ONNX export: Instance Normalization

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

@@ -843,6 +843,41 @@ def convert_identity(node, **kwargs):
     )
     return [node]
 
+@mx_op.register("InstanceNorm")
+def convert_instancenorm(node, **kwargs):
+    """Map MXNet's InstanceNorm operator attributes to onnx's InstanceNormalization operator
+    based on the input node's attributes and return the created node.
+    """
+    onnx = import_onnx_modules()
+    name = node["name"]
+    proc_nodes = kwargs["proc_nodes"]
+    inputs = node["inputs"]
+    inputs = node["inputs"]
+
+    input_node_id = kwargs["index_lookup"][inputs[0][0]]
+    gamma_node_id = kwargs["index_lookup"][inputs[1][0]]
+    beta_node_id = kwargs["index_lookup"][inputs[2][0]]
+
+    proc_nodes = kwargs["proc_nodes"]
+    input_node = proc_nodes[input_node_id]
+    gamma_node = proc_nodes[gamma_node_id]
+    beta_node = proc_nodes[beta_node_id]
+
+    input_name = input_node.name
+    gamma_name = gamma_node.name
+    beta_name = beta_node.name
+
+    attrs = node.get("attrs", {})
+    eps = float(attrs.get("eps", 0.001))
+
+    node = onnx.helper.make_node(
+        'InstanceNormalization',
+        inputs=[input_name, gamma_name, beta_name],
+        outputs=[name],
+        name=name,
+        epsilon=eps)
+
+    return [node]
 
 @mx_op.register("LeakyReLU")
 def convert_leakyrelu(node, **kwargs):

tests/python-pytest/onnx/export/onnx_backend_test.py

@@ -92,7 +92,8 @@
     'test_operator_permute2',
     'test_clip',
     'test_cast',
-    'test_hardsigmoid'
+    'test_hardsigmoid',
+    'test_instancenorm'
     ]
 
 BASIC_MODEL_TESTS = [