added logaddexp

src/frontends/pytorch/src/op/logaddexp.cpp

@@ -0,0 +1,53 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/frontend/pytorch/node_context.hpp"
+#include "openvino/op/add.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/convert.hpp"
+#include "openvino/op/convert_like.hpp"
+#include "openvino/op/exp.hpp"
+#include "openvino/op/log.hpp"
+#include "utils.hpp"
+
+namespace ov {
+namespace frontend {
+namespace pytorch {
+namespace op {
+
+using namespace ov::op;
+
+OutputVector translate_logaddexp(const NodeContext& context) {
+    // "aten::logaddexp(Tensor self, Tensor other) -> Tensor"
+    num_inputs_check(context, 2, 2);
+
+    auto input1 = context.get_input(0);
+    auto input2 = context.get_input(1);
+
+    // Convert inputs to floating point type if needed
+    input1 = context.mark_node(std::make_shared<v0::Convert>(input1, element::f32));
+    input2 = context.mark_node(std::make_shared<v0::Convert>(input2, element::f32));
+
+    // Calculate exp(input1) and exp(input2)
+    auto exp1 = context.mark_node(std::make_shared<v0::Exp>(input1));
+    auto exp2 = context.mark_node(std::make_shared<v0::Exp>(input2));
+
+    // Add the exponentials
+    auto sum = context.mark_node(std::make_shared<v1::Add>(exp1, exp2));
+
+    // Take the natural logarithm of the sum
+    auto result = context.mark_node(std::make_shared<v0::Log>(sum));
+
+    // If the output tensor type is different, convert to match
+    if (input1.get_element_type() != element::f32) {
+        result = context.mark_node(std::make_shared<v1::ConvertLike>(result, input1));
+    }
+
+    return {result};
+};
+
+}  // namespace op
+}  // namespace pytorch
+}  // namespace frontend
+}  // namespace ov