From 77815af04dfbb4eec7bb613435bd00972697b55c Mon Sep 17 00:00:00 2001
From: vandanavk <vandana268@gmail.com>
Date: Tue, 30 Oct 2018 13:46:50 -0700
Subject: [PATCH] ONNX export: Add helper for creating node

---
 .../contrib/onnx/mx2onnx/_op_translations.py  | 355 +++---------------
 1 file changed, 45 insertions(+), 310 deletions(-)

diff --git a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
index 32c9494c2e9a..11e75d9a6000 100644
--- a/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
+++ b/python/mxnet/contrib/onnx/mx2onnx/_op_translations.py
@@ -145,6 +145,19 @@ def get_inputs(node, kwargs):
 
     return name, input_nodes, attrs
 
+def create_basic_op_node(op_name, node, kwargs):
+    """Helper function to create a basic operator
+    node that doesn't contain op specific attrs"""
+    name, input_nodes, _ = get_inputs(node, kwargs)
+
+    node = onnx.helper.make_node(
+        op_name,
+        input_nodes,
+        [name],
+        name=name
+    )
+    return [node]
+
 @mx_op.register("null")
 def convert_weights_and_inputs(node, **kwargs):
     """Helper function to convert weights and inputs.
@@ -280,105 +293,49 @@ def convert_tanh(node, **kwargs):
     """Map MXNet's tanh operator attributes to onnx's Tanh operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Tanh',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Tanh', node, kwargs)
 
 @mx_op.register("cos")
 def convert_cos(node, **kwargs):
     """Map MXNet's cos operator attributes to onnx's Cos operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Cos',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Cos', node, kwargs)
 
 @mx_op.register("sin")
 def convert_sin(node, **kwargs):
     """Map MXNet's sin operator attributes to onnx's Sin operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Sin',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Sin', node, kwargs)
 
 @mx_op.register("tan")
 def convert_tan(node, **kwargs):
     """Map MXNet's tan operator attributes to onnx's tan operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Tan',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Tan', node, kwargs)
 
 @mx_op.register("arccos")
 def convert_acos(node, **kwargs):
     """Map MXNet's acos operator attributes to onnx's acos operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Acos',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Acos', node, kwargs)
 
 @mx_op.register("arcsin")
 def convert_asin(node, **kwargs):
     """Map MXNet's asin operator attributes to onnx's asin operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Asin',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Asin', node, kwargs)
 
 @mx_op.register("arctan")
 def convert_atan(node, **kwargs):
     """Map MXNet's atan operator attributes to onnx's atan operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Atan',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Atan', node, kwargs)
 
 #Basic neural network functions
 @mx_op.register("sigmoid")
@@ -386,31 +343,14 @@ def convert_sigmoid(node, **kwargs):
     """Map MXNet's sigmoid operator attributes to onnx's Sigmoid operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Sigmoid',
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Sigmoid', node, kwargs)
 
 @mx_op.register("relu")
 def convert_relu(node, **kwargs):
     """Map MXNet's relu operator attributes to onnx's Relu operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Relu',
-        input_nodes,
-        [name],
-        name=name
-    )
-
-    return [node]
+    return create_basic_op_node('Relu', node, kwargs)
 
 @mx_op.register("Activation")
 def convert_activation(node, **kwargs):
@@ -674,31 +614,14 @@ def convert_exp(node, **kwargs):
     """Map MXNet's exp operator attributes to onnx's Exp operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Exp",
-        input_nodes,
-        [name],
-        name=name,
-    )
-    return [node]
-
+    return create_basic_op_node('Exp', node, kwargs)
 
 @mx_op.register("_copy")
 def convert_identity(node, **kwargs):
     """Map MXNet's _copy operator attributes to onnx's Identity operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Identity",
-        input_nodes,
-        [name],
-        name=name,
-    )
-    return [node]
+    return create_basic_op_node('Identity', node, kwargs)
 
 
 @mx_op.register("LeakyReLU")
@@ -893,15 +816,7 @@ def convert_flatten(node, **kwargs):
     """Map MXNet's Flatten operator attributes to onnx's Flatten operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    flatten_node = onnx.helper.make_node(
-        "Flatten",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [flatten_node]
+    return create_basic_op_node('Flatten', node, kwargs)
 
 @mx_op.register("clip")
 def convert_clip(node, **kwargs):
@@ -1077,16 +992,7 @@ def convert_maximum(node, **kwargs):
     """Map MXNet's _maximum operator attributes to onnx's Max operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Max',
-        inputs=input_nodes,
-        outputs=[name],
-        name=name,
-    )
-
-    return [node]
+    return create_basic_op_node('Max', node, kwargs)
 
 
 @mx_op.register("_minimum")
@@ -1094,17 +1000,7 @@ def convert_minimum(node, **kwargs):
     """Map MXNet's _minimum operator attributes to onnx's Min operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        'Min',
-        inputs=input_nodes,
-        outputs=[name],
-        name=name,
-    )
-
-    return [node]
-
+    return create_basic_op_node('Min', node, kwargs)
 
 @mx_op.register("min")
 def convert_min(node, **kwargs):
@@ -1252,16 +1148,7 @@ def convert_elementwise_add(node, **kwargs):
     """Map MXNet's elemwise_add operator attributes to onnx's Add operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    add_node = onnx.helper.make_node(
-        "Add",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [add_node]
+    return create_basic_op_node('Add', node, kwargs)
 
 
 @mx_op.register("broadcast_add")
@@ -1269,16 +1156,7 @@ def covert_broadcast_add(node, **kwargs):
     """Map MXNet's broadcast_add operator attributes to onnx's Add operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    add_node = onnx.helper.make_node(
-        "Add",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [add_node]
+    return create_basic_op_node('Add', node, kwargs)
 
 
 @mx_op.register("elemwise_sub")
@@ -1286,149 +1164,63 @@ def convert_elementwise_sub(node, **kwargs):
     """Map MXNet's elemwise_sub operator attributes to onnx's Sub operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    sub_node = onnx.helper.make_node(
-        "Sub",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [sub_node]
+    return create_basic_op_node('Sub', node, kwargs)
 
 @mx_op.register("broadcast_sub")
 def covert_broadcast_sub(node, **kwargs):
     """Map MXNet's broadcast_sub operator attributes to onnx's Sub operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    sub_node = onnx.helper.make_node(
-        "Sub",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [sub_node]
-
+    return create_basic_op_node('Sub', node, kwargs)
 
 @mx_op.register("elemwise_mul")
 def convert_elemwise_mul(node, **kwargs):
     """Map MXNet's elemwise_mul operator attributes to onnx's Mul operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    mul_node = onnx.helper.make_node(
-        "Mul",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [mul_node]
+    return create_basic_op_node('Mul', node, kwargs)
 
 @mx_op.register("broadcast_mul")
 def convert_broadcast_mul(node, **kwargs):
     """Map MXNet's broadcast_mul operator attributes to onnx's Mul operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    mul_node = onnx.helper.make_node(
-        "Mul",
-        input_nodes,
-        [name],
-        name=name
-    )
-
-    return [mul_node]
-
+    return create_basic_op_node('Mul', node, kwargs)
 
 @mx_op.register("elemwise_div")
 def convert_elemwise_div(node, **kwargs):
     """Map MXNet's elemwise_div operator attributes to onnx's Div operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    div_node = onnx.helper.make_node(
-        "Div",
-        input_nodes,
-        [name],
-        name=name
-    )
-
-    return [div_node]
-
+    return create_basic_op_node('Div', node, kwargs)
 
 @mx_op.register("broadcast_div")
 def convert_broadcast_div(node, **kwargs):
     """Map MXNet's broadcast_div operator attributes to onnx's Div operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    div_node = onnx.helper.make_node(
-        "Div",
-        input_nodes,
-        [name],
-        name=name
-    )
-
-    return [div_node]
-
+    return create_basic_op_node('Div', node, kwargs)
 
 @mx_op.register("negative")
 def convert_negative(node, **kwargs):
     """Map MXNet's negative operator attributes to onnx's Neg operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    neg_node = onnx.helper.make_node(
-        "Neg",
-        input_nodes,
-        [name],
-        name=name,
-    )
-
-    return [neg_node]
-
+    return create_basic_op_node('Neg', node, kwargs)
 
 @mx_op.register("abs")
 def convert_abs(node, **kwargs):
     """Map MXNet's abs operator attributes to onnx's Abs operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    abs_node = onnx.helper.make_node(
-        "Abs",
-        input_nodes,
-        [name],
-        name=name
-    )
-
-    return [abs_node]
-
+    return create_basic_op_node('Abs', node, kwargs)
 
 @mx_op.register("add_n")
 def convert_addn(node, **kwargs):
     """Map MXNet's add_n operator attributes to onnx's Sum operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    sum_node = onnx.helper.make_node(
-        "Sum",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [sum_node]
+    return create_basic_op_node('Sum', node, kwargs)
 
  # Rounding
 @mx_op.register("ceil")
@@ -1436,30 +1228,14 @@ def convert_ceil(node, **kwargs):
     """Map MXNet's ceil operator attributes to onnx's Ceil operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Ceil",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Ceil', node, kwargs)
 
 @mx_op.register("floor")
 def convert_floor(node, **kwargs):
     """Map MXNet's floor operator attributes to onnx's Floor operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Floor",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Floor', node, kwargs)
 
 # Changing shape and type.
 @mx_op.register("Reshape")
@@ -1641,76 +1417,35 @@ def convert_log(node, **kwargs):
     """Map MXNet's log operator attributes to onnx's Log operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Log",
-        input_nodes,
-        [name],
-        name=name,
-    )
-    return [node]
-
+    return create_basic_op_node('Log', node, kwargs)
 
 @mx_op.register("reciprocal")
 def convert_reciprocal(node, **kwargs):
     """Map MXNet's reciprocal operator attributes to onnx's Reciprocal operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Reciprocal",
-        input_nodes,
-        [name],
-        name=name,
-    )
-    return [node]
+    return create_basic_op_node('Reciprocal', node, kwargs)
 
 @mx_op.register("_power")
 def convert_power(node, **kwargs):
     """Map MXNet's _power operator attributes to onnx's Pow operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Pow",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Pow', node, kwargs)
 
 @mx_op.register("broadcast_power")
 def convert_broadcast_power(node, **kwargs):
     """Map MXNet's _power operator attributes to onnx's Pow operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Pow",
-        input_nodes,
-        [name],
-        name=name
-    )
-    return [node]
+    return create_basic_op_node('Pow', node, kwargs)
 
 @mx_op.register("sqrt")
 def convert_sqrt(node, **kwargs):
     """Map MXNet's sqrt operator attributes to onnx's Sqrt operator
     and return the created node.
     """
-    name, input_nodes, _ = get_inputs(node, kwargs)
-
-    node = onnx.helper.make_node(
-        "Sqrt",
-        input_nodes,
-        [name],
-        name=name,
-    )
-    return [node]
+    return create_basic_op_node('Sqrt', node, kwargs)
 
 @mx_op.register("depth_to_space")
 def convert_depthtospace(node, **kwargs):