fix pooling_convention warning when convert model to onnx

python/mxnet/contrib/onnx/mx2onnx/_op_translations.py

@@ -759,12 +759,13 @@ def convert_pooling(node, **kwargs):
     p_value = attrs.get('p_value', 'None')
 
     pooling_convention = attrs.get('pooling_convention', 'valid')
-
+    ceil_mode = False
     if pooling_convention == 'full':
-        pooling_warning = "Pooling: ONNX currently doesn't support pooling_convention. " \
-                          "This might lead to shape or accuracy issues. " \
-                          "https://github.com/onnx/onnx/issues/549"
-
+        if onnx.__version__ < "1.5.0":
+            pooling_warning = "Pooling: ONNX lower than 1.5.0 doesn't support pooling_convention. " \
+                              "This might lead to shape or accuracy issues. " \
+                              "https://github.com/onnx/onnx/issues/549"
+        ceil_mode = True
         logging.warning(pooling_warning)
 
     pad_dims = list(parse_helper(attrs, "pad", [0, 0]))
@@ -805,15 +806,27 @@ def convert_pooling(node, **kwargs):
                 name=name
             )
         else:
-            node = onnx.helper.make_node(
-                pool_types[pool_type],
-                input_nodes,  # input
-                [name],
-                kernel_shape=kernel,
-                pads=pad_dims,
-                strides=stride,
-                name=name
-            )
+            if onnx.__version__ >= "1.5.0":
+                node = onnx.helper.make_node(
+                    pool_types[pool_type],
+                    input_nodes,  # input
+                    [name],
+                    kernel_shape=kernel,
+                    pads=pad_dims,
+                    strides=stride,
+                    name=name,
+                    ceil_mode=ceil_mode
+                )
+            else:
+                node = onnx.helper.make_node(
+                    pool_types[pool_type],
+                    input_nodes,  # input
+                    [name],
+                    kernel_shape=kernel,
+                    pads=pad_dims,
+                    strides=stride,
+                    name=name
+                )
 
     return [node]