Fix broadcast with BroadcastType::NONE and unit dimensions

ngraph/core/src/op/util/broadcast_base.cpp

@@ -147,7 +147,8 @@ void op::util::BroadcastBase::validate_target_shape_none(const PartialShape& arg
         if (arg_shape.rank().get_length() > 0)
         {
             NODE_VALIDATION_CHECK(this,
-                                  target_shape[axes_mapping_val[i]].compatible(arg_shape[i]),
+                                  target_shape[axes_mapping_val[i]].compatible(arg_shape[i]) ||
+                                      arg_shape[i].compatible(1),
                                   "Broadcast target[axes_mapping[",
                                   i,
                                   "]]",
@@ -575,4 +576,4 @@ bool op::util::BroadcastBase::evaluate_upper(const HostTensorVector& output_valu
         (get_input_size() > 2 && !input_value(2).get_tensor().has_and_set_bound()))
         return false;
     return default_upper_bound_evaluator(this, output_values);
-}
+}

ngraph/python/tests/__init__.py

@@ -134,8 +134,6 @@ def xfail_test(reason="Mark the test as expected to fail", strict=True):
                                       "FakeQuantize_xxx has non const input on 1 port")
 xfail_issue_46762 = xfail_test(reason="Incorrect result of Minimum op if uint data type is used")
 xfail_issue_46765 = xfail_test(reason="select_last_index attribute is not supported by ArgMin and ArgMax")
-xfail_issue_47317 = xfail_test(reason="RuntimeError: While validating ONNX node '<Node(Add): 2>': "
-                                      "Check shape_size(axes_shape) == input_rank' failed")
 xfail_issue_47323 = xfail_test(reason="RuntimeError: The plugin does not support FP64")
 xfail_issue_47337 = xfail_test(reason="RuntimeError: Unsupported dynamic ops: v1::OneHot")
 xfail_issue_33593 = xfail_test(reason="Current implementation of MaxPool doesn't support indices output")
@@ -173,3 +171,5 @@ def xfail_test(reason="Mark the test as expected to fail", strict=True):
 xfail_issue_49752 = xfail_test(reason="RuntimeError: Unsupported dynamic ops: v1::Pad")
 xfail_issue_49753 = xfail_test(reason="RuntimeError: Unsupported dynamic ops: v1::StridedSlice")
 xfail_issue_49754 = xfail_test(reason="RuntimeError: Unsupported dynamic ops: v1::TopKIE")
+xfail_issue_52463 = xfail_test(reason="test_operator_add_size1_singleton_broadcast_cpu - "
+                                      "Not equal to tolerance")

ngraph/python/tests/test_onnx/test_backend.py

@@ -57,15 +57,15 @@
                    xfail_issue_45344,
                    xfail_issue_46762,
                    xfail_issue_46765,
-                   xfail_issue_47317,
                    xfail_issue_47323,
                    xfail_issue_47337,
                    xfail_issue_48052,
                    xfail_issue_49207,
                    xfail_issue_49750,
                    xfail_issue_49752,
                    xfail_issue_49753,
-                   xfail_issue_49754)
+                   xfail_issue_49754,
+                   xfail_issue_52463)
 
 
 def expect_fail(test_case_path, xfail):  # type: (str) -> None
@@ -189,9 +189,8 @@ def expect_fail(test_case_path, xfail):  # type: (str) -> None
      "OnnxBackendNodeModelTest.test_argmin_no_keepdims_random_select_last_index_cpu"),
     (xfail_issue_38091,
      "OnnxBackendNodeModelTest.test_gather_negative_indices_cpu"),
-    (xfail_issue_47317,
-     "OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_broadcast_cpu",
-     "OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_singleton_broadcast_cpu",),
+    (xfail_issue_52463,
+     "OnnxBackendPyTorchOperatorModelTest.test_operator_add_size1_singleton_broadcast_cpu"),
     (xfail_issue_47323,
      "OnnxBackendPyTorchOperatorModelTest.test_operator_add_broadcast_cpu",
      "OnnxBackendPyTorchOperatorModelTest.test_operator_addconstant_cpu",

ngraph/test/backend/broadcast.in.cpp

@@ -456,6 +456,22 @@ NGRAPH_TEST(${BACKEND_NAME}, broadcast_algo_3d_stride_2)
     broadcast_test_helper(shape_a, shape_r, axis);
 }
 
+NGRAPH_TEST(${BACKEND_NAME}, broadcast_algo_3d_diffrent_rank)
+{
+    Shape shape_a{3, 1};
+    Shape shape_r{2, 3, 3};
+    AxisSet axis{1, 2};
+    broadcast_test_helper(shape_a, shape_r, axis);
+}
+
+NGRAPH_TEST(${BACKEND_NAME}, broadcast_algo_4d_same_rank)
+{
+    Shape shape_a{2, 3, 1, 1};
+    Shape shape_r{2, 3, 4, 5};
+    AxisSet axis{0, 1, 2, 3};
+    broadcast_test_helper(shape_a, shape_r, axis);
+}
+
 NGRAPH_TEST(${BACKEND_NAME}, broadcast_matrix_0)
 {
     Shape shape_a{2, 2};

ngraph/test/type_prop/broadcast.cpp

@@ -151,7 +151,7 @@ TYPED_TEST_P(BroadcastTests, broadcast_fail_axes_map)
 
 TYPED_TEST_P(BroadcastTests, broadcast_fail_axes_map_shape)
 {
-    auto param = make_shared<op::Parameter>(element::f32, Shape{3, 1});
+    auto param = make_shared<op::Parameter>(element::f32, Shape{3, 2});
     auto target_shape = op::Constant::create<int64_t>(element::i64, Shape{3}, {2, 3, 3});
     auto axes_mapping = op::Constant::create<int64_t>(element::i64, Shape{2}, {1, 2});
 
@@ -162,7 +162,7 @@ TYPED_TEST_P(BroadcastTests, broadcast_fail_axes_map_shape)
     }
     catch (const NodeValidationFailure& error)
     {
-        EXPECT_HAS_SUBSTRING(error.what(), "Broadcast target[axes_mapping[1]] Expected 1. Got 3");
+        EXPECT_HAS_SUBSTRING(error.what(), "Broadcast target[axes_mapping[1]] Expected 2. Got 3");
     }
     catch (...)
     {