test: add a new step test

examples/server/tests/features/embeddings.feature

@@ -23,6 +23,13 @@ Feature: llama.cpp server
     """
     Then embeddings are generated
 
+  Scenario: Tokenize / Detokenize complex
+    When tokenizing:
+    """
+    España is a èspciâl café über naïve résumé cañón élite cañas Barça 例子 東京 こんにちは 你好 中国
+    """
+    Then tokens can be detokenize and is equivalent False
+
   Scenario: OAI Embeddings compatibility
     Given a model bert-bge-small
     When an OAI compatible embeddings computation request for:

examples/server/tests/features/server.feature

@@ -91,7 +91,7 @@ Feature: llama.cpp server
     """
     What is the capital of France ?
     """
-    Then tokens can be detokenize
+    Then tokens can be detokenize and is equivalent True
 
   Scenario: Models available
     Given available models

examples/server/tests/features/steps/steps.py

@@ -670,9 +670,10 @@ async def step_tokenize(context):
             context.tokens = tokenize_json['tokens']
 
 
-@step('tokens can be detokenize')
+@step('tokens can be detokenize and is equivalent {equivalent}')
 @async_run_until_complete
-async def step_detokenize(context):
+async def step_detokenize(context, equivalent):
+    equivalent = equivalent == 'True'
     assert len(context.tokens) > 0
     async with aiohttp.ClientSession() as session:
         async with session.post(f'{context.base_url}/detokenize',
@@ -682,9 +683,9 @@ async def step_detokenize(context):
             assert response.status == 200
             detokenize_json = await response.json()
             # SPM tokenizer adds a whitespace prefix: https://github.com/google/sentencepiece/issues/15
+            if equivalent:
                 assert context.tokenized_text == detokenize_json['content'].strip()
 
-
 @step('an OPTIONS request is sent from {origin}')
 @async_run_until_complete
 async def step_options_request(context, origin):

unicode.cpp

@@ -492,7 +492,7 @@ std::vector<uint32_t> sort_by_canonical_class(std::vector<uint32_t> & cpts) {
 std::vector<uint32_t> canonical_decomposition_cpts(std::vector<uint32_t> & cpts, uint32_t starting_offset) {
     std::vector<uint32_t> result;
     for (auto i = starting_offset; i < cpts.size(); i++) {
-        auto it = unicode_map_nfd.equal_range(cpts[i]);
+        const auto& it = unicode_map_nfd.equal_range(cpts[i]);
         if (it.first != it.second) {
             uint offset = 0;
             for (auto jt = it.first; jt != it.second; jt++) {