Merge pull request #339 from Channingss/prior_box

support Reisze opset 11

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -332,10 +332,37 @@ class OpSet9():
 
     def _interpolate(self, node):
         val_x = self.graph.get_input_node(node, idx=0, copy=True)
+        inputs = {'input': val_x}
         if node.layer_type == 'Resize':
+            if len(node.layer.input) == 2:
+                # opset 10
+                val_scales = self.graph.get_input_node(node, idx=1, copy=True)
+                inputs['scale'] = val_scales
+            elif len(node.layer.input) == 3:
+                # opset 11
                 val_scales = self.graph.get_input_node(node, idx=2, copy=True)
+                inputs['scale'] = val_scales
+            elif len(node.layer.input) == 4:
+                # opset 11
+                val_sizes = self.graph.get_input_node(node, idx=3, copy=True)
+                var_nc, var_hw = val_sizes.layer_name + '_nc', val_sizes.layer_name + '_hw'
+                node.fluid_code.add_layer(
+                    'split',
+                    inputs=val_sizes,
+                    output=var_nc + ',' + var_hw,
+                    param_attr={
+                        'dim': 0,
+                        'num_or_sections': [2, 2],
+                    })
+                node.fluid_code.add_layer(
+                    "cast",
+                    inputs=var_hw,
+                    output=var_hw,
+                    param_attr={'dtype': string('int32')})
+                inputs['out_shape'] = var_hw
         elif node.layer_type == 'Upsample':
             val_scales = self.graph.get_input_node(node, idx=1, copy=True)
+            inputs['scale'] = val_scales
 
         attr = {'name': string(node.layer_name)}
         mode = node.get_attr('mode', 'nearest')
@@ -345,13 +372,8 @@ class OpSet9():
                 'Warnning: paddle not support op:resize wiht mode: linear, we use bilinear replace linear'
             )
             fluid_op = 'resize_bilinear'
-
         node.fluid_code.add_layer(
-            fluid_op,
-            inputs={'input': val_x,
-                    'scale': val_scales},
-            output=node,
-            param_attr=attr)
+            fluid_op, inputs=inputs, output=node, param_attr=attr)
 
     @print_mapping_info
     def RoiAlign(self, node):
@@ -497,7 +519,6 @@ class OpSet9():
                             'attribute "shape" of %s not inferred, '
                             'using value as 1-D tensor may lead to fails',
                             val_output.layer_name, val_output.layer_name)
-
         if len(value) == 1:
             value = value.tolist()
             shape = [1]