fixed for ci

x2paddle/op_mapper/onnx2paddle/onnx_custom_layer/roi_align.py

@@ -21,18 +21,13 @@ from paddle.common_ops_import import Variable, LayerHelper, check_variable_and_d
 @paddle.jit.not_to_static
 def roi_align(input,
               rois,
-              output_size,
+              pooled_height,
+              pooled_width,
               spatial_scale=1.0,
               sampling_ratio=-1,
               rois_num=None,
               aligned=True,
               name=None):
-    check_type(output_size, 'output_size', (int, tuple), 'roi_align')
-    if isinstance(output_size, int):
-        output_size = (output_size, output_size)
-
-    pooled_height, pooled_width = output_size
-
     if in_dynamic_mode():
         assert rois_num is not None, "rois_num should not be None in dygraph mode."
         align_out = _C_ops.roi_align(
@@ -71,15 +66,15 @@ def roi_align(input,
 
 class ROIAlign(object):
     def __init__(self, pooled_height, pooled_width, spatial_scale,
-                 sampling_ratio, rois_num):
+                 sampling_ratio):
         self.roialign_layer_attrs = {
             "pooled_height": pooled_height,
             "pooled_width": pooled_width,
             "spatial_scale": spatial_scale,
             'sampling_ratio': sampling_ratio,
-            'rois_num': rois_num,
         }
 
-    def __call__(self, x0, x1):
-        out = roi_align(input=x0, rois=x1, **self.roialign_layer_attrs)
+    def __call__(self, x0, x1, x2):
+        out = roi_align(
+            input=x0, rois=x1, rois_num=x2, **self.roialign_layer_attrs)
         return out

x2paddle/op_mapper/onnx2paddle/opset9/opset.py

@@ -538,12 +538,14 @@ class OpSet9():
             'pooled_width': pooled_width,
             'spatial_scale': spatial_scale,
             'sampling_ratio': sampling_ratio,
-            'rois_num': val_rois_num,
         }
         self.paddle_graph.add_layer(
             'custom_layer:ROIAlign',
-            inputs={'input': val_x.name,
-                    'rois': val_rois.name},
+            inputs={
+                'input': val_x.name,
+                'rois': val_rois.name,
+                'rois_num': val_rois_num
+            },
             outputs=[node.name],
             **layer_attrs)