Merge branch 'master' into dynamic_kv_cache_allocation

.github/workflows/llm_bench-python.yml

@@ -151,7 +151,7 @@ jobs:
           rm -rf ./ov_models/internvl2-1B
       - name: WWB Tests
         run: |
-          pip install git+https://github.com/huggingface/optimum-intel.git
+          pip install git+https://github.com/huggingface/optimum-intel.git@420fa87d039425a906b7f755e4562b65947f016a
           GIT_CLONE_PROTECTION_ACTIVE=false PIP_PRE=1 PIP_EXTRA_INDEX_URL=https://storage.openvinotoolkit.org/simple/wheels/nightly pip install ${{ env.WWB_PATH }}
           python -m pytest -v ${{ env.WWB_PATH }}/tests
   stateful:
@@ -190,7 +190,7 @@ jobs:
       - name: WWB Tests
         run: |
           pip install pytest
-          pip install git+https://github.com/huggingface/optimum-intel.git
+          pip install git+https://github.com/huggingface/optimum-intel.git@420fa87d039425a906b7f755e4562b65947f016a
           GIT_CLONE_PROTECTION_ACTIVE=false PIP_PRE=1 PIP_EXTRA_INDEX_URL=https://storage.openvinotoolkit.org/simple/wheels/nightly pip install ${{ env.WWB_PATH }}
           python -m pytest -v ${{ env.WWB_PATH }}/tests
 

samples/export-requirements.txt

@@ -2,7 +2,7 @@
 --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/pre-release
 --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly
 openvino-tokenizers~=2025.0.0.0.dev
-optimum-intel @ git+https://github.com/huggingface/optimum-intel.git
+optimum-intel @ git+https://github.com/huggingface/optimum-intel.git@420fa87d039425a906b7f755e4562b65947f016a
 numpy<2.0.0; sys_platform == 'darwin'
 einops==0.8.0  # For Qwen
 transformers_stream_generator==0.0.5  # For Qwen

src/cpp/src/llm_pipeline_static.cpp

@@ -407,7 +407,8 @@ ov::genai::ModelConfigDesc get_modeldesc_from_json(const std::filesystem::path&
     if (config_data.contains("_name_or_path")) {
         desc.name_or_path = config_data["_name_or_path"].get<std::string>();
     }
-    desc.num_key_value_heads = config_data["num_key_value_heads"].get<int>();
+    desc.num_key_value_heads = config_data.contains("num_key_value_heads")
+        ? config_data["num_key_value_heads"].get<int>() : -1;
     return desc;
 }
 
@@ -1102,6 +1103,11 @@ EncodedResults StaticLLMPipeline::generate(
             m_kvcache_request.get_tensor(output_name).copy_to(kvcache_in_slice);
         }
     }
+
+    if (streamer_ptr) {
+        streamer_ptr->end();
+    }
+
     auto stop_time = std::chrono::steady_clock::now();
     // If is called without tokenization then that stat will not be reported.
     auto& metrics = results.perf_metrics;

src/cpp/src/lm_encoding.cpp

@@ -239,4 +239,4 @@ std::pair<EncodedResults, int32_t> get_lm_encoded_results(
 }
 
 }  // namespace genai
-}  // namespace ov
+}  // namespace ov

src/cpp/src/sampler.cpp

@@ -85,75 +85,63 @@ std::string clean_wrapped_text(const std::string& wrapped_text, const std::strin
     return clean_text;
 }
 
+std::vector<int64_t> encode_and_process_string(const std::string& stop_string, ov::genai::Tokenizer& tokenizer) {
+    // encode stop_string
+    std::string stop_string_copy = stop_string;
+    ov::Tensor ov_encoded_stop_string = tokenizer.encode(stop_string_copy, ov::genai::add_special_tokens(false)).input_ids;
+    size_t tensor_size = ov_encoded_stop_string.get_size();
+    std::vector<int64_t> encoded_stop_string(tensor_size);
+    std::copy_n(ov_encoded_stop_string.data<int64_t>(), tensor_size, encoded_stop_string.begin());
+    return encoded_stop_string;
+}
+
+struct MatchStopStringResult {
+    size_t to_remove = 0;
+    // int64_t last_token_id = 0;
+    // bool is_to_update_last_token = false;
+    bool is_matched = false;
+};
+
 // Return number of last tokens that match one of the stop_strings. If there's no match 0 is returned.
-int match_stop_string(Tokenizer & tokenizer, const TokenIds & generated_tokens, const std::set<std::string> & stop_strings) {
-    /*
-    For catching stop_string hit we run comparisons character-wise to catch cases where stop string 
-    overlaps with part of another token on both sides or is just a part of a single token. 
-    For every stop_string we iterate over generated tokens starting from the last one and going backwards. 
-    Every token is wrapped with prefix tokens to ensure tokenizer doesn't remove prefix whitespace of the actual token.
-    After that all tokens are decoded and prefix is removed from the decoded text, so we end up with decoded token.
-    Its characters are compared to the stop_string character at a current_position 
-    (position of a character in the stop_string counting from the last one) - at the beginning position is 0.
-    When characters match we increase current_position and check if we have a full match already, if not we continue.
-    If we have already matched some characters (current_position > 0) and next character is not matching 
-    before we reach the full match, then we reset current_position to 0. 
-    */ 
-    std::string prefix = "a";
-    auto prefix_ov = tokenizer.encode(prefix).input_ids;
-    std::vector<int64_t> prefix_tokens(prefix_ov.data<int64_t>(), prefix_ov.data<int64_t>() + prefix_ov.get_size());
-    std::string suffix = "b";
-    auto suffix_ov = tokenizer.encode(suffix).input_ids;
-    std::vector<int64_t> suffix_tokens(suffix_ov.data<int64_t>(), suffix_ov.data<int64_t>() + suffix_ov.get_size());
-
-    // Since whitespace can be added at the beginning of the suffix we also try to capture that behavior here
-    // and get suffix string that will actually be part of the decoded string so we can remove it correctly
-    auto wrapped_suffix_tokens = suffix_tokens;
-    wrapped_suffix_tokens.insert(wrapped_suffix_tokens.begin(), prefix_tokens.begin(), prefix_tokens.end());
-    std::string wrapped_suffix = tokenizer.decode(wrapped_suffix_tokens);
-    auto wrapper_pos = wrapped_suffix.find(prefix);
-    suffix = wrapped_suffix.substr(wrapper_pos + prefix.size());
-
-    for (auto stop_string: stop_strings) {
-        int current_position = 0;
-        int num_matched_tokens = 0; 
-        // Getting reverse iterator to check tokens starting from the last one generated and going backwards
-        auto generated_tokens_rit = generated_tokens.rbegin();
-        std::vector<int64_t> tokens_buffer;
-        while (generated_tokens_rit != generated_tokens.rend()) {
-            num_matched_tokens++;
-            tokens_buffer.insert(tokens_buffer.begin(), *generated_tokens_rit);
-
-            std::vector<int64_t> wrapped_tokens = wrap_tokens(tokens_buffer, prefix_tokens, suffix_tokens);
-            std::string wrapped_text = tokenizer.decode(wrapped_tokens);
-            std::string clean_text = clean_wrapped_text(wrapped_text, prefix, suffix);
-
-            if (clean_text == "" || (clean_text.size() >= 3 && (clean_text.compare(clean_text.size() - 3, 3, "�") == 0))) { 
-                generated_tokens_rit++;
-                continue;
-            } else {
-                tokens_buffer.clear();
-            }
-            // Checking clean_text characters starting from the last one
-            for (auto clean_text_rit = clean_text.rbegin(); clean_text_rit != clean_text.rend(); clean_text_rit++) {
-                // On character match increment current_position for the next comparisons
-                if (*clean_text_rit == *(stop_string.rbegin() + current_position)) {
-                    current_position++;
-                    // If this is the last character from the stop_string we have a match
-                    if ((stop_string.rbegin() + current_position) == stop_string.rend()) {
-                        return num_matched_tokens;
-                    } 
-                } else if (current_position) {
-                    // Already found matching characters, but the last one didn't match, so we reset current_position
-                    current_position = 0;
-                    // Looking for the match will start over from this character so we decrement iterator
-                    clean_text_rit--;
+MatchStopStringResult match_stop_string(Tokenizer& tokenizer,
+                      const TokenIds& generated_tokens,
+                      const std::pair<size_t, std::set<std::string>>& stop_strings,
+                      bool is_include_to_output) {
+    MatchStopStringResult result;
+    if (generated_tokens.size() >= stop_strings.first) {
+        size_t offset = generated_tokens.size() - stop_strings.first;
+        TokenIds buffer(generated_tokens.begin() + offset, generated_tokens.end());
+        std::string decoded_buffer = tokenizer.decode(buffer);
+        for (const auto& stop_string : stop_strings.second) {
+            auto pos = decoded_buffer.find(stop_string);
+            if (pos != std::string::npos) {
+                result.is_matched = true;
+
+                auto stop_string_len = is_include_to_output ? stop_string.length() : 0;
+                decoded_buffer = decoded_buffer.substr(0, pos + stop_string_len);
+                // to remove word splitting symbols from tail
+                while (decoded_buffer.back() == ' ' || decoded_buffer.back() == '\n') {
+                    decoded_buffer.pop_back();
+                }
+                if (decoded_buffer.empty()) {
+                    result.to_remove = buffer.size();
+                    return result;
                 }
+
+                // find token cnt to be removed from sequence by decoding token by token
+                std::string decoded_partially_string = "";
+                for (size_t i = 0; i < buffer.size(); ++i) {
+                    decoded_partially_string += tokenizer.decode(TokenIds{buffer[i]});
+                    if (decoded_partially_string.find(decoded_buffer) != std::string::npos) {
+                        result.to_remove = buffer.size() - i - 1;
+                        break;
+                    }
+                }
+                return result;
             }
-            generated_tokens_rit++;
         }
     }
-    return 0;
+    return result;
 }
 
 // Return number of last tokens that match one of the stop_strings. If there's no match 0 is returned.
@@ -245,7 +233,9 @@ std::map<size_t, int32_t> Sampler::GroupBeamSearcher::get_beam_idxs() {
     return next_beams;
 }
 
-void Sampler::GroupBeamSearcher::select_next_tokens(const ov::Tensor& logits, SamplerOutput& sampler_output) {
+void Sampler::GroupBeamSearcher::select_next_tokens(const ov::Tensor& logits,
+    SamplerOutput& sampler_output,
+    const std::pair<size_t, std::set<std::string>>& stop_strings) {
     assert(m_parameters.num_beams % m_parameters.num_beam_groups == 0 &&
         "number of beams should be divisible by number of groups");
     size_t group_size = m_parameters.num_beams / m_parameters.num_beam_groups;
@@ -392,19 +382,17 @@ void Sampler::GroupBeamSearcher::select_next_tokens(const ov::Tensor& logits, Sa
                 // There's probably a better way to do that, than copying whole vector...
                 std::vector<int64_t> token_ids = candidate.m_sequence->get_generated_ids();
                 token_ids.push_back(candidate.m_token_id);
-                int num_last_matched_tokens = match_stop_string(m_tokenizer, token_ids, m_sequence_group->get_sampling_parameters().stop_strings);
-                if (num_last_matched_tokens) {
+                auto match_result = match_stop_string(m_tokenizer, token_ids, stop_strings, m_parameters.include_stop_str_in_output);
+                if (match_result.is_matched) {
                     // If beam_token does not belong to top num_beams tokens, it should not be added
                     if (cand_idx >= group_size)
                         continue;
 
-                    if(!m_parameters.include_stop_str_in_output) {
-                        // remove tokens that match stop_string from output (last token is not included in candidate.m_sequence at this point)
-                        candidate.m_sequence->remove_last_tokens(num_last_matched_tokens - 1);
-                    }
+                    // remove tokens that match stop_string from output (last token is not included in candidate.m_sequence at this point)
+                    candidate.m_sequence->remove_last_tokens(match_result.to_remove);
 
                     // try to finish candidate
-                    try_to_finish_candidate(group, candidate, m_parameters.include_stop_str_in_output);
+                    try_to_finish_candidate(group, candidate);
                     continue;
                 }
             }
@@ -576,10 +564,11 @@ std::vector<int64_t> Sampler::_try_finish_generation(SequenceGroup::Ptr & sequen
         }
 
         if (!sampling_params.stop_strings.empty()) {
-            int num_matched_last_tokens = match_stop_string(m_tokenizer, running_sequence->get_generated_ids(), sampling_params.stop_strings);
-            if (num_matched_last_tokens) {
-                if (!sampling_params.include_stop_str_in_output)
-                    running_sequence->remove_last_tokens(num_matched_last_tokens);
+            auto& stop_strings = m_stop_strings.at(sequence_group->get_request_id());
+            auto match_result = match_stop_string(m_tokenizer, running_sequence->get_generated_ids(), stop_strings, sampling_params.include_stop_str_in_output);
+            if (match_result.is_matched) {
+                running_sequence->remove_last_tokens(match_result.to_remove);
+
                 running_sequence->set_status(SequenceStatus::FINISHED);
                 running_sequence->set_finish_reason(GenerationFinishReason::STOP);
                 dropped_seq_ids.push_back(running_sequence->get_id());
@@ -741,6 +730,19 @@ float get_p_prime(Sequence::Ptr& running_sequence,
     return p_prime;
 }
 
+std::pair<size_t, std::set<std::string>>
+process_stop_strings(const std::set<std::string>& stop_strings, Tokenizer& tokenizer) {
+    std::pair<size_t, std::set<std::string>> result;
+    for (const auto& stop_string : stop_strings) {
+        auto encoded_stop_string = encode_and_process_string(stop_string, tokenizer);
+        if (result.first < encoded_stop_string.size()) {
+            result.first = encoded_stop_string.size();
+        }
+        result.second.insert(stop_string);
+    }
+    return result;
+}
+
 SamplerOutput Sampler::sample(std::vector<SequenceGroup::Ptr> & sequence_groups,
                               ov::Tensor logits,
                               bool is_validation_mode_enabled) {
@@ -764,6 +766,12 @@ SamplerOutput Sampler::sample(std::vector<SequenceGroup::Ptr> & sequence_groups,
         if (!m_logit_processors.count(request_id)) {
             m_logit_processors.insert({request_id, LogitProcessor(sampling_params, sequence_group->get_prompt_ids())});
         }
+        if (!m_stop_strings.count(request_id)) {
+            auto processed_stop_string = process_stop_strings(sampling_params.stop_strings, m_tokenizer);
+            m_stop_strings.insert({request_id, processed_stop_string});
+            sequence_group->set_stream_window_size(processed_stop_string.first);
+        }
+        auto& stop_strings = m_stop_strings.at(request_id);
         auto& logit_processor = m_logit_processors.at(request_id);
         const void * sequence_group_logits_data = logits_data + vocab_size * currently_processed_tokens;
         ov::Tensor sequence_group_logits(ov::element::f32, ov::Shape{num_running_sequences, actual_seq_len, vocab_size}, (void *)sequence_group_logits_data);
@@ -873,7 +881,7 @@ SamplerOutput Sampler::sample(std::vector<SequenceGroup::Ptr> & sequence_groups,
                 }
 
                 // current algorithm already adds new tokens to running sequences and
-                m_beam_search_info.at(request_id).select_next_tokens(sequence_group_logits, sampler_output);
+                m_beam_search_info.at(request_id).select_next_tokens(sequence_group_logits, sampler_output, stop_strings);
 
                 // check max length stop criteria
                 std::vector<Sequence::Ptr> running_sequences = sequence_group->get_running_sequences();
@@ -886,8 +894,7 @@ SamplerOutput Sampler::sample(std::vector<SequenceGroup::Ptr> & sequence_groups,
             // Notify handle after sampling is done. 
             // For non-streaming this is effective only when the generation is finished.
             OPENVINO_ASSERT(num_tokens_to_process >= max_removed_tokens_per_request);
-            size_t num_output_token_to_push = num_tokens_to_process - max_removed_tokens_per_request + 1;
-            sequence_group->notify_handle(num_output_token_to_push);
+            sequence_group->notify_handle();
         } else {
             // we are in prompt processing phase when prompt is split into chunks and processed step by step
         }
@@ -926,6 +933,7 @@ void Sampler::create_logit_processor(uint64_t request_id, const GenerationConfig
 void Sampler::clear_request_info(uint64_t request_id) { 
     m_beam_search_info.erase(request_id);
     m_logit_processors.erase(request_id);
+    m_stop_strings.erase(request_id);
 }
 
 int64_t Sampler::GroupBeamSearcher::Group::finish(Beam beam, const ov::genai::GenerationConfig& sampling_params) {

src/cpp/src/sampler.hpp

@@ -58,6 +58,8 @@ class Sampler {
     size_t seed = rng_engine.default_seed;
     // { request_id, logit_processor }
     std::map<uint64_t, LogitProcessor> m_logit_processors;
+    // { request_id, { max_encoded_len, { stop_strings }}}
+    std::map<int64_t, std::pair<size_t, std::set<std::string>>> m_stop_strings;
 
     Tokenizer m_tokenizer;
 
@@ -120,7 +122,7 @@ class Sampler::GroupBeamSearcher {
 public:
     explicit GroupBeamSearcher(SequenceGroup::Ptr sequence_group, Tokenizer tokenizer);
 
-    void select_next_tokens(const ov::Tensor& logits, SamplerOutput& sampler_output);
+    void select_next_tokens(const ov::Tensor& logits, SamplerOutput& sampler_output, const std::pair<size_t, std::set<std::string>>& stop_strings);
     void finalize(SamplerOutput& sampler_output);
     std::map<size_t, int32_t> get_beam_idxs();
 };