fc04/torch/onnx/symbolic_helper.py#L375 # noqa: E501
+    scales = g.op('Concat', offsets, scales_list, axis_i=0)
     return scales