Fix bug in casting Log inputs

Signed-off-by: Tom Wildenhain <[email protected]>

Author: TomWildenhain-Microsoft

tests/test_backend.py

@@ -903,6 +903,14 @@ def func(x):
             return tf.identity(x_, name=_TFOUTPUT)
         self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})
 
+    @check_onnxruntime_incompatibility("Log")
+    def test_log_double(self):
+        x_val = np.array([1.0, 2.0, 3.0, 4.0], dtype=np.float64).reshape((2, 2))
+        def func(x):
+            x_ = tf.math.log(x)
+            return tf.identity(x_, name=_TFOUTPUT)
+        self._run_test_case(func, [_OUTPUT], {_INPUT: x_val})
+
     def test_gather(self):
         x_val = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float32)
         idx = np.array([1, 0, 2], dtype=np.int32)

tf2onnx/onnx_opset/math.py

@@ -51,8 +51,19 @@ def version_6(cls, ctx, node, **kwargs):
         if node.type == "Log":
             # ORT doesn't implement Log on doubles
             double_to_float = {onnx_pb.TensorProto.DOUBLE: onnx_pb.TensorProto.FLOAT}
-            node.maybe_cast_input([[onnx_pb.TensorProto.FLOAT]], double_to_float)
+            dtypes = node.output_dtypes
+            if node.maybe_cast_input([[onnx_pb.TensorProto.FLOAT]], double_to_float):
+                cast_back_node = ctx.insert_new_node_on_output(
+                    "Cast", node.output[0], name=utils.make_name(node.name + "_castback"),
+                    to=dtypes[0])
+                ctx.set_dtype(cast_back_node.output[0], dtypes[0])
+                ctx.copy_shape(node.name, cast_back_node.output[0])
+                ctx.copy_dtype(node.input[0], node.output[0])
 
+    @classmethod
+    def version_13(cls, ctx, node, **kwargs):
+        # Latest ORT does implement Log on doubles
+        pass
 
 @tf_op(["Acos", "Asin", "Atan", "Cos", "Sin", "Tan"])
 class TrigOpSinceOpset7: