[GitHub] [incubator-tvm] leandron commented on a change in pull request #6366: [TARGET] Add layout_transform, clip and expand_dims in onnx converter

[GitBox <gi...@apache.org>]

leandron commented on a change in pull request #6366:
URL: https://github.com/apache/incubator-tvm/pull/6366#discussion_r481235312



##########
File path: python/tvm/contrib/target/onnx.py
##########
@@ -510,6 +510,99 @@ def convert(cls, node_entry, model_container, node_dict):
                                            axis=axis)
         model_container.add_nodes([slice_node])
 
+class LayoutTransform(OpConverter):
+    """ Operator converter for Layouttransform
+    """
+
+    @classmethod
+    def convert_attributes(cls, attrs):
+        src_layout = attrs.get_str("src_layout")
+        dst_layout = attrs.get_str("dst_layout")
+
+        perm = [src_layout.index(c) for c in dst_layout]
+        return {'perm': tuple(perm)}
+
+    @classmethod
+    def convert(cls, node_entry, model_container, node_dict):
+        attrs = cls.convert_attributes(node_entry['relay_node'].attrs)
+        onnx_node = onnx.helper.make_node("Transpose",
+                                          node_entry['input_names'],
+                                          node_entry['output_names'],
+                                          **attrs)
+        model_container.add_nodes([onnx_node])
+
+class Clip(OpConverter):
+    """ Operator converter for Clip.
+    """
+
+    @classmethod
+    def convert_attributes(cls, attrs):
+        return {
+            'min': attrs.a_min,
+            'max': attrs.a_max
+        }
+
+    @classmethod
+    def convert(cls, node_entry, model_container, node_dict):
+        attrs = cls.convert_attributes(node_entry['relay_node'].attrs)
+
+        name = node_entry['name']
+
+        def _add_input(val, input_name):
+            val_arr = numpy.asarray(val).astype(numpy.float32)
+            input_name = '{}_{}'.format(name, input_name)
+            add_input(val_arr, input_name, model_container)
+            return input_name
+
+        input_names = []
+        input_names.append(_add_input(attrs['min'], 'min'))
+        input_names.append(_add_input(attrs['max'], 'max'))
+
+        input_names = [node_entry['input_names'][0]] + input_names
+
+        node = onnx.helper.make_node(cls.__name__, input_names, node_entry['output_names'])
+        model_container.add_nodes([node])
+
+class Expand(OpConverter):
+    """ Operator converter for Expand_dims.
+    """
+
+    @classmethod
+    def convert_attributes(cls, attrs):
+        return {
+            'axis': attrs.axis,
+            'num_newaxis': attrs.num_newaxis
+        }
+
+    @classmethod
+    def convert(cls, node_entry, model_container, node_dict):
+        attrs = cls.convert_attributes(node_entry['relay_node'].attrs)
+
+        name = node_entry['name']
+
+        def _add_input(val, input_name):
+            val_arr = numpy.asarray(val).astype(numpy.int64)
+            input_name = '{}_{}'.format(name, input_name)
+            add_input(val_arr, input_name, model_container)
+            return input_name

Review comment:
       It seems this function is now repeated quite a few times in `OpConverter` subclasses. Wouldn't be interesting to make it a common implementation, provided by `OpConverter` itself?




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