Added support for unused pad node

hpvm/projects/onnx/frontend/graph_builder.py

@@ -12,6 +12,7 @@ import graph_ir as g
 GraphT = onnx.GraphProto
 NodeT = onnx.NodeProto
 NodeT.__hash__ = lambda self: id(self)
+NodeT.__repr__ = NodeT.__str__ = lambda self: self.name
 
 
 class MarkedSubGraph:
@@ -74,7 +75,8 @@ class DFG(object):
         if len(onnx_graph.output) > 1:
             raise ValueError("Graph must have single output")
 
-    def _build_onnx_dfg(self, graph: GraphT) -> nx.DiGraph:
+    @staticmethod
+    def _build_onnx_dfg(graph: GraphT) -> nx.DiGraph:
         """Creates a DiGraph (by use-def relation) of onnx nodes from onnx GraphProto.
         DiGraph is easier to use as a graph compared to GraphProto where use-def is implicit."""
 
@@ -92,6 +94,7 @@ class DFG(object):
 
     def _build_dfg(self, onnx_graph: nx.DiGraph) -> nx.DiGraph:
         onnx_graph = detect_flatten(onnx_graph)
+        onnx_graph = remove_no_padding(onnx_graph)
         # For each onnx node, generate our nodes
         node_to_nodes, error_nodes = {}, []
         for onnx_node in nx.topological_sort(onnx_graph):
@@ -183,6 +186,26 @@ def def_use(nodes: Iterable) -> Tuple[dict, dict]:
     return defs, uses
 
 
+def remove_no_padding(graph: nx.DiGraph) -> nx.DiGraph:
+    for node in list(graph.nodes):
+        if node.op_type != "Pad":
+            continue
+        input_args = sorted_inputs(graph, node)
+        # Find the second input argument to Pad (will be a Constant node)
+        # and take that away as well.
+        nct = input_args[1]
+        padding = node_attr_to_dict(nct)["value"]
+        if any(p != 0 for p in padding):
+            continue
+        # Connect input of Pad to where output of Pad goes
+        succ = graph.out_edges(node, "index")
+        for _, to, index in succ:
+            graph.add_edge(input_args[0], to, index=index)
+        # Remove nodes
+        graph.remove_nodes_from([node, nct])
+    return graph
+
+
 def detect_flatten(graph: nx.DiGraph) -> nx.DiGraph:
     """Look for a shape-gather-unsqueeze-concat-reshape chain and replace that with flatten."""
 
@@ -280,3 +303,11 @@ def extract_tensors_from_graph(onnx_graph: GraphT) -> Dict[str, g.TensorNode]:
 def sorted_inputs(graph: nx.DiGraph, node):
     sorted_edges = sorted(graph.in_edges(node, "index"), key=lambda p: p[2])
     return [e[0] for e in sorted_edges]
+
+
+def draw_graph(graph: nx.DiGraph, output_to):
+    from networkx.drawing.nx_agraph import to_agraph
+
+    agraph = to_agraph(graph)
+    agraph.layout("dot")
+    agraph.draw(output_to)