Add SegmentMax-16 reference implementation

src/core/include/openvino/op/ops.hpp

@@ -172,6 +172,7 @@
 #include "openvino/op/scatter_nd_update.hpp"
 #include "openvino/op/scatter_update.hpp"
 #include "openvino/op/search_sorted.hpp"
+#include "openvino/op/segment_max.hpp"
 #include "openvino/op/select.hpp"
 #include "openvino/op/selu.hpp"
 #include "openvino/op/shape_of.hpp"

src/core/include/openvino/op/segment_max.hpp

@@ -0,0 +1,46 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/op/op.hpp"
+
+namespace ov::op::v16 {
+/// \brief An operation which computes the maximum values along segments of a tensor.
+/// \ingroup ov_ops_cpp_api
+class OPENVINO_API SegmentMax : public ov::op::Op {
+public:
+    OPENVINO_OP("SegmentMax", "opset16", ov::op::Op);
+
+    SegmentMax() = default;
+
+    /// \brief Constructs a SegmentMax operation.
+    ///
+    /// \param data Input tensor with data
+    /// \param segment_ids Indices of segments in the data input tensor
+    /// \param fill_mode The value assigned to segments which are empty
+    SegmentMax(const Output<Node>& data, const Output<Node>& segment_ids, const op::FillMode fill_mode);
+
+    /// \brief Constructs a SegmentMax operation.
+    ///
+    /// \param data Input tensor with data
+    /// \param segment_ids Indices of segments in the data input tensor
+    /// \param num_segments The segments count
+    /// \param fill_mode The value assigned to segments which are empty
+    SegmentMax(const Output<Node>& data,
+               const Output<Node>& segment_ids,
+               const Output<Node>& num_segments,
+               const op::FillMode fill_mode);
+
+    bool visit_attributes(AttributeVisitor& visitor) override;
+    void validate_and_infer_types() override;
+    std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
+
+    const op::FillMode get_fill_mode() const;
+
+private:
+    op::FillMode m_fill_mode{};
+};
+
+}  // namespace ov::op::v16

src/core/include/openvino/op/util/attr_types.hpp

@@ -20,6 +20,12 @@ enum class PadMode { CONSTANT = 0, EDGE, REFLECT, SYMMETRIC };
 OPENVINO_API
 std::ostream& operator<<(std::ostream& s, const PadMode& type);
 
+/// \brief Fill modes to set default value for operators like `SegmentMax`.
+enum class FillMode { ZERO = 0, LOWEST };
+
+OPENVINO_API
+std::ostream& operator<<(std::ostream& s, const FillMode& type);
+
 /// \brief Padding Type used for `Convolution` and `Pooling`
 ///
 /// Follows ONNX padding type definitions
@@ -219,6 +225,14 @@ class OPENVINO_API AttributeAdapter<op::PadMode> : public EnumAttributeAdapterBa
     OPENVINO_RTTI("AttributeAdapter<PadMode>");
 };
 
+template <>
+class OPENVINO_API AttributeAdapter<op::FillMode> : public EnumAttributeAdapterBase<op::FillMode> {
+public:
+    AttributeAdapter(op::FillMode& value) : EnumAttributeAdapterBase<op::FillMode>(value) {}
+
+    OPENVINO_RTTI("AttributeAdapter<FillMode>");
+};
+
 template <>
 class OPENVINO_API AttributeAdapter<op::PadType> : public EnumAttributeAdapterBase<op::PadType> {
 public:

src/core/include/openvino/opsets/opset16_tbl.hpp

@@ -16,3 +16,4 @@ _OPENVINO_OP_REG(ShapeOf, ov::op::v3)
 // New operations added in opset16
 _OPENVINO_OP_REG(Identity, ov::op::v16)
 _OPENVINO_OP_REG(ISTFT, ov::op::v16)
+_OPENVINO_OP_REG(SegmentMax, ov::op::v16)

src/core/reference/include/openvino/reference/segment_max.hpp

@@ -0,0 +1,63 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <algorithm>
+#include <limits>
+#include <vector>
+
+#include "openvino/core/shape.hpp"
+
+namespace ov::reference {
+
+template <typename T,
+          typename T_idx,
+          typename std::enable_if<std::is_same<typename std::decay<T_idx>::type, int64_t>::value>::type* = nullptr>
+void segment_max(const T* data,
+                 const Shape& data_shape,
+                 const T_idx* segment_ids,
+                 T* out,
+                 const Shape& output_shape,
+                 const T empty_segment_value) {
+    const T_idx num_segments = output_shape[0];
+    const auto inner_dim_size = shape_size(data_shape.begin() + 1, data_shape.end());
+
+    // Initialize output with empty_segment_value
+    std::fill(out, out + num_segments * inner_dim_size, empty_segment_value);
+
+    // Iterate over each element in the first dimension
+    for (size_t i = 0; i < data_shape[0]; ++i) {
+        const T_idx segment_id = segment_ids[i];
+        if (segment_id >= num_segments) {
+            continue;
+        }
+        // Iterate over each element in the inner dimensions
+        for (size_t j = 0; j < inner_dim_size; ++j) {
+            const size_t index = i * inner_dim_size + j;
+            const size_t out_index = segment_id * inner_dim_size + j;
+            // Update the maximum value for the current segment and inner dimension
+            out[out_index] = std::max(out[out_index], data[index]);
+        }
+    }
+}
+
+template <typename T,
+          typename T_idx,
+          typename std::enable_if<!std::is_same<typename std::decay<T_idx>::type, int64_t>::value>::type* = nullptr>
+void segment_max(const T* data,
+                 const Shape& data_shape,
+                 const T_idx* segment_ids,
+                 T* out,
+                 const Shape& output_shape,
+                 const T empty_segment_value) {
+    std::vector<int64_t> segment_ids_int64(data_shape[0]);
+    std::transform(segment_ids, segment_ids + data_shape[0], segment_ids_int64.begin(), [](T_idx id) {
+        return static_cast<int64_t>(id);
+    });
+
+    segment_max(data, data_shape, segment_ids_int64.data(), out, output_shape, empty_segment_value);
+}
+
+}  // namespace ov::reference

src/core/shape_inference/include/segment_max_shape_inference.hpp

@@ -0,0 +1,82 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <cmath>
+
+#include "openvino/op/segment_max.hpp"
+#include "utils.hpp"
+
+namespace ov {
+namespace op {
+namespace v16 {
+template <class TShape, class TRShape = result_shape_t<TShape>>
+std::vector<TRShape> shape_infer(const SegmentMax* op,
+                                 const std::vector<TShape>& input_shapes,
+                                 const ITensorAccessor& tensor_accessor = make_tensor_accessor()) {
+    NODE_VALIDATION_CHECK(op, input_shapes.size() == 2 || input_shapes.size() == 3);
+
+    // validate shape of data input
+    const auto& data_shape = input_shapes[0];
+    const auto is_data_shape_rank_static = data_shape.rank().is_static();
+    if (is_data_shape_rank_static) {
+        NODE_SHAPE_INFER_CHECK(op, input_shapes, data_shape.size() > 0, "The data input cannot be a scalar.");
+    }
+
+    // validate segment_ids input
+    const auto& segment_ids_shape = input_shapes[1];
+    const auto is_segment_ids_rank_static = segment_ids_shape.rank().is_static();
+    if (is_segment_ids_rank_static) {
+        NODE_SHAPE_INFER_CHECK(op,
+                               input_shapes,
+                               segment_ids_shape.size() == 1,
+                               "segment_ids must be a 1D input. Got: ",
+                               segment_ids_shape);
+        if (is_data_shape_rank_static) {
+            NODE_SHAPE_INFER_CHECK(op,
+                                   input_shapes,
+                                   data_shape[0].compatible(segment_ids_shape[0]),
+                                   "The number of elements in segment_ids must match the first dimension of data.");
+        }
+    }
+    const auto segment_ids = ov::op::get_input_const_data_as<TRShape, int64_t>(op, 1, tensor_accessor);
+    if (segment_ids) {
+        NODE_VALIDATION_CHECK(op,
+                              std::is_sorted(segment_ids->begin(), segment_ids->end()),
+                              "segment_ids must be sorted.");
+    }
+
+    // validate num_segments input
+    const auto num_segments_available = op->inputs().size() == 3;
+    const auto num_segments = num_segments_available ? get_input_const_data_as_shape<TRShape>(op, 2, tensor_accessor)
+                                                     : ov::optional<TRShape>{};
+    if (num_segments_available) {
+        const auto& num_segments_shape = input_shapes[2];
+        NODE_SHAPE_INFER_CHECK(op,
+                               input_shapes,
+                               num_segments_shape.rank().compatible(0),
+                               "num_segments must be a scalar input. Got: ",
+                               num_segments_shape);
+    }
+
+    if (!is_data_shape_rank_static) {
+        return {PartialShape::dynamic()};
+    }
+    using TDim = typename TShape::value_type;
+    auto output_shapes = std::vector<TRShape>{data_shape};
+    auto& output_shape = output_shapes[0];
+    if (num_segments) {
+        output_shape[0] = TDim((*num_segments)[0]);
+    } else if (segment_ids && !num_segments_available) {
+        output_shape[0] = TDim(segment_ids->back() + 1);
+    } else {
+        // if num_segments input is provided but the value is unknown, the first dimension should be dynamic
+        output_shape[0] = Dimension::dynamic();
+    }
+    return output_shapes;
+}
+}  // namespace v16
+}  // namespace op
+}  // namespace ov

src/core/src/op/segment_max.cpp

@@ -0,0 +1,72 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/segment_max.hpp"
+
+#include "itt.hpp"
+#include "openvino/core/validation_util.hpp"
+#include "openvino/op/op.hpp"
+#include "segment_max_shape_inference.hpp"
+
+namespace ov {
+namespace op {
+namespace v16 {
+
+SegmentMax::SegmentMax(const Output<Node>& data, const Output<Node>& segment_ids, const op::FillMode fill_mode)
+    : Op({data, segment_ids}),
+      m_fill_mode(fill_mode) {
+    constructor_validate_and_infer_types();
+}
+
+SegmentMax::SegmentMax(const Output<Node>& data,
+                       const Output<Node>& segment_ids,
+                       const Output<Node>& num_segments,
+                       const op::FillMode fill_mode)
+    : Op({data, segment_ids, num_segments}),
+      m_fill_mode(fill_mode) {
+    constructor_validate_and_infer_types();
+}
+
+bool SegmentMax::visit_attributes(ov::AttributeVisitor& visitor) {
+    OV_OP_SCOPE(v16_SegmentMax_visit_attributes);
+    visitor.on_attribute("fill_mode", m_fill_mode);
+    return true;
+}
+
+void SegmentMax::validate_and_infer_types() {
+    OV_OP_SCOPE(v16_SegmentMax_validate_and_infer_types);
+    const auto& segment_ids_element_type = get_input_element_type(1);
+    NODE_VALIDATION_CHECK(this,
+                          segment_ids_element_type == element::i32 || segment_ids_element_type == element::i64,
+                          "The element type of the segment_ids input be i32 or i64. Got: ",
+                          segment_ids_element_type);
+    if (inputs().size() == 3) {
+        const auto& num_segments_element_type = get_input_element_type(2);
+        NODE_VALIDATION_CHECK(this,
+                              num_segments_element_type == element::i32 || num_segments_element_type == element::i64,
+                              "The element type of the num_segments input be i32 or i64. Got: ",
+                              num_segments_element_type);
+    }
+
+    const auto output_shapes = shape_infer(this, ov::util::get_node_input_partial_shapes(*this));
+    set_output_type(0, get_input_element_type(0), output_shapes[0]);
+}
+
+std::shared_ptr<Node> SegmentMax::clone_with_new_inputs(const ov::OutputVector& new_args) const {
+    OV_OP_SCOPE(v16_SegmentMax_clone_with_new_inputs);
+    check_new_args_count(this, new_args);
+    if (new_args.size() == 3) {
+        return std::make_shared<SegmentMax>(new_args.at(0), new_args.at(1), new_args.at(2), m_fill_mode);
+    } else {
+        return std::make_shared<SegmentMax>(new_args.at(0), new_args.at(1), m_fill_mode);
+    }
+}
+
+const op::FillMode SegmentMax::get_fill_mode() const {
+    return m_fill_mode;
+}
+
+}  // namespace v16
+}  // namespace op
+}  // namespace ov

src/core/src/op/util/attr_types.cpp

@@ -21,6 +21,14 @@ OPENVINO_API EnumNames<ov::op::PadMode>& EnumNames<ov::op::PadMode>::get() {
     return enum_names;
 }
 
+template <>
+OPENVINO_API EnumNames<ov::op::FillMode>& EnumNames<ov::op::FillMode>::get() {
+    static auto enum_names =
+        EnumNames<ov::op::FillMode>("ov::op::FillMode",
+                                    {{"zero", ov::op::FillMode::ZERO}, {"lowest", ov::op::FillMode::LOWEST}});
+    return enum_names;
+}
+
 template <>
 OPENVINO_API EnumNames<ov::op::PadType>& EnumNames<ov::op::PadType>::get() {
     static auto enum_names = EnumNames<ov::op::PadType>("ov::op::PadType",
@@ -132,6 +140,10 @@ std::ostream& op::operator<<(std::ostream& s, const ov::op::PadMode& type) {
     return s << as_string(type);
 }
 
+std::ostream& op::operator<<(std::ostream& s, const ov::op::FillMode& type) {
+    return s << as_string(type);
+}
+
 std::ostream& op::operator<<(std::ostream& s, const ov::op::PadType& type) {
     return s << as_string(type);
 }