[TRANSFORMATIONS] Fix sliding window handling for gpt-oss in SDPAToPA (#32939)

It was observed that the initial implementation of sliding window
handling for gpt-oss was incorrect and instead of using the real sliding
window value, the 0 stub was always used.

* Fix the pattern that captures the real subgraph in the model and
extracts the real sliding window value.
* Fix the test that was implemented based on the incorrect
post-transformation graph.

Tickets:
[CVS-176323](https://jira.devtools.intel.com/browse/CVS-176323)

Signed-off-by: Andrii Staikov
[[email protected]](mailto:[email protected])

Signed-off-by: Andrii Staikov <[email protected]>

Author: CuriousPanCake

src/common/transformations/src/transformations/sdpa_to_paged_attention/state_management_pattern.cpp

@@ -207,22 +207,19 @@ static std::tuple<std::shared_ptr<ov::Node>, std::shared_ptr<ov::Node>> gpt_oss_
     auto q_idx = pattern::any_input();
     auto kv_idx = pattern::any_input();
 
-    auto kv_idx_opt_conv_0 = pattern::optional<v0::Convert>();
-    auto kv_idx_opt_conv_1 = pattern::optional<v0::Convert>(kv_idx_opt_conv_0);
-    auto less_eq = pattern::wrap_type<v1::LessEqual>({q_idx, kv_idx_opt_conv_1});
+    auto kv_idx_opt_conv = pattern::optional<v0::Convert>(kv_idx);
 
     auto offset = wrap_type<v0::Constant>();
 
     auto add = wrap_type<v1::Add>({q_idx, offset});
-    auto opt_conv_2 = pattern::optional<v0::Convert>(add);
-    auto greater = pattern::wrap_type<v1::Greater>({kv_idx_opt_conv_1, opt_conv_2});
+    auto greater = pattern::wrap_type<v1::Greater>({kv_idx_opt_conv, add});
     auto bitwise_and = pattern::wrap_type<v13::BitwiseAnd>({any_input(), greater});
     auto bitwise_and_1 = pattern::wrap_type<v13::BitwiseAnd>({bitwise_and, any_input()});
     auto bitwise_and_2 = pattern::wrap_type<v13::BitwiseAnd>({any_input(), bitwise_and_1});
     auto bitwise_and_3 = pattern::wrap_type<v13::BitwiseAnd>({bitwise_and_2, any_input()});
     auto broadcast = pattern::wrap_type<v3::Broadcast>({bitwise_and_3, any_input()});
     auto select = pattern::wrap_type<v1::Select>({broadcast, any_input(), any_input()});
-    auto mask = pattern::wrap_type<v1::StridedSlice>({select, any_input(), any_input(), any_input()});
+    auto mask = pattern::wrap_type<v8::Slice>({select, any_input(), any_input(), any_input(), any_input()});
 
     return {mask, offset};
 }

src/common/transformations/tests/op_conversions/sdpa_to_paged_attention_test.cpp

@@ -2646,8 +2646,11 @@ TEST_F(SDPAToPATest, SDPAToPA_gpt_oss_General) {
                                     }),
                                     MOCK_VALUE);
 
-        auto scale = v0::Constant::create(element::f32, {}, {0.125000f});
-        auto sliding_window = v0::Constant::create(element::i32, {}, {0});
+        auto sliding_window_neg = makeConst(element::f32, ov::Shape({1, 1, 1, 1}), {-128.0f});
+        auto Squeeze2 = makeOP<v15::Squeeze>({sliding_window_neg}, {{"allow_axis_skip", false}});
+        auto Convert16 = makeOP<v0::Convert>({Squeeze2}, {{"destination_type", "i32"}});
+        auto sliding_window = makeOP<v1::Multiply>({Convert16, -1}, {{"auto_broadcast", "numpy"}});
+        auto scale = v0::Constant::create(element::f32, {}, {0.1250f});
         auto alibi_slopes_stub = v0::Constant::create(element::f32, Shape{0}, {});
         auto PagedAttentionExtension =
             std::make_shared<ov::op::PagedAttentionExtension>(OutputVector{Reshape1,