Fixed ngraph reference impl for Range operation (openvinotoolkit#20631)

* Fixed ngraph reference impl for Range operation * Truncate range for integer output type * explicit static cast
itikhono · Oct 24, 2023 · 5853509 · 5853509
1 parent 7ceff55
commit 5853509
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Showing 2 changed files with 42 additions and 12 deletions.
diff --git a/src/core/src/op/range.cpp b/src/core/src/op/range.cpp
@@ -144,37 +144,46 @@ bool evaluate(const HostTensorPtr& out,
               const HostTensorPtr& step,
               int version) {
     using T = typename element_type_traits<ET>::value_type;
-    T start_val;
-    T stop_val;
-    T step_val;
+    double start_val;
+    double stop_val;
+    double step_val;
     if (version < 4) {
-        start_val = *start->get_data_ptr<ET>();
-        stop_val = *stop->get_data_ptr<ET>();
-        step_val = *step->get_data_ptr<ET>();
+        start_val = static_cast<double>(*start->get_data_ptr<ET>());
+        stop_val = static_cast<double>(*stop->get_data_ptr<ET>());
+        step_val = static_cast<double>(*step->get_data_ptr<ET>());
         if (!(check_value(start_val) && check_value(stop_val) && check_value(step_val) &&
               (step_val != static_cast<T>(0)))) {
             return false;
         }
     } else {
-        if (!(get_casted_value<T>(start, &start_val) && get_casted_value<T>(stop, &stop_val) &&
-              get_casted_value<T>(step, &step_val))) {
+        if (!(get_casted_value<double>(start, &start_val) && get_casted_value<double>(stop, &stop_val) &&
+              get_casted_value<double>(step, &step_val))) {
             return false;
         }
     }
 
     int64_t out_size = 0;
 
+    if (ov::element::Type(ET).is_integral_number()) {
+        start_val = std::trunc(start_val);
+        stop_val = std::trunc(stop_val);
+        step_val = std::trunc(step_val);
+    }
+
     int64_t steps = static_cast<int64_t>(std::ceil(double(stop_val - start_val) / step_val));
     if (steps > 0) {
         out_size = steps;
     }
     ov::Shape out_shape = ov::Shape({static_cast<size_t>(out_size)});
     out->set_shape(out_shape);
-    ov::reference::range(&start_val, &step_val, shape_size(out_shape), out->get_data_ptr<ET>());
+
+    T start_val_casted = static_cast<T>(start_val);
+    T step_val_casted = static_cast<T>(step_val);
+    ov::reference::range(&start_val_casted, &step_val_casted, shape_size(out_shape), out->get_data_ptr<ET>());
     return true;
 }
 
-bool evaluate_power(const HostTensorPtr& out,
+bool evaluate_range(const HostTensorPtr& out,
                     const HostTensorPtr& start,
                     const HostTensorPtr& stop,
                     const HostTensorPtr& step,
@@ -209,7 +218,7 @@ bool op::v4::Range::evaluate(const HostTensorVector& outputs, const HostTensorVe
     HostTensorPtr start = inputs[0];
     HostTensorPtr stop = inputs[1];
     HostTensorPtr step = inputs[2];
-    return rangeop::evaluate_power(out, start, stop, step, m_output_type, 4);
+    return rangeop::evaluate_range(out, start, stop, step, m_output_type, 4);
 }
 
 bool op::v4::Range::has_evaluate() const {
@@ -381,7 +390,7 @@ bool op::v0::Range::evaluate(const HostTensorVector& outputs, const HostTensorVe
     HostTensorPtr start = inputs[0];
     HostTensorPtr stop = inputs[1];
     HostTensorPtr step = inputs[2];
-    return rangeop::evaluate_power(out, start, stop, step, start->get_element_type(), 0);
+    return rangeop::evaluate_range(out, start, stop, step, start->get_element_type(), 0);
 }
 
 bool op::v0::Range::has_evaluate() const {

diff --git a/src/core/tests/eval.cpp b/src/core/tests/eval.cpp
@@ -178,6 +178,27 @@ TEST(eval, evaluate_dynamic_range_sum) {
     ASSERT_EQ(cval, seq);
 }
 
+TEST(eval, evaluate_dynamic_range_fp16_out) {
+    auto p_start = make_shared<ov::op::v0::Parameter>(element::i32, PartialShape{});
+    auto p_stop = make_shared<ov::op::v0::Parameter>(element::i32, PartialShape{});
+    auto p_step = make_shared<ov::op::v0::Parameter>(element::i32, PartialShape{});
+    auto range = make_shared<op::v4::Range>(p_start, p_stop, p_step, ov::element::f16);
+    auto model = make_shared<Model>(OutputVector{range}, ParameterVector{p_start, p_stop, p_step});
+    auto result_tensor = ov::Tensor();
+    auto out_vector = ov::TensorVector{result_tensor};
+    auto in_vector = ov::TensorVector{make_tensor<element::Type_t::i32>({}, {0}),
+                                      make_tensor<element::Type_t::i32>({}, {3087}),
+                                      make_tensor<element::Type_t::i32>({}, {1})};
+    ASSERT_TRUE(model->evaluate(out_vector, in_vector));
+    result_tensor = out_vector.at(0);
+    EXPECT_EQ(result_tensor.get_element_type(), element::f16);
+    EXPECT_EQ(result_tensor.get_shape(), (Shape{3087}));
+    auto cval = read_vector<ov::float16>(result_tensor);
+    for (size_t i = 0; i < 3087; i++) {
+        ASSERT_EQ(cval[i], ov::float16(i));
+    }
+}
+
 TEST(eval, evaluate_broadcast_v3_bidirectional) {
     Shape shape_a{4, 1};
     auto A = make_shared<ov::op::v0::Parameter>(element::f32, shape_a);