Update randperm.cpp

now it can handle value of n dynamically

Author: vijaykr338

src/frontends/pytorch/src/op/randperm.cpp

@@ -1,8 +1,12 @@
+// Copyright (C) 2018-2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
 #include "openvino/frontend/pytorch/node_context.hpp"
 #include "openvino/op/constant.hpp"
 #include "openvino/op/random_uniform.hpp"
-#include "openvino/op/shape_of.hpp"
 #include "openvino/op/topk.hpp"
+#include "openvino/op/unsqueeze.hpp"
 #include "utils.hpp"
 
 namespace ov {
@@ -14,38 +18,34 @@ using namespace ov::op;
 
 OutputVector translate_randperm(const NodeContext& context) {
     auto num_inputs = context.get_input_size();
-    int64_t n = context.const_input<int64_t>(0);
+    auto n_node = context.get_input(0);
     int dtype_value = 4;
     if (num_inputs == 1) {
     } else if (num_inputs == 2) {
         if (!context.input_is_none(1)) {
             dtype_value = context.const_input<int>(1);
-            OPENVINO_ASSERT(dtype_value == 4,
-                            "Only dtype value 4 (int64) is supported for aten::randperm, got: ",
-                            dtype_value);
+            PYTORCH_OP_CONVERSION_CHECK(dtype_value == 4,
+                                        "Only dtype value 4 (int64) is supported for aten::randperm, got: ",
+                                        dtype_value);
         }
     } else if (num_inputs == 5) {
         if (!context.input_is_none(1)) {
             dtype_value = context.const_input<int>(1);
-            OPENVINO_ASSERT(dtype_value == 4,
-                            "Only dtype value 4 (int64) is supported for aten::randperm, got: ",
-                            dtype_value);
+            PYTORCH_OP_CONVERSION_CHECK(dtype_value == 4,
+                                        "Only dtype value 4 (int64) is supported for aten::randperm, got: ",
+                                        dtype_value);
         }
     } else {
         PYTORCH_OP_CONVERSION_CHECK(false, "Unexpected number of inputs for aten::randperm: ", num_inputs);
     }
-    if (n == 0) {
-        auto const_empty = std::make_shared<v0::Constant>(element::i64, Shape{0}, std::vector<int64_t>{});
-        return {context.mark_node(const_empty)};
-    }
-    auto shape = v0::Constant::create(element::i64, Shape{1}, {n});
+    auto axis_zero = v0::Constant::create(element::i64, Shape{1}, {0});
+    auto shape = context.mark_node(std::make_shared<v0::Unsqueeze>(n_node, axis_zero));
     auto min_val = v0::Constant::create(element::f32, Shape{}, {0.0f});
     auto max_val = v0::Constant::create(element::f32, Shape{}, {1.0f});
     auto random_tensor = context.mark_node(std::make_shared<v8::RandomUniform>(shape, min_val, max_val, element::f32));
     const int64_t axis = 0;
-    auto k = v0::Constant::create(element::i64, Shape{}, {n});
     auto topk = context.mark_node(std::make_shared<v11::TopK>(random_tensor,
-                                                              k,
+                                                              n_node,
                                                               axis,
                                                               ov::op::TopKMode::MIN,
                                                               ov::op::TopKSortType::SORT_VALUES,