Replace auto with appropriate data type

Signed-off-by: Shrinath Suresh <shrinath@ideas2it.com>

cpp/src/examples/babyllama/baby_llama_handler.cc

@@ -48,7 +48,7 @@ LlmHandler::LoadModel(
     float topp = 0.9f;  // top-p in nucleus sampling. 1.0 = off. 0.9 works well,
                         // but slower
     int steps = 256;    // number of steps to run for
-    unsigned long long rng_seed = 0;
+    unsigned long long rng_seed;
     // build the Sampler
     build_sampler(&sampler, transformer.config.vocab_size, temperature, topp,
                   rng_seed);
@@ -110,11 +110,12 @@ std::vector<torch::jit::IValue> LlmHandler::Preprocess(
       int num_prompt_tokens = 0;
       int* prompt_tokens = (int*)malloc(
           (strlen(msgCStr) + 3) * sizeof(int));  // +3 for '\0', ?BOS, ?EOS
+
       encode(&tokenizer, msgCStr, 1, 0, prompt_tokens, &num_prompt_tokens);
 
       std::vector<torch::Tensor> tensor_vector;
       for (int64_t i = 0; i < num_prompt_tokens; ++i) {
-        auto token = prompt_tokens[i];
+        int token = prompt_tokens[i];
         torch::Tensor tensor = torch::tensor(token, torch::kInt64);
         tensor_vector.push_back(tensor);
       }
@@ -153,7 +154,7 @@ torch::Tensor LlmHandler::Inference(
     std::pair<std::string&, std::map<uint8_t, std::string>&>& idx_to_req_id,
     std::shared_ptr<torchserve::InferenceResponseBatch>& response_batch) {
   std::vector<torch::Tensor> tensor_vector;
-  auto tokens_list_tensor = inputs[0].toTensor();
+  torch::Tensor tokens_list_tensor = inputs[0].toTensor();
 
   int64_t num_elements = tokens_list_tensor.numel();
 
@@ -162,7 +163,7 @@ torch::Tensor LlmHandler::Inference(
   std::vector<long> long_vector;
   long_vector.reserve(num_elements);
 
-  auto data_ptr = tokens_list_tensor.data_ptr<int64_t>();
+  int64_t* data_ptr = tokens_list_tensor.data_ptr<int64_t>();
   for (int64_t i = 0; i < num_elements; ++i) {
     long_vector.push_back(data_ptr[i]);
   }
@@ -213,7 +214,7 @@ torch::Tensor LlmHandler::Inference(
   // iteration)
   if (pos > 1) {
     long end = time_in_ms();
-    auto token_per_sec = (pos - 1) / (double)(end - start) * 1000;
+    double token_per_sec = (pos - 1) / (double)(end - start) * 1000;
     std::cout << "Achieved tok per sec: " << token_per_sec << std::endl;
   }
 
@@ -230,7 +231,7 @@ void LlmHandler::Postprocess(
   for (const auto& kv : idx_to_req_id.second) {
     try {
       int64_t num_elements = data.numel();
-      auto data_ptr = data.data_ptr<int64_t>();
+      int64_t* data_ptr = data.data_ptr<int64_t>();
       int64_t token = 1;
       std::string concatenated_string;
       for (int64_t i = 0; i < num_elements; ++i) {
@@ -264,7 +265,6 @@ void LlmHandler::Postprocess(
                             "c10 error, failed to postprocess tensor");
     }
   }
-
 }
 
 }  // namespace llm