lintrunner formatting

Author: cmodi-meta

examples/mediatek/executor_runner/llama_runner/llm_helper/include/llama_runner_values.h

@@ -11,32 +11,36 @@
 #pragma once
 
 namespace mtk::vars {
-  using example::llm_helper::LLMType;
-
-  // Sizes
-  const size_t PROMPT_TOKEN_BATCH_SIZE = 128;
-  const size_t CACHE_SIZE = 512;
-  const size_t HIDDEN_SIZE = 4096;
-  const size_t NUM_HEAD = 32;
-  const size_t NUM_LAYER = 32;
-  const size_t MAX_TOKEN_LENGTH = 8192;
-  const double ROT_EMB_BASE = 500000;
-
-  // Types
-  const LLMType MODEL_INPUT_TYPE = LLMType::FP32;
-  const LLMType MODEL_OUTPUT_TYPE = LLMType::FP32;
-  const LLMType CACHE_TYPE = LLMType::FP32;
-  const LLMType MASK_TYPE = LLMType::FP32;
-  const LLMType ROT_EMB_TYPE = LLMType::FP32;
-
-  // Paths
-  const std::string TOKENIZER_PATH="/data/local/tmp/et-mtk/llama3/tokenizer.model";
-  const std::string TOKEN_EMBEDDING_PATH="/data/local/tmp/et-mtk/llama3/embedding_llama3-8B-instruct_fp32.bin";
-
-  // Comma-Separated Paths
-  const std::string PROMPT_MODEL_PATHS="/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_0.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_1.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_2.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_3.pte,";
-
-  // Comma-Separated Paths
-  const std::string GEN_MODEL_PATHS="/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_0.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_1.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_2.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_3.pte,";
-
-} // namespace mtk:vars
+using example::llm_helper::LLMType;
+
+// Sizes
+const size_t PROMPT_TOKEN_BATCH_SIZE = 128;
+const size_t CACHE_SIZE = 512;
+const size_t HIDDEN_SIZE = 4096;
+const size_t NUM_HEAD = 32;
+const size_t NUM_LAYER = 32;
+const size_t MAX_TOKEN_LENGTH = 8192;
+const double ROT_EMB_BASE = 500000;
+
+// Types
+const LLMType MODEL_INPUT_TYPE = LLMType::FP32;
+const LLMType MODEL_OUTPUT_TYPE = LLMType::FP32;
+const LLMType CACHE_TYPE = LLMType::FP32;
+const LLMType MASK_TYPE = LLMType::FP32;
+const LLMType ROT_EMB_TYPE = LLMType::FP32;
+
+// Paths
+const std::string TOKENIZER_PATH =
+    "/data/local/tmp/et-mtk/llama3/tokenizer.model";
+const std::string TOKEN_EMBEDDING_PATH =
+    "/data/local/tmp/et-mtk/llama3/embedding_llama3-8B-instruct_fp32.bin";
+
+// Comma-Separated Paths
+const std::string PROMPT_MODEL_PATHS =
+    "/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_0.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_1.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_2.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_128t512c_3.pte,";
+
+// Comma-Separated Paths
+const std::string GEN_MODEL_PATHS =
+    "/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_0.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_1.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_2.pte,/data/local/tmp/et-mtk/llama3/llama3-8B-instruct_A16W4_4_chunks_1t512c_3.pte,";
+
+} // namespace mtk::vars

examples/mediatek/executor_runner/mtk_llama_runner.cpp

@@ -44,8 +44,8 @@
  * any receiver's applicable license agreements with MediaTek Inc.
  */
 
-#include "executorch/backends/mediatek/runtime/include/NeuronBufferAllocator.h"
 #include <executorch/examples/mediatek/executor_runner/mtk_llama_runner.h>
+#include "executorch/backends/mediatek/runtime/include/NeuronBufferAllocator.h"
 
 #include <ctime>
 #include <iostream>
@@ -65,8 +65,8 @@
 
 #include "llama_runner/ModelChunk.h"
 #include "llama_runner/Utils.h"
-#include "llama_runner/llm_helper/include/llm_types.h"
 #include "llama_runner/llm_helper/include/llama_runner_values.h"
+#include "llama_runner/llm_helper/include/llm_types.h"
 
 static uint64_t MAX_RESPONSE = 50; // Maximum number of tokens to generate.
 // Global BOS and EOS option for tokenization (encoding)
@@ -83,15 +83,14 @@ using namespace mtk::vars;
 namespace llm = ::executorch::extension::llm;
 
 MTKLlamaRunner::MTKLlamaRunner(
-  const std::string& model_path,
-  const std::string& tokenizer_path,
-  const float temperature)
-  : modeloptions_(get_model_options()),
-    modelpaths_(get_model_paths()) {
+    const std::string& model_path,
+    const std::string& tokenizer_path,
+    const float temperature)
+    : modeloptions_(get_model_options()), modelpaths_(get_model_paths()) {
   executorch::runtime::runtime_init();
   ET_LOG(
-        Info,
-        "Creating MTK Llama runner. Current it will self-load .pte, .bin, and .so files. Initiated runtime_init().");
+      Info,
+      "Creating MTK Llama runner. Current it will self-load .pte, .bin, and .so files. Initiated runtime_init().");
 }
 
 Error MTKLlamaRunner::load() {
@@ -122,7 +121,6 @@ Error MTKLlamaRunner::generate(
     int32_t seq_len,
     std::function<void(const std::string&)> token_callback,
     std::function<void(const Stats&)> stats_callback) {
-
   if (!is_loaded()) {
     ET_CHECK_OK_OR_RETURN_ERROR(load());
   }
@@ -137,9 +135,9 @@ Error MTKLlamaRunner::generate(
         }
       };
 
-  ET_LOG(Info, "Starting inference from MTKLlamaRunner");    
+  ET_LOG(Info, "Starting inference from MTKLlamaRunner");
   inference(*runtime_.get(), tokenizer_, prompt, wrapped_callback);
-  ET_LOG(Info, "Completed inference from MTKLlamaRunner"); 
+  ET_LOG(Info, "Completed inference from MTKLlamaRunner");
 
   return Error::Ok;
 }
@@ -169,7 +167,7 @@ LlamaModelOptions MTKLlamaRunner::get_model_options() {
       .cache_type = CACHE_TYPE,
       .mask_type = MASK_TYPE,
       .rot_emb_type = ROT_EMB_TYPE};
-  ET_LOG(Info, "Completed get_model_options");    
+  ET_LOG(Info, "Completed get_model_options");
   return options;
 }
 
@@ -179,7 +177,7 @@ LlamaModelPaths MTKLlamaRunner::get_model_paths() {
       .token_embedding_path = TOKEN_EMBEDDING_PATH,
       .prompt_model_paths = split(PROMPT_MODEL_PATHS, ','),
       .gen_model_paths = split(GEN_MODEL_PATHS, ',')};
-  ET_LOG(Info, "Completed get_model_paths");   
+  ET_LOG(Info, "Completed get_model_paths");
   return model_paths;
 }
 
@@ -325,7 +323,8 @@ Error MTKLlamaRunner::inference(
   const auto first_output_token = prefill_res.get();
 
   // run generation mode (decoding)
-  return gen_response(llama_runtime, tokenizer, first_output_token, token_callback);
+  return gen_response(
+      llama_runtime, tokenizer, first_output_token, token_callback);
 }
 
 std::unique_ptr<Tokenizer> MTKLlamaRunner::load_tokenizer() {

examples/mediatek/executor_runner/mtk_llama_runner.h

@@ -11,14 +11,14 @@
 
 #pragma once
 
+#include <executorch/examples/models/llama2/tokenizer/llama_tiktoken.h>
+#include <executorch/extension/llm/runner/stats.h>
+#include <executorch/extension/llm/tokenizer/bpe_tokenizer.h>
+#include <executorch/extension/llm/tokenizer/tiktoken.h>
 #include <cstdint>
 #include <functional>
 #include <memory>
 #include <string>
-#include <executorch/extension/llm/runner/stats.h>
-#include <executorch/examples/models/llama2/tokenizer/llama_tiktoken.h>
-#include <executorch/extension/llm/tokenizer/bpe_tokenizer.h>
-#include <executorch/extension/llm/tokenizer/tiktoken.h>
 
 #include "llama_runner/LlamaConfig.h"
 #include "llama_runner/LlamaRuntime.h"
@@ -65,7 +65,6 @@ class MTKLlamaRunner {
       std::function<void(const std::string&)> token_callback);
   std::unique_ptr<Tokenizer> load_tokenizer();
 
-
  private:
   // model
   const LlamaModelOptions modeloptions_;

extension/android/jni/jni_layer_llama.cpp

@@ -119,9 +119,9 @@ class ExecuTorchLlamaJni
           temperature);
     } else if (model_type_category == MODEL_TYPE_MEDIATEK_LLAMA) {
       mtk_llama_runner_ = std::make_unique<MTKLlamaRunner>(
-        model_path->toStdString().c_str(),
-        tokenizer_path->toStdString().c_str(),
-        temperature);
+          model_path->toStdString().c_str(),
+          tokenizer_path->toStdString().c_str(),
+          temperature);
     }
   }