deal with comments

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -740,25 +740,22 @@ class OpSet9():
     def Unsqueeze(self, node):
         val_x = self.graph.get_input_node(node, idx=0, copy=True)
         axes = node.get_attr('axes')
-        if axes is None:
-            axes = self.graph.get_input_node(node, idx=1, copy=True)
-            axes = _const_weight_or_none(axes)
-        if len(val_x.out_shapes[0]) == 0 and len(axes) == 1 and axes[0] == 0:
-            if node.name:
+        if axes is not None:
+            if len(val_x.out_shapes[0]) == 0 and len(axes) == 1 and axes[
+                    0] == 0:
                 self.paddle_graph.add_layer(
                     'paddle.reshape',
                     inputs={"x": val_x.name},
                     outputs=[node.name],
                     shape=[1])
             else:
-            if isinstance(axes, list) or isinstance(axes, tuple) or isinstance(
-                    axes, np.ndarray):
                 self.paddle_graph.add_layer(
                     'paddle.unsqueeze',
                     inputs={"x": val_x.name},
                     axis=axes,
                     outputs=[node.name])
         else:
+            axes = self.graph.get_input_node(node, idx=1, copy=True)
             self.paddle_graph.add_layer(
                 'paddle.unsqueeze',
                 inputs={"x": val_x.name,
@@ -896,7 +893,7 @@ class OpSet9():
     def Gather(self, node):
         val_x = self.graph.get_input_node(node, idx=0, copy=True)
         indices = self.graph.get_input_node(node, idx=1, copy=True)
-        indices_values = _const_weight_or_none(indices)
+        indices_values = _const_weight_or_none(indices, necessary=True)
         if isinstance(indices_values, np.ndarray):
             indices_values = indices_values.tolist()
         indices_shape = indices.out_shapes[0]