[Tokenizers] add max_lengh parametrisation to encode (#1518)

Works in collaboration with tokenizers changes
openvinotoolkit/openvino_tokenizers#362
Ticket: CVS-157356, CVS-159924

src/README.md

@@ -398,6 +398,103 @@ print(f'Median from token to token duration: {np.median(durations):.2f} ms')
 
 For more examples of how metrics are used, please refer to the Python [benchmark_genai.py](../samples/python/text_generation/README.md) and C++ [benchmark_genai](../samples/cpp/text_generation/README.md) samples.
 
+### Tokenization
+
+OpenVINO™ GenAI provides a way to tokenize and detokenize text using the `ov::genai::Tokenizer` class. The `Tokenizer` is a high level abstraction over the OpenVINO Tokenizers library.
+
+It can be initialized from the path, in-memory IR representation or obtained from the `ov::genai::LLMPipeline` object.
+
+```cpp
+// Initialize from the path
+#include "openvino/genai/llm_pipeline.hpp"
+auto tokenizer = ov::genai::Tokenizer(models_path);
+
+// Get instance of Tokenizer from LLMPipeline.
+auto pipe = ov::genai::LLMPipeline pipe(models_path, "CPU");
+auto tokenzier = pipe.get_tokenizer();
+````
+
+```python
+import openvino_genai as ov_genai
+tokenizer = ov_genai.Tokenizer(models_path)
+
+# Or from LLMPipeline.
+pipe = ov_genai.LLMPipeline(models_path, "CPU")
+tokenizer = pipe.get_tokenizer()
+```
+
+`Tokenizer` has `encode` and `decode` methods which support the following arguments: `add_special_tokens`, `skip_special_tokens`, `pad_to_max_length`, `max_length` arguments.
+
+In order to disable adding special tokens do the followings, in C++:
+```cpp
+auto tokens = tokenizer.encode("The Sun is yellow because", ov::genai::add_special_tokens(false));
+```
+
+In Python:
+```python
+tokens = tokenizer.encode("The Sun is yellow because", add_special_tokens=False)
+```
+The `encode` method returns a `TokenizedInputs` object containing `input_ids` and `attention_mask`, both stored as ov::Tensor. Since ov::Tensor requires fixed-length sequences, padding is applied to match the longest sequence in a batch, ensuring a uniform shape. Also resulting sequence is truncated by `max_length`. If this value is not defined by used, it's is taken from the IR.
+
+Both padding and `max_length` can be controlled by the user. If `pad_to_max_length` is set to true, then instead of padding to the longest sequence it will be padded to the `max_length`.
+
+Below are example how padding can be controlled, in C++:
+```cpp
+#include "openvino/genai/llm_pipeline.hpp"
+auto tokenizer = ov::genai::Tokenizer(models_path);
+std::vector<std::string> prompts = {"The Sun is yellow because", "The"};
+
+// Since prompt is defenitely shorter than maximal length (which is taken from IR) will not affect shape.
+// Resulting shape is defined by length of the longest tokens sequence.
+// Equivalent of HuggingFace hf_tokenizer.encode(prompt, padding="longest", truncation=True)
+tokens = tokenizer.encode({"The Sun is yellow because", "The"})
+// or is equivalent to
+tokens = tokenizer.encode({"The Sun is yellow because", "The"}, ov::genai::pad_to_max_length(False))
+// out_shape: [2, 6]
+
+// Resulting tokens tensor will be padded to 1024.
+// Equivalent of HuggingFace hf_tokenizer.encode(prompt, padding="max_length", truncation=True, max_length=1024)
+tokens = tokenizer.encode({"The Sun is yellow because", 
+                           "The",
+                           std::string(2000, 'n')}, ov::genai::pad_to_max_length(True), ov::genai::max_length(1024))
+// out_shape: [3, 1024]
+
+// For single string prompts truncation and padding are also applied.
+tokens = tokenizer.encode({"The Sun is yellow because"}, ov::genai::pad_to_max_length(True), ov::genai::max_length(1024))
+// out_shape: [1, 128]
+```
+
+In Python:
+```python
+import openvino_genai as ov_genai
+
+tokenizer = ov_genai.Tokenizer(models_path)
+prompts = ["The Sun is yellow because", "The"]
+
+# Since prompt is defenitely shorter than maximal length (which is taken from IR) will not affect shape.
+# Resulting shape is defined by length of the longest tokens sequence.
+# Equivalent of HuggingFace hf_tokenizer.encode(prompt, padding="longest", truncation=True)
+tokens = tokenizer.encode(["The Sun is yellow because", "The"])
+# or is equivalent to
+tokens = tokenizer.encode(["The Sun is yellow because", "The"], pad_to_max_length=False)
+print(tokens.input_ids.shape)
+# out_shape: [2, 6]
+
+# Resulting tokens tensor will be padded to 1024, sequences which exceed this length will be truncated.
+# Equivalent of HuggingFace hf_tokenizer.encode(prompt, padding="max_length", truncation=True, max_length=1024)
+tokens = tokenizer.encode(["The Sun is yellow because", 
+                           "The"
+                           "The longest string ever" * 2000], pad_to_max_length=True, max_length=1024)
+print(tokens.input_ids.shape)
+# out_shape: [3, 1024]
+
+# For single string prompts truncation and padding are also applied.
+tokens = tokenizer.encode("The Sun is yellow because", pad_to_max_length=True, max_length=128)
+print(tokens.input_ids.shape)
+# out_shape: [1, 128]
+
+```
+
 ## How It Works
 
 For information on how OpenVINO™ GenAI works, refer to the [How It Works Section](./docs/HOW_IT_WORKS.md).

src/cpp/include/openvino/genai/tokenizer.hpp

@@ -107,15 +107,15 @@ class OPENVINO_GENAI_EXPORTS Tokenizer {
     /**
     * @brief encode a single prompt
     * @param prompt std::string with input prompt
-    * @param tokenization_params AnyMap with tokenization parameters, e.g. {"add_special_tokens", false}
+    * @param tokenization_params AnyMap with tokenization parameters, e.g. {{"add_special_tokens", false}, {"max_length", 128}}
     * @return pair of [input_ids, attention_mask]
     */
     TokenizedInputs encode(const std::string prompt, const ov::AnyMap& tokenization_params = {});
 
     /**
     * @brief encode batch of prompts. Left padding will be applied by default
     * @param prompts vector storing batch of prompts
-    * @param tokenization_params AnyMap with tokenization parameters, e.g. {"add_special_tokens", false}
+    * @param tokenization_params AnyMap with tokenization parameters, e.g. {{"add_special_tokens", false}, {"max_length", 128}}
     * @return pair of [input_ids, attention_mask]
     */
     TokenizedInputs encode(std::vector<std::string>& prompt, const ov::AnyMap& tokenization_params = {});
@@ -125,7 +125,9 @@ class OPENVINO_GENAI_EXPORTS Tokenizer {
     /**
     * @brief encode a single prompt
     * @param prompt std::string with input prompt
-    * @param properties tokenization properties, e.g. ov::genai::add_special_tokens(false)
+    * @param add_special_tokens whether to add special tokens
+    * @param max_length optional maximum length to which output will be truncated and/or padded. If not defined, taken from IR.
+    * @param pad_to_max_length either pad to max_length, or pad to the longest sequence in the batch. Default is false.
     * @return pair of [input_ids, attention_mask]
     */
     template <typename... Properties>
@@ -136,7 +138,9 @@ class OPENVINO_GENAI_EXPORTS Tokenizer {
     /**
     * @brief encode batch of prompts. Left padding will be applied by default
     * @param prompts vector storing batch of prompts
-    * @param properties tokenization properties, e.g. ov::genai::add_special_tokens(false)
+    * @param add_special_tokens whether to add special tokens
+    * @param max_length optional maximum length to which output will be truncated and/or padded. If not defined, taken from IR.
+    * @param pad_to_max_length either pad to max_length, or pad to the longest sequence in the batch. Default is false.
     * @return pair of [input_ids, attention_mask]
     */
     template <typename... Properties>
@@ -243,6 +247,7 @@ class OPENVINO_GENAI_EXPORTS Tokenizer {
 
 static constexpr ov::Property<bool> add_special_tokens{"add_special_tokens"};
 static constexpr ov::Property<bool> skip_special_tokens{"skip_special_tokens"};
+static constexpr ov::Property<bool> pad_to_max_length{"pad_to_max_length"};
 
 }  // namespace genai
 }  // namespace ov

src/cpp/src/make_tokenizer_stateful.cpp

@@ -4,6 +4,10 @@
 #include "make_tokenizer_stateful.hpp"
 #include "openvino/op/constant.hpp"
 #include "openvino/op/select.hpp"
+#include "openvino/op/maximum.hpp"
+#include "openvino/op/minimum.hpp"
+#include "openvino/op/add.hpp"
+#include "openvino/op/subtract.hpp"
 #include "openvino/op/slice.hpp"
 #include "openvino/op/multiply.hpp"
 #include "openvino/op/read_value.hpp"
@@ -13,7 +17,7 @@
 using namespace ov;
 using namespace ov::op;
 
-bool ov::genai::MakeCombineSegmentsSatateful::run_on_model(const std::shared_ptr<ov::Model>& model) {
+bool ov::genai::MakeAddSpecialTokensSatateful::run_on_model(const std::shared_ptr<ov::Model>& model) {
     std::shared_ptr<ov::Node> combine_seg_node;
     for (auto node: model->get_ordered_ops()) {
         if (strcmp(node->get_type_info().name, "CombineSegments") == 0) {
@@ -56,6 +60,7 @@ bool ov::genai::MakeCombineSegmentsSatateful::run_on_model(const std::shared_ptr
     return true;
 }
 
+
 bool ov::genai::MakeVocabDecoderSatateful::run_on_model(const std::shared_ptr<ov::Model>& model) {
     std::shared_ptr<ov::Node> vocab_decoder_node;
     for (auto node: model->get_ordered_ops()) {
@@ -97,3 +102,118 @@ bool ov::genai::MakeVocabDecoderSatateful::run_on_model(const std::shared_ptr<ov
     model->add_variables({variable});
     return true;
 }
+
+
+bool ov::genai::MakePaddingSatateful::run_on_model(const std::shared_ptr<ov::Model>& model) {
+    std::shared_ptr<ov::Node> combine_seg_node;
+    for (auto node: model->get_ordered_ops()) {
+        if (strcmp(node->get_type_info().name, "CombineSegments") == 0) {
+            combine_seg_node = node;
+        }
+    }
+    if (!combine_seg_node) { return false; }
+    auto num_comb = combine_seg_node->get_input_size();
+
+    size_t num_segments = (combine_seg_node->get_input_size() - 1) / 3;
+    size_t number_of_main_tokens_inputs = 0;
+    std::shared_ptr<Node> add_or_sub_node;
+    for (size_t i = 0; i < num_segments; i++) {
+        // Check all ends inputs of CombineSegments node.
+        // For special tokens they are Constant/Select, 
+        // for the ends input with main tokens sequence it's Add/Subtract.
+        // If  Add then it's a right truncation, if Subtract then it's a left truncation.
+        auto tmp_node = combine_seg_node->input_value(3*i + 1).get_node_shared_ptr();
+        if (ov::as_type_ptr<v1::Add>(tmp_node) || ov::as_type_ptr<v1::Subtract>(tmp_node)) {
+            number_of_main_tokens_inputs += 1;
+            add_or_sub_node = tmp_node;
+        }
+    }
+
+    // Exit if couldn't find main input or there are several.
+    if (number_of_main_tokens_inputs != 1) { return false; }
+
+    // Minimum between max_length and length of token sequence.
+    auto min_node = ov::as_type_ptr<v1::Minimum>(add_or_sub_node->get_input_node_shared_ptr(1));
+    if (!min_node) { return false; }
+
+    // constant containing final max_length - num_added tokens at the end of pipeline.
+    auto const_node = ov::as_type_ptr<v0::Constant>(min_node->get_input_node_shared_ptr(1));
+    if (!const_node) { return false; }
+
+    op::util::VariableInfo var_info{const_node->get_output_shape(0), const_node->get_output_element_type(0), MAX_LENGTH_VAR_ID};
+    auto variable_1 = std::make_shared<op::util::Variable>(var_info);
+
+    size_t num_added_tokens = num_segments - number_of_main_tokens_inputs;
+    // Constant which stores number of added_tokens.
+    auto num_added_tokens_const = std::make_shared<v0::Constant>(
+        const_node->get_output_element_type(0), const_node->get_output_shape(0), std::vector{num_added_tokens});
+
+    OPENVINO_ASSERT(const_node->get_element_type() == element::i32);
+    auto values = const_node->get_vector<int32_t>();
+    OPENVINO_ASSERT(values.size() == 1);
+    // Since const_node contain value = max_length - num_added tokens, 
+    size_t default_max_length = values[0] + num_added_tokens;
+
+    auto default_max_length_const = std::make_shared<v0::Constant>(
+        const_node->get_output_element_type(0), const_node->get_output_shape(0), std::vector{default_max_length});
+
+    // Save targets before adding new target with ReadValue to avoid recursion.
+    auto target_inputs = const_node->output(0).get_target_inputs();
+    auto max_length_rv = std::make_shared<v6::ReadValue>(default_max_length_const, variable_1);
+    auto subtract_node = std::make_shared<v1::Subtract>(max_length_rv, num_added_tokens_const);
+
+    for (auto target_input : target_inputs) {
+        target_input.replace_source_output(subtract_node->output(0));
+    }
+
+    // We need to check if user requested to not add special tokens.
+    std::shared_ptr<v6::ReadValue> read_value_spec_tokens;
+    for (const auto& sink : model->get_sinks()) {
+        // Check if sink accepts input from Assign, and if that't the case get the ReadValus node input.
+        if (auto read_value = ov::as_type_ptr<v6::ReadValue>(sink->get_input_node_shared_ptr(0))) {
+            if (read_value->get_variable()->get_info().variable_id == ADD_SPECIAL_TOKENS_VAR_ID) {
+                read_value_spec_tokens = read_value;
+                break;
+            }
+        }
+    }
+
+    // If user requested to not add special tokens in order to correctly calculate 
+    // truncation we need to enforce num_added_tokens to 0 regardless the hardcoded value of Constant.
+    if (read_value_spec_tokens && num_added_tokens_const) {
+        auto zero_constant = std::make_shared<v0::Constant>(ov::element::i32, ov::Shape{}, std::vector{0});
+        auto select_node = std::make_shared<v1::Select>(read_value_spec_tokens, num_added_tokens_const, zero_constant);
+        subtract_node->input(1).replace_source_output(select_node->output(0));
+    }
+
+    model->add_sinks({std::make_shared<v6::Assign>(max_length_rv, variable_1)});
+    model->add_variables({variable_1});
+
+    std::shared_ptr<ov::Node> ragged_to_dense_node;
+    for (auto node: model->get_ordered_ops()) {
+        if (strcmp(node->get_type_info().name, "RaggedToDense") == 0) {
+            ragged_to_dense_node = node;
+        }
+    }
+
+    if (!ragged_to_dense_node || ragged_to_dense_node->input_value(3).get_element_type() != ov::element::i32) {
+        return true;  // true since at this point we already have modified the graph.s
+    }
+
+    auto variable_2 = std::make_shared<op::util::Variable>(op::util::VariableInfo{ov::Shape{1}, ov::element::boolean, PAD_TO_LONGEST_VAR_ID});
+
+    // By default do not pad to max_length
+    auto default_false_const = std::make_shared<v0::Constant>(ov::element::boolean, ov::Shape{1}, std::vector{false});
+    auto pad_to_max_length_rv = std::make_shared<v6::ReadValue>(default_false_const, variable_2);
+
+    auto zero_constant = std::make_shared<v0::Constant>(ov::element::i32, ov::Shape{}, std::vector{0});
+    auto select_node = std::make_shared<v1::Select>(pad_to_max_length_rv, max_length_rv, zero_constant);
+
+    auto max_op = std::make_shared<v1::Maximum>(ragged_to_dense_node->input_value(3), select_node);
+    ragged_to_dense_node->input(3).replace_source_output(max_op->output(0));
+
+    model->add_sinks({std::make_shared<v6::Assign>(pad_to_max_length_rv, variable_2)});
+    model->add_variables({variable_2});
+
+    return true;
+}

src/cpp/src/make_tokenizer_stateful.hpp

@@ -3,6 +3,7 @@
 
 #include "openvino/op/constant.hpp"
 #include "openvino/pass/pass.hpp"
+#include "openvino/pass/matcher_pass.hpp"
 
 namespace ov {
 namespace genai {
@@ -32,9 +33,19 @@ namespace genai {
  *          |     CombineSegments     |
  *          +-------------------------+
 **/
-class MakeCombineSegmentsSatateful : public ov::pass::ModelPass {
+class MakeAddSpecialTokensSatateful : public ov::pass::ModelPass {
 public:
-    OPENVINO_MODEL_PASS_RTTI("MakeCombineSegmentsSatateful");
+    OPENVINO_MODEL_PASS_RTTI("MakeAddSpecialTokensSatateful");
+    bool run_on_model(const std::shared_ptr<ov::Model>& model) override;
+};
+
+/** 
+ * @brief This pass modifies tokenizer ov::Model so that inputs to RaggedToDense, CombineSegments 
+ * become modifiable during runtime so that padding can be controlled.
+ */
+class MakePaddingSatateful : public ov::pass::ModelPass {
+public:
+    OPENVINO_MODEL_PASS_RTTI("MakePaddingSatateful");
     bool run_on_model(const std::shared_ptr<ov::Model>& model) override;
 };
 
@@ -74,8 +85,10 @@ class MakeVocabDecoderSatateful : public ov::pass::ModelPass {
     bool run_on_model(const std::shared_ptr<ov::Model>& model) override;
 };
 
-const std::string ADD_SPECIAL_TOKENS_VAR_ID = "add_special_tokens";
-const std::string SKIP_SPECIAL_TOKENS_VAR_ID = "skip_special_tokens";
+inline const std::string ADD_SPECIAL_TOKENS_VAR_ID = "add_special_tokens";
+inline const std::string SKIP_SPECIAL_TOKENS_VAR_ID = "skip_special_tokens";
+inline const std::string MAX_LENGTH_VAR_ID = "max_length";
+inline const std::string PAD_TO_LONGEST_VAR_ID = "PAD_TO_LONGEST";
 
 } // namespace genai
 } // namespace ov