Peft python interface (#1306)

* update script * less model renaming * fix * fix * fix * backup * . * update * . * fixes * fix * fix build * fix * fix * fix issues for downloading peft model * solved issues for download peft model * added printouts for debugging * fix * fix seg fault * add test, separate peft script in cpp * fix * fixes * fix * update peft python interface * update * update * update * updates * fix * fixes * fix * fixes --------- Co-authored-by: april-yyt <aprilytyang@gmail.com>
flexflow · Mar 27, 2024 · b6ada2f · b6ada2f
1 parent 0b35b0c
commit b6ada2f
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diff --git a/CMakeLists.txt b/CMakeLists.txt
@@ -558,6 +558,7 @@ if(NOT BUILD_LEGION_ONLY)
   if(FF_BUILD_ALL_INFERENCE_EXAMPLES OR FF_BUILD_ALL_EXAMPLES)
     add_subdirectory(inference/spec_infer)
     add_subdirectory(inference/incr_decoding)
+    add_subdirectory(inference/peft)
   endif()
 
 

diff --git a/include/flexflow/ffconst.h b/include/flexflow/ffconst.h
@@ -78,6 +78,11 @@ enum InferenceMode {
   TREE_VERIFY_MODE = 2003,
 };
 
+enum RequestType {
+  REQ_INFERENCE = 4001,
+  REQ_FINETUNING = 4002,
+};
+
 // This is consistent with TASO's OpType
 // https://github.com/jiazhihao/TASO/blob/master/include/taso/ops.h#L75-L138
 enum OperatorType {
@@ -179,8 +184,7 @@ enum OperatorType {
   OP_TREE_INC_MULTIHEAD_SELF_ATTENTION,
   OP_SAMPLING,
   // PEFT Ops
-  OP_LORA_MLP_FIRST,
-  OP_LORA_MLP_SECOND,
+  OP_LORA,
   // Parallel Ops
   OP_REPARTITION,
   OP_COMBINE,

diff --git a/include/flexflow/flexflow_c.h b/include/flexflow/flexflow_c.h
@@ -55,6 +55,8 @@ FF_NEW_OPAQUE_TYPE(flexflow_inference_manager_t);
 FF_NEW_OPAQUE_TYPE(flexflow_request_manager_t);
 FF_NEW_OPAQUE_TYPE(flexflow_file_data_loader_t);
 FF_NEW_OPAQUE_TYPE(flexflow_generation_result_t);
+FF_NEW_OPAQUE_TYPE(flexflow_lora_linear_config_t);
+FF_NEW_OPAQUE_TYPE(flexflow_peft_model_id_t);
 
 // -----------------------------------------------------------------------
 // FFConfig
@@ -593,6 +595,9 @@ flexflow_tensor_t flexflow_model_add_argmax(flexflow_model_t handle_,
                                             bool beam_search,
                                             char const *name);
 
+flexflow_peft_model_id_t flexflow_model_add_lora_layer(
+    flexflow_model_t handle_, const flexflow_lora_linear_config_t peft_config_);
+
 void flexflow_model_set_sgd_optimizer(flexflow_model_t handle,
                                       flexflow_sgd_optimizer_t optimizer);
 
@@ -616,10 +621,13 @@ void flexflow_model_set_transformer_layer_id(flexflow_model_t handle, int id);
 
 void flexflow_model_generate(flexflow_model_t handle_,
                              int num_requests,
-                             char const **input_text,
-                             int max_num_chars,
-                             char **output_text,
-                             int max_seq_length,
+                             enum RequestType *request_types,
+                             char const **input_texts,
+                             char **output_texts,
+                             int *max_seq_lengths,
+                             flexflow_peft_model_id_t *peft_model_ids,
+                             char const **dataset_filepaths,
+                             int *training_steps,
                              int **output_length_and_tokens);
 
 void flexflow_model_set_position_offset(flexflow_model_t handle, int offset);
@@ -1036,6 +1044,26 @@ void flexflow_file_data_loader_destroy(flexflow_file_data_loader_t handle_);
 void flexflow_file_data_loader_load_weights(flexflow_file_data_loader_t handle_,
                                             flexflow_model_t model_handle_);
 
+// -----------------------------------------------------------------------
+// LoraLinearConfig
+// -----------------------------------------------------------------------
+
+flexflow_lora_linear_config_t
+    flexflow_lora_linear_config_create(char const *cache_folder_,
+                                       char const *peft_model_id_);
+
+void flexflow_lora_linear_config_destroy(flexflow_lora_linear_config_t handle_);
+
+// -----------------------------------------------------------------------
+// PEFTModelID
+// -----------------------------------------------------------------------
+
+flexflow_peft_model_id_t flexflow_peft_model_id_create();
+
+flexflow_peft_model_id_t flexflow_peft_model_id_create_id(unsigned long id);
+
+void flexflow_peft_model_id_destroy(flexflow_peft_model_id_t handle_);
+
 #ifdef __cplusplus
 }
 #endif

diff --git a/include/flexflow/model.h b/include/flexflow/model.h
@@ -837,19 +837,12 @@ class FFModel {
   // ========================================
   // PEFT Layers
   // ========================================
-  void lora_linear(Tensor const input,
-                   Tensor const output,
-                   OperatorType _type,
-                   char const *name = nullptr);
+  PEFTModelID *add_lora_layer(LoraLinearConfig const peft_config);
   // ========================================
   // Inference APIs
   // ========================================
   std::vector<GenerationResult> generate(std::vector<Request> const &requests);
 
-  PEFTModelID register_peft_model(
-      LoraLinearConfig const mlp_first = LoraLinearConfig::DefaultConfig,
-      LoraLinearConfig const mlp_second = LoraLinearConfig::DefaultConfig);
-
   Tensor create_tensor_legion_ordering(int num_dim,
                                        int const dims[],
                                        DataType data_type,
@@ -1174,6 +1167,12 @@ class FFModel {
   std::vector<Layer *> layers;
   std::vector<Op *> operators;
   std::vector<ParallelTensor> parameters;
+  // PEFT related
+  std::unordered_map<Layer *, Layer *> base_layer_to_peft_layer;
+  std::unordered_map<Layer *, std::vector<PEFTModelID>> peft_layer_to_peft_id;
+  std::unordered_map<PEFTModelID, LoraLinearConfig> peft_configs;
+  //   std::vector<Op *> peft_operators;
+
   FFHandler handlers[MAX_NUM_WORKERS];
   Legion::Future current_metrics;
   // Cached operators: key: operator hash, value: operator pointer

diff --git a/include/flexflow/ops/lora_linear.h b/include/flexflow/ops/lora_linear.h
@@ -17,12 +17,14 @@ class LoraLinear : public Op {
   using Params = LoraLinearParams;
   using Input = std::pair<ParallelTensor, ParallelTensor>;
 
-  LoraLinear(FFModel &model,
-             LayerID const &layer_guid,
-             OperatorType type,
-             ParallelTensor const input,
-             ParallelTensor const output,
-             char const *name = nullptr);
+  LoraLinear(
+      FFModel &model,
+      LayerID const &layer_guid,
+      OperatorType type,
+      ParallelTensor const input,
+      ParallelTensor const output,
+      std::unordered_map<PEFTModelID, LoraLinearConfig> const &_peft_configs,
+      char const *name = nullptr);
   LoraLinear(FFModel &model,
              LoraLinear const &other,
              ParallelTensor const input,
@@ -39,11 +41,6 @@ class LoraLinear : public Op {
                       MachineView const *mv = nullptr) override;
   void forward(FFModel const &) override;
   void backward(FFModel const &) override;
-  void register_peft_model(FFModel const &ff,
-                           std::vector<ParallelTensor> const &batch_inputs,
-                           std::vector<ParallelTensor> const &batch_outputs,
-                           PEFTModelID const &model_id,
-                           LoraLinearConfig const lora_config);
   Legion::FutureMap inference(FFModel const &,
                               BatchConfigFuture const &,
                               std::vector<ParallelTensor> const &,
@@ -64,11 +61,6 @@ class LoraLinear : public Op {
                            std::vector<Legion::PhysicalRegion> const &regions,
                            Legion::Context ctx,
                            Legion::Runtime *runtime);
-  static void
-      register_model_task(Legion::Task const *task,
-                          std::vector<Legion::PhysicalRegion> const &regions,
-                          Legion::Context ctx,
-                          Legion::Runtime *runtime);
   static void inference_task(Legion::Task const *task,
                              std::vector<Legion::PhysicalRegion> const &regions,
                              Legion::Context ctx,
@@ -98,6 +90,8 @@ class LoraLinear : public Op {
                   int num_inputs) const override;
   // size_t get_params_hash() const override;
   LoraLinearParams get_params() const;
+
+  std::unordered_map<PEFTModelID, LoraLinearConfig> peft_configs;
 };
 
 }; // namespace FlexFlow

diff --git a/include/flexflow/ops/lora_linear_params.h b/include/flexflow/ops/lora_linear_params.h
@@ -12,7 +12,7 @@ namespace FlexFlow {
 
 class LoraLinearConfig {
 public:
-  static const LoraLinearConfig DefaultConfig;
+  static const LoraLinearConfig EmptyConfig;
   LoraLinearConfig();
   LoraLinearConfig(int rank,
                    OptimizerType type = OPTIMIZER_TYPE_SGD,
@@ -33,6 +33,7 @@ class LoraLinearConfig {
   std::string peft_model_id;
   int lora_alpha;
   float lora_dropout;
+  std::vector<std::string> target_modules;
   // whether to load weights from file, instead of initializing them randomly
   bool load_weights_from_file;
 };
@@ -41,6 +42,7 @@ class LoraLinearParams {
 public:
   LayerID layer_guid;
   OperatorType type;
+  std::unordered_map<PEFTModelID, LoraLinearConfig> peft_configs;
   char name[MAX_OPNAME];
 
   bool is_valid(std::pair<ParallelTensorShape, ParallelTensorShape> const

diff --git a/include/flexflow/request_manager.h b/include/flexflow/request_manager.h
@@ -65,7 +65,6 @@ struct Request {
     COMPLETED = 103, // finished and verified
     FINISHING = 104, // finishing request, but not yet verified
   };
-  enum RequestType { REQ_INFERENCE = 201, REQ_FINETUNING = 202 };
   BatchConfig::RequestGuid guid;
   PEFTModelID peft_model_id = PEFTModelID::NO_ID;
   int max_sequence_length = 128;
@@ -81,10 +80,11 @@ struct Request {
   RequestType req_type = REQ_INFERENCE;
   int completed_training_steps = 0;
   int max_training_steps = 1;
-  std::vector<std::pair<std::string, std::string>> dataset_text;
+  std::string dataset_filepath;
   std::vector<std::pair<std::vector<BatchConfig::TokenId>,
                         std::vector<BatchConfig::TokenId>>>
       dataset;
+  friend std::ostream &operator<<(std::ostream &os, Request const &req);
 };
 
 // store the result of beam search

diff --git a/inference/incr_decoding/incr_decoding.cc b/inference/incr_decoding/incr_decoding.cc
@@ -40,7 +40,6 @@ void parse_input_args(char **argv,
                       int argc,
                       FilePaths &paths,
                       std::string &llm_model_name,
-                      std::string &peft_model_name,
                       bool &use_full_precision,
                       bool &verbose,
                       bool &do_sample,
@@ -58,13 +57,6 @@ void parse_input_args(char **argv,
       }
       continue;
     }
-    if (!strcmp(argv[i], "-peft-model")) {
-      peft_model_name = std::string(argv[++i]);
-      for (char &c : peft_model_name) {
-        c = std::tolower(c);
-      }
-      continue;
-    }
     // cache folder
     if (!strcmp(argv[i], "-cache-folder")) {
       paths.cache_folder_path = std::string(argv[++i]);
@@ -133,7 +125,7 @@ void FlexFlow::top_level_task(Task const *task,
     assert(false && "Doesn't support quantization in non-offload mode");
   }
   FilePaths file_paths;
-  std::string llm_model_name, peft_model_name;
+  std::string llm_model_name;
   bool use_full_precision = false;
   bool verbose = false;
   bool do_sample = false;
@@ -150,7 +142,6 @@ void FlexFlow::top_level_task(Task const *task,
                    argc,
                    file_paths,
                    llm_model_name,
-                   peft_model_name,
                    use_full_precision,
                    verbose,
                    do_sample,
@@ -159,6 +150,7 @@ void FlexFlow::top_level_task(Task const *task,
                    max_requests_per_batch,
                    max_tokens_per_batch,
                    max_sequence_length);
+
   assert(ffconfig.data_parallelism_degree * ffconfig.tensor_parallelism_degree *
              ffconfig.pipeline_parallelism_degree ==
          ffconfig.numNodes * ffconfig.workersPerNode);
@@ -259,19 +251,6 @@ void FlexFlow::top_level_task(Task const *task,
     assert(false && "unknow model type");
   }
 
-  // Register PEFT layer
-  LoraLinearConfig mlp_second =
-      peft_model_name.empty()
-          ? LoraLinearConfig::DefaultConfig
-          : LoraLinearConfig(file_paths.cache_folder_path, peft_model_name);
-  PEFTModelID peft_model_id =
-      peft_model_name.empty()
-          ? PEFTModelID::NO_ID
-          : model.register_peft_model(
-                LoraLinearConfig::DefaultConfig /*mlp_first*/,
-                mlp_second /*mlp_second*/);
-
-  // Start background server
   rm->start_background_server(&model);
 
   int total_num_requests = 0;
@@ -288,20 +267,10 @@ void FlexFlow::top_level_task(Task const *task,
     for (auto &prompt : prompt_json) {
       std::string text = prompt.get<std::string>();
       printf("Prompt[%d]: %s\n", total_num_requests, text.c_str());
-      // Add inference request
-      // Request inference_req;
-      // inference_req.prompt = text;
-      // inference_req.max_sequence_length = 128;
-      // inference_req.peft_model_id = peft_model_id;
-      // requests.push_back(inference_req);
-      // total_num_requests++;
-      // Add fine-tuning request
-      Request fine_tuning_req;
-      fine_tuning_req.req_type = Request::RequestType::REQ_FINETUNING;
-      fine_tuning_req.max_sequence_length = 128;
-      fine_tuning_req.peft_model_id = peft_model_id;
-      fine_tuning_req.dataset_text.push_back(std::make_pair(text, ""));
-      requests.push_back(fine_tuning_req);
+      Request inference_req;
+      inference_req.prompt = text;
+      inference_req.max_sequence_length = 128;
+      requests.push_back(inference_req);
       total_num_requests++;
     }
     std::vector<GenerationResult> result = model.generate(requests);