Merge pull request #903 from jignparm/master

Some ops for opset 12.

Author: jignparm

tf2onnx/onnx_opset/math.py

@@ -137,6 +137,9 @@ def version_1(cls, ctx, node, **kwargs):
         ctx.remove_node(node.name)
         make_min_or_max_op(ctx, node.type, node.input, node.output, shapes, dtypes)
 
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):
+        pass # support all numeric types and broadcasting
 
 @tf_op("ClipByValue")
 class ClipByValueOp:
@@ -178,6 +181,9 @@ def version_8(cls, ctx, node, **kwargs):
             ctx.set_dtype(new_node.output[0], dtypes[0])
             ctx.set_shape(new_node.output[0], shapes[0])
 
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):
+        node.name = 'Clip' # clip supports all types now
 
 @tf_op("Softmax")
 class Softmax:

tf2onnx/onnx_opset/reduction.py

@@ -89,6 +89,11 @@ def version_11(cls, ctx, node, **kwargs):
         # Opset 11 supports negative axis, but core logic same
         cls.version_1(ctx, node, **kwargs)
 
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):
+        # Opset 12 adds extra attribute 'select_last_index'
+        # No changes needed
+        cls.version_1(ctx, node, **kwargs)
 
 @tf_op(["All", "Any"])
 class AllAny:

tf2onnx/onnx_opset/tensor.py

@@ -100,6 +100,10 @@ def version_7(cls, ctx, node, **kwargs):
     def version_10(cls, ctx, node, **kwargs):
         pass
 
+    @classmethod
+    def version_12(cls, ctx, node, **kwargs):
+        pass
+
 
 @tf_op("Identity")
 class Identity: