Port SDPA to PagedAttention transformation (openvinotoolkit#24336)

### Details:
Ported SDPA to PagedAttention transformation from python to C++ code.

the related PRs:
openvinotoolkit#24127
openvinotoolkit#24177

Tested model scope:
- [x]          "hf-internal-testing/tiny-random-BloomForCausalLM",
- [x]          "hf-internal-testing/tiny-random-FalconForCausalLM",
- [x]          "hf-internal-testing/tiny-random-Starcoder2ForCausalLM",
- [x]          "hf-internal-testing/tiny-random-GPTJForCausalLM",
- [x]          "hf-internal-testing/tiny-random-StableLmForCausalLM",
- [x]          "hf-internal-testing/tiny-random-LlamaForCausalLM",
- [x]          "hf-internal-testing/tiny-random-MistralForCausalLM",
- [x]          "hf-internal-testing/tiny-random-OPTForCausalLM",
- [x]          "hf-internal-testing/tiny-random-PhiForCausalLM",
- [x]          "hf-internal-testing/tiny-random-StableLmForCausalLM",
- [x]          "facebook/opt-125m",
- [x]          "llama2",
- [x]          "bigcode/starcoder2-7b"
- [ ] "mosaicml/mpt-7b-chat" (FAILED both py/c++) - acceptable for this
PR
Issue: RuntimeError: Check '(axis_range_min <= axis) && (axis <=
axis_range_max)' failed at src/core/src/validation_util.cpp:386:
Concat Parameter axis 2 out of the tensor rank range [0, 0].
- [x] _means, that the response to the dedicated prompt is the same for
the py and c++ transformations._




### Tickets:
 - *CVS-138664*

---------

Co-authored-by: Sergey Lyalin <sergey.lyalin@intel.com>
Co-authored-by: Andrii Staikov <andrii.staikov@intel.com>

Author: 3 people

src/bindings/python/src/openvino/_offline_transformations/__init__.py

@@ -17,3 +17,4 @@
 from openvino._pyopenvino._offline_transformations import compress_model_transformation
 from openvino._pyopenvino._offline_transformations import compress_quantize_weights_transformation
 from openvino._pyopenvino._offline_transformations import convert_sequence_to_tensor_iterator_transformation
+from openvino._pyopenvino._offline_transformations import paged_attention_transformation

src/bindings/python/src/pyopenvino/core/offline_transformations.cpp

@@ -8,6 +8,7 @@
 
 #include <compress_quantize_weights.hpp>
 #include <openvino/pass/make_stateful.hpp>
+#include <openvino/pass/sdpa_to_paged_attention.hpp>
 #include <openvino/pass/serialize.hpp>
 #include <pruning.hpp>
 #include <transformations/common_optimizations/compress_float_constants.hpp>
@@ -127,4 +128,13 @@ void regmodule_offline_transformations(py::module m) {
             manager.run_passes(model);
         },
         py::arg("model"));
+
+    m_offline_transformations.def(
+        "paged_attention_transformation",
+        [](std::shared_ptr<ov::Model> model) {
+            ov::pass::Manager manager;
+            manager.register_pass<ov::pass::SDPAToPagedAttention>();
+            manager.run_passes(model);
+        },
+        py::arg("model"));
 }

src/bindings/python/src/pyopenvino/graph/ops/paged_attention_extension.cpp

@@ -5,162 +5,13 @@
 #include "pyopenvino/graph/ops/paged_attention_extension.hpp"
 
 #include "openvino/op/op.hpp"
+#include "openvino/op/paged_attention.hpp"
 #include "pyopenvino/core/common.hpp"
 
 namespace py = pybind11;
 
-namespace {
-
-// This is an experimental operation that is implemented in the plugins.
-// Do not use in user applications, backward compatibility is not guaranteed in future releases.
-class PagedAttentionExtension : public ov::op::Op {
-public:
-    OPENVINO_OP("PagedAttentionExtension");
-
-    PagedAttentionExtension(const ov::OutputVector& args) : ov::op::Op(args) {
-        constructor_validate_and_infer_types();
-    }
-
-    void validate_and_infer_types() override {
-        auto value_cache_shape = get_input_partial_shape(4);
-        // m_num_kv_heads = value_cache_shape[1];
-        // m_head_size = value_cache_shape[2];
-        // m_block_size = value_cache_shape[3];
-        NODE_VALIDATION_CHECK(this, value_cache_shape.size() == 4, "Value cache shape must be 4 dims");
-
-        // key_cache: shape [num_blocks, num_kv_heads, head_size/x, block_size, x]
-        auto key_cache_shape = get_input_partial_shape(3);
-        NODE_VALIDATION_CHECK(this,
-                              value_cache_shape.size() == 4,
-                              // value_cache_shape[0] == key_cache_shape[0] && // num_blocks
-                              // key_cache_shape[1] == m_num_kv_heads &&
-                              // key_cache_shape[2] * key_cache_shape[4] == m_head_size &&
-                              // m_block_size == key_cache_shape[3], // block_size,
-                              "Key cache shape must be 4 dims");
-
-        // query: shape [batch_size, seq_len, num_heads * head_size]
-        auto query_type = get_input_element_type(0);
-        auto query_shape = get_input_partial_shape(0);
-        NODE_VALIDATION_CHECK(
-            this,
-            // query_type.is_real() &&
-            query_shape.size() == 3,
-            // query_shape[2] == m_num_heads * m_head_size,
-            "Query type must be real, shape must be like [batch_size, seq_len, num_heads * head_size]. ",
-            "Got element type ",
-            query_type,
-            ", shape ",
-            query_shape);
-
-        // key: shape [batch_size, seq_len, num_kv_heads * head_size]
-        auto key_type = get_input_element_type(1);
-        auto key_shape = get_input_partial_shape(1);
-        NODE_VALIDATION_CHECK(this,
-                              // query_type == key_type &&
-                              key_shape.size() == 3,
-                              "Key type must be the same as query, shape must be the same as query. "
-                              "Got element type ",
-                              key_type,
-                              ", shape ",
-                              key_shape);
-
-        // value: shape [batch_size, seq_len, num_kv_heads * head_size]
-        // auto value_type = get_input_element_type(2);
-        auto value_shape = get_input_partial_shape(2);
-
-        // is_prompt: boolean scalar
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(5) == ov::element::boolean &&
-                              get_input_shape(5) == ov::Shape({}),
-                              "is_prompt validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(5),
-                              ", shape ",
-                              get_input_shape(5));
-
-        // slot_mapping: shape [batch_size, max_context_len]
-        auto slot_mapping_shape = get_input_partial_shape(6);
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(6) == ov::element::i64 &&
-                              slot_mapping_shape.size() == 2,
-                              "slot_mapping validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(6),
-                              ", shape ",
-                              slot_mapping_shape);
-
-        // max_context_len: integer scalar
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(7) == ov::element::i32 &&
-                              get_input_shape(7) == ov::Shape({}),
-                              "max_context_len validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(7),
-                              ", shape ",
-                              get_input_shape(7));
-
-        // context_lens: shape [batch_size]
-        auto context_lens_shape = get_input_partial_shape(8);
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(8) == ov::element::i32 &&
-                              context_lens_shape.size() == 1,
-                              "context_lens validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(8),
-                              ", shape ",
-                              context_lens_shape);
-
-        // block_tables: shape [batch_size, max_block_per_request]
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(9) == ov::element::i32 &&
-                              get_input_partial_shape(9).size() == 2,
-                              "block_tables validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(9),
-                              ", shape ",
-                              get_input_partial_shape(9));
-
-        // scale: float scalar
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(10) == ov::element::f32 &&
-                              get_input_shape(10) == ov::Shape({}),
-                              "block_tables validation failed. ",
-                              "Got element type ",
-                              get_input_element_type(10),
-                              ", shape ",
-                              get_input_shape(10));
-
-        // alibi_slopes: 1D float tensor
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(11) == ov::element::f32 &&
-                              get_input_partial_shape(11).rank().get_length() == 1,
-                              "alibi_slopes should be a 1D float tensor. ",
-                              "Got element type ",
-                              get_input_element_type(11),
-                              ", shape ",
-                              get_input_partial_shape(11));
-
-        // sliding_window: int scalar
-        NODE_VALIDATION_CHECK(this,
-                              // get_input_element_type(12) == ov::element::i32 &&
-                              get_input_partial_shape(12).rank().get_length() == 0,
-                              "sliding_window argument should be an i32 scalar. ",
-                              "Got element type ",
-                              get_input_element_type(12),
-                              ", shape ",
-                              get_input_partial_shape(12));
-
-        set_output_type(0, query_type, query_shape);
-    }
-
-    std::shared_ptr<ov::Node> clone_with_new_inputs(const ov::OutputVector& new_args) const override {
-        return std::make_shared<PagedAttentionExtension>(new_args);
-    }
-};
-
-}  // namespace
-
 void regclass_graph_op_PagedAttentionExtension(py::module m) {
+    using ov::op::PagedAttentionExtension;
     py::class_<PagedAttentionExtension, std::shared_ptr<PagedAttentionExtension>, ov::Node> cls(
         m,
         "_PagedAttentionExtension");

src/common/transformations/include/transformations/sdpa_to_paged_attention/position_ids_replacer.hpp

@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/cc/pass/itt.hpp"
+#include "openvino/op/add.hpp"
+#include "openvino/op/parameter.hpp"
+#include "openvino/pass/graph_rewrite.hpp"
+#include "openvino/pass/pattern/op/wrap_type.hpp"
+#include "transformations/utils/utils.hpp"
+#include "transformations_visibility.hpp"
+
+namespace ov {
+namespace pass {
+
+class PositionIDsReplacer;
+
+}  // namespace pass
+}  // namespace ov
+
+class ov::pass::PositionIDsReplacer : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("PositionIDsReplacer", "0");
+    explicit PositionIDsReplacer(const std::shared_ptr<Output<Node>>& position_ids);
+};

src/common/transformations/include/transformations/sdpa_to_paged_attention/prev_sequence_length_pattern.hpp

@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/cc/pass/itt.hpp"
+#include "openvino/op/shape_of.hpp"
+#include "openvino/op/subtract.hpp"
+#include "openvino/pass/graph_rewrite.hpp"
+#include "openvino/pass/pattern/op/wrap_type.hpp"
+#include "transformations/utils/utils.hpp"
+#include "transformations_visibility.hpp"
+
+namespace ov {
+namespace pass {
+
+class PrevSequenceLengthPattern;
+
+}  // namespace pass
+}  // namespace ov
+
+class ov::pass::PrevSequenceLengthPattern : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("PrevSequenceLengthPattern", "0");
+    explicit PrevSequenceLengthPattern(const std::shared_ptr<ov::op::v1::Subtract>& prev_max_seq_len);
+};

src/common/transformations/include/transformations/sdpa_to_paged_attention/state_management_pattern.hpp

@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/pass/graph_rewrite.hpp"
+#include "transformations_visibility.hpp"
+
+namespace ov {
+namespace pass {
+
+class StateManagementPattern;
+
+}  // namespace pass
+}  // namespace ov
+
+class ov::pass::StateManagementPattern : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("StateManagementPattern", "0");
+    StateManagementPattern(ParameterVector& kv_parameters,
+                           const ParameterVector& model_remaining_params,
+                           const std::shared_ptr<ov::op::v0::Constant>& sliding_window,
+                           ParameterVector& parameters_to_remove,
+                           NodeVector& assignes_to_remove,
+                           int& layer_index);
+};

src/common/transformations/include/transformations/sdpa_to_paged_attention/total_sequence_length_pattern.hpp

@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "openvino/cc/pass/itt.hpp"
+#include "openvino/op/concat.hpp"
+#include "openvino/op/parameter.hpp"
+#include "openvino/pass/graph_rewrite.hpp"
+#include "openvino/pass/pattern/op/wrap_type.hpp"
+#include "transformations/utils/utils.hpp"
+#include "transformations_visibility.hpp"
+
+namespace ov {
+namespace pass {
+
+class TotalSequenceLengthPattern;
+
+}  // namespace pass
+}  // namespace ov
+
+class ov::pass::TotalSequenceLengthPattern : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("TotalSequenceLengthPattern", "0");
+    explicit TotalSequenceLengthPattern(const std::shared_ptr<ov::op::v0::Parameter>& max_context_len);
+};

src/common/transformations/src/transformations/sdpa_to_paged_attention/position_ids_replacer.cpp

@@ -0,0 +1,39 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/sdpa_to_paged_attention/position_ids_replacer.hpp"
+
+#include "openvino/cc/pass/itt.hpp"
+#include "openvino/op/gather.hpp"
+#include "openvino/pass/pattern/op/wrap_type.hpp"
+#include "transformations/utils/utils.hpp"
+
+using namespace ov::op;
+
+// TODO: Instead of using the following transformation that matches quite a specific place in a model graph in case when
+// position_ids parameter is missing, consider replacing always existing attention_mask parameter with a sub-graph using
+// a new slot_mapping parameter.
+ov::pass::PositionIDsReplacer::PositionIDsReplacer(const std::shared_ptr<Output<Node>>& position_ids) {
+    MATCHER_SCOPE(PositionIDsReplacer);
+
+    auto input_ids = pattern::any_input();
+    auto input_embed = pattern::wrap_type<v8::Gather>({pattern::any_input(), input_ids, pattern::any_input()});
+
+    auto position_ids_pattern = pattern::any_input();
+    auto offset = pattern::wrap_type<v0::Constant>();
+    auto add_offset = pattern::wrap_type<v1::Add>({position_ids_pattern, offset});
+    auto convert = pattern::wrap_type<v0::Convert>({add_offset});
+    auto position_embed = pattern::wrap_type<v8::Gather>({pattern::any_input(), convert, pattern::any_input()});
+
+    auto add = pattern::wrap_type<v1::Add>({input_embed, position_embed});
+
+    ov::matcher_pass_callback callback = [=](ov::pass::pattern::Matcher& m) {
+        const auto& pattern_map = m.get_pattern_value_map();
+        replace_node(pattern_map.at(position_ids_pattern).get_node_shared_ptr(), position_ids->get_node_shared_ptr());
+        return true;
+    };
+
+    auto m = std::make_shared<ov::pass::pattern::Matcher>(add, matcher_name);
+    register_matcher(m, callback);
+}

src/common/transformations/src/transformations/sdpa_to_paged_attention/prev_sequence_length_pattern.cpp

@@ -0,0 +1,41 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/sdpa_to_paged_attention/prev_sequence_length_pattern.hpp"
+
+#include "openvino/cc/pass/itt.hpp"
+#include "openvino/op/gather.hpp"
+#include "openvino/op/shape_of.hpp"
+#include "openvino/pass/pattern/op/wrap_type.hpp"
+#include "transformations/utils/utils.hpp"
+
+using namespace ov::op;
+
+ov::pass::PrevSequenceLengthPattern::PrevSequenceLengthPattern(
+    const std::shared_ptr<ov::op::v1::Subtract>& prev_max_seq_len) {
+    MATCHER_SCOPE(PrevSequenceLengthPattern);
+
+    auto kv_past = pattern::wrap_type<v6::ReadValue>({pattern::any_input()});
+    auto kv_gather = pattern::wrap_type<v8::Gather>({kv_past, pattern::any_input(), pattern::any_input()});
+    auto kv_shape = pattern::wrap_type<v3::ShapeOf>({kv_gather});
+    auto seq = pattern::wrap_type<v8::Gather>({kv_past, pattern::any_input(), pattern::any_input()});
+
+    ov::matcher_pass_callback callback = [=](ov::pass::pattern::Matcher& m) {
+        // TODO: Check that seq has axis that really takes sequence len but not any other dimension -- use symbolics or
+        // look at the constant input
+        auto gather = m.get_match_root();
+        auto target_type = gather->get_output_element_type(0);
+        std::shared_ptr<Node> replacement;
+        if (prev_max_seq_len->get_output_element_type(0) != target_type) {
+            replacement = std::make_shared<v0::Convert>(prev_max_seq_len, target_type);
+        } else {
+            replacement = prev_max_seq_len;
+        }
+        replace_node(gather, replacement);
+        return true;
+    };
+
+    auto m = std::make_shared<ov::pass::pattern::Matcher>(seq, matcher_name);
+    register_matcher(m, callback);
+}