Add support for ReduceL1 and ReduceL2 to ONNX Importer (#1838)

openvinotoolkit · Aug 27, 2020 · d368241 · d368241
1 parent c147f03
commit d368241
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Showing 3 changed files with 14 additions and 21 deletions.
diff --git a/ngraph/core/include/ngraph/op/reduce_l1.hpp b/ngraph/core/include/ngraph/op/reduce_l1.hpp
@@ -39,7 +39,6 @@ namespace ngraph
                 ///
                 /// \param arg The tensor to be reduced.
                 /// \param reduction_axes The axis positions (0-based) to be eliminated.
-                /// \param p The scalar defining the order of normalization.
                 /// \param keep_dims If set to true it holds axes that are used for reduction.
                 ReduceL1(const Output<Node>& arg,
                          const Output<Node>& reduction_axes,

diff --git a/ngraph/frontend/onnx_import/src/op/reduce.cpp b/ngraph/frontend/onnx_import/src/op/reduce.cpp
@@ -59,28 +59,24 @@ namespace ngraph
 
                 OutputVector reduce_l1(const Node& node)
                 {
-                    auto l1_norm_reduction = [](const Output<ngraph::Node>& node,
-                                                const ngraph::AxisSet& axis_set) {
-                        const auto axis_set_const = default_opset::Constant::create(
-                            element::i64, {axis_set.size()}, axis_set.to_vector());
-                        return ngraph::builder::opset1::l1_norm(node, axis_set_const, 0.f);
-                    };
-
                     return {reduction::make_ng_reduction_op(
-                        node, node.get_ng_inputs().at(0), l1_norm_reduction)};
+                        node,
+                        node.get_ng_inputs().at(0),
+                        std::make_shared<default_opset::ReduceL1,
+                                         const Output<ngraph::Node>&,
+                                         const Output<ngraph::Node>&,
+                                         bool>)};
                 }
 
                 OutputVector reduce_l2(const Node& node)
                 {
-                    auto l2_norm_reduction = [](const Output<ngraph::Node>& node,
-                                                const ngraph::AxisSet& axis_set) {
-                        const auto axis_set_const = default_opset::Constant::create(
-                            element::i64, {axis_set.size()}, axis_set.to_vector());
-                        return ngraph::builder::opset1::l2_norm(
-                            node, axis_set_const, 0.f, ngraph::builder::BiasMode::ADD, false);
-                    };
                     return {reduction::make_ng_reduction_op(
-                        node, node.get_ng_inputs().at(0), l2_norm_reduction)};
+                        node,
+                        node.get_ng_inputs().at(0),
+                        std::make_shared<default_opset::ReduceL2,
+                                         const Output<ngraph::Node>&,
+                                         const Output<ngraph::Node>&,
+                                         bool>)};
                 }
 
                 OutputVector reduce_max(const Node& node)

diff --git a/ngraph/python/tests/test_onnx/test_ops_reduction.py b/ngraph/python/tests/test_onnx/test_ops_reduction.py
@@ -96,7 +96,6 @@ def test_reduce_l1(reduction_axes):
     assert np.allclose(expected, ng_result)
 
 
-@xfail_issue_35925
 def test_reduce_l1_default_axes():
     shape = [2, 4, 3, 2]
     np.random.seed(133391)
@@ -108,7 +107,7 @@ def test_reduce_l1_default_axes():
     assert np.array_equal(expected.shape, ng_result.shape)
     assert np.allclose(expected, ng_result)
 
-    expected = np.sum(np.abs(input_data), keepdims=False)
+    expected = np.array([np.sum(np.abs(input_data), keepdims=False)])
     node = onnx.helper.make_node("ReduceL1", inputs=["x"], outputs=["y"], keepdims=0)
     ng_result = np.array(run_node(node, [input_data]).pop())
     assert np.array_equal(expected.shape, ng_result.shape)
@@ -135,7 +134,6 @@ def test_reduce_l2(reduction_axes):
     assert np.allclose(expected, ng_result)
 
 
-@xfail_issue_35925
 def test_reduce_l2_default_axes():
     shape = [2, 4, 3, 2]
     np.random.seed(133391)
@@ -147,7 +145,7 @@ def test_reduce_l2_default_axes():
     assert np.array_equal(expected.shape, ng_result.shape)
     assert np.allclose(expected, ng_result)
 
-    expected = np.sqrt(np.sum(np.square(input_data), keepdims=False))
+    expected = np.array([np.sqrt(np.sum(np.square(input_data), keepdims=False))])
     node = onnx.helper.make_node("ReduceL2", inputs=["x"], outputs=["y"], keepdims=0)
     ng_result = np.array(run_node(node, [input_data]).pop())
     assert np.array_equal(expected.shape, ng_result.shape)