leandron commented on a change in pull request #6366:
URL: https://github.com/apache/incubator-tvm/pull/6366#discussion_r481294810
##########
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:
Yep. Agree with @comaniac
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