llama : sanitize invalid tokens (ggml-org#9357)

* common : do not add null tokens during warmup

ggml-ci

* llama : check that the input tokens are valid

ggml-ci

* tests : fix batch size of bert model

ggml-ci

Author: ggerganov

common/common.cpp

@@ -2690,10 +2690,15 @@ struct llama_init_result llama_init_from_gpt_params(gpt_params & params) {
         llama_token bos = llama_token_bos(model);
         llama_token eos = llama_token_eos(model);
         // some models (e.g. T5) don't have a BOS token
-        if (bos != -1) {
+        if (bos != LLAMA_TOKEN_NULL) {
             tmp.push_back(bos);
         }
-        tmp.push_back(eos);
+        if (eos != LLAMA_TOKEN_NULL) {
+            tmp.push_back(eos);
+        }
+        if (tmp.empty()) {
+            tmp.push_back(0);
+        }
 
         if (llama_model_has_encoder(model)) {
             llama_encode(lctx, llama_batch_get_one(tmp.data(), tmp.size(), 0, 0));

examples/server/tests/features/embeddings.feature

@@ -9,8 +9,11 @@ Feature: llama.cpp server
     And   a model alias bert-bge-small
     And   42 as server seed
     And   2 slots
-    And   1024 as batch size
-    And   1024 as ubatch size
+    # the bert-bge-small model has context size of 512
+    # since the generated prompts are as big as the batch size, we need to set the batch size to 512
+    # ref: https://huggingface.co/BAAI/bge-small-en-v1.5/blob/5c38ec7c405ec4b44b94cc5a9bb96e735b38267a/config.json#L20
+    And   512 as batch size
+    And   512 as ubatch size
     And   2048 KV cache size
     And   embeddings extraction
     Then  the server is starting

src/llama.cpp

@@ -16070,6 +16070,13 @@ static int llama_decode_internal(
         return -1;
     }
 
+    for (uint32_t i = 0; i < n_tokens_all; ++i) {
+        if (batch_all.token[i] < 0) {
+            LLAMA_LOG_ERROR("%s: invalid token[%d] = %d", __func__, i, batch_all.token[i]);
+            return -1;
+        }
+    }
+
     const auto & model   = lctx.model;
     const auto & hparams = model.hparams;
     const auto & cparams = lctx.cparams;
@@ -16362,6 +16369,13 @@ static int llama_encode_internal(
         return -1;
     }
 
+    for (uint32_t i = 0; i < n_tokens; ++i) {
+        if (batch.token[i] < 0) {
+            LLAMA_LOG_ERROR("%s: invalid token[%d] = %d", __func__, i, batch.token[i]);
+            return -1;
+        }
+    }
+
     const auto & model   = lctx.model;
     const auto & hparams = model.hparams;
     const auto & cparams = lctx.cparams;