Supports ReduceLogSum for python runtime (#403)

_unittests/ut_onnxrt/test_onnxrt_python_runtime_.py

@@ -59,7 +59,8 @@
     OnnxRange,
     OnnxReciprocal,
     OnnxReduceL1, OnnxReduceL2,
-    OnnxReduceLogSumExp, OnnxReduceMax, OnnxReduceMean, OnnxReduceMin,
+    OnnxReduceLogSum, OnnxReduceLogSumExp, OnnxReduceMax,
+    OnnxReduceMean, OnnxReduceMin,
     OnnxReduceProd,
     OnnxReduceSum, OnnxReduceSumApi11,
     OnnxReduceSum_13, OnnxReduceSum_11, OnnxReduceSum_1,
@@ -3631,6 +3632,24 @@ def reduce_l2(x, axis, keepdims):
                               got['Y'].ravel())
         python_tested.append(OnnxReduceL2)
 
+    @wraplog()
+    def test_onnxt_runtime_reduce_log_sum(self):
+        X = numpy.array([[2, 1], [4, 1]], dtype=float)
+
+        onx = OnnxReduceLogSum('X', output_names=['Y'], keepdims=0,
+                               op_version=TARGET_OPSET)
+        model_def = onx.to_onnx({'X': X.astype(numpy.float32)},
+                                target_opset=TARGET_OPSET)
+        oinf = OnnxInference(model_def)
+        got = oinf.run({'X': X.astype(numpy.float32)})
+        self.assertEqual(list(sorted(got)), ['Y'])
+        res = numpy.log(numpy.sum(X))
+        self.assertEqualArray(res, got['Y'], decimal=5)
+        self.common_expected_shapes_types(
+            oinf, {'X': X.astype(numpy.float32)}, got,
+            OnnxReduceLogSum, model_def)
+        python_tested.append(OnnxReduceLogSum)
+
     @wraplog()
     def test_onnxt_runtime_reduce_log_sum_exp(self):
         X = numpy.array([[2, 1], [0, 1]], dtype=float)

mlprodict/onnxrt/ops_cpu/_op_list.py

@@ -99,6 +99,7 @@
     RandomNormal, RandomUniform, RandomUniformLike, RandomNormalLike)
 from .op_range import Range
 from .op_reciprocal import Reciprocal
+from .op_reduce_log_sum import ReduceLogSum
 from .op_reduce_log_sum_exp import ReduceLogSumExp
 from .op_reduce_l1 import ReduceL1
 from .op_reduce_l2 import ReduceL2

mlprodict/onnxrt/ops_cpu/op_reduce_log_sum.py

@@ -0,0 +1,25 @@
+# -*- encoding: utf-8 -*-
+# pylint: disable=E0203,E1101,C0111
+"""
+@file
+@brief Runtime operator.
+"""
+import numpy
+from ._op import OpRunReduceNumpy
+
+
+class ReduceLogSum(OpRunReduceNumpy):
+
+    atts = {'axes': [], 'keepdims': 1}
+
+    def __init__(self, onnx_node, desc=None, **options):
+        OpRunReduceNumpy.__init__(self, onnx_node, desc=desc,
+                                  expected_attributes=ReduceLogSum.atts,
+                                  **options)
+
+    def _run(self, data):  # pylint: disable=W0221
+        tax = tuple(self.axes) if self.axes else None
+        res = numpy.sum(data, axis=tax, keepdims=self.keepdims)
+        if len(res.shape) > 0:
+            return (numpy.log(res, out=res), )
+        return (numpy.log(res), )