diff --git a/qlib/data/dataset/handler.py b/qlib/data/dataset/handler.py
index 9812864af..d32b251de 100644
--- a/qlib/data/dataset/handler.py
+++ b/qlib/data/dataset/handler.py
@@ -56,7 +56,24 @@ class DataHandler(Serializable):
         end_time=None,
         data_loader: Tuple[dict, str, DataLoader] = None,
         init_data=True,
+        fetch_orig=True,
     ):
+        """
+        Parameters
+        ----------
+        instruments :
+            The stock list to retrive
+        start_time :
+            start_time of the original data
+        end_time :
+            end_time of the original data
+        data_loader : Tuple[dict, str, DataLoader]
+            data loader to load the data
+        init_data :
+            intialize the original data in the constructor
+        fetch_orig : bool
+            Return the original data instead of copy if possible
+        """
         # Set logger
         self.logger = get_module_logger("DataHandler")
 
@@ -72,6 +89,7 @@ class DataHandler(Serializable):
         self.instruments = instruments
         self.start_time = start_time
         self.end_time = end_time
+        self.fetch_orig = fetch_orig
         if init_data:
             with TimeInspector.logt("Init data"):
                 self.init()
@@ -138,7 +156,7 @@ class DataHandler(Serializable):
         -------
         pd.DataFrame:
         """
-        df = fetch_df_by_index(self._data, selector, level)
+        df = fetch_df_by_index(self._data, selector, level, fetch_orig=self.fetch_orig)
         df = self._fetch_df_by_col(df, col_set)
         if squeeze:
             # squeeze columns
@@ -269,8 +287,10 @@ class DataHandlerLP(DataHandler):
         for pname in "infer_processors", "learn_processors":
             for proc in locals()[pname]:
                 getattr(self, pname).append(
-                    init_instance_by_config(proc, processor_module, accept_types=(processor_module.Processor,))
-                )
+                    init_instance_by_config(
+                        proc,
+                        None if (isinstance(data_loader, dict) and "module_path" in data_loader) else data_loader_module,
+                        accept_types=processor_module.Processor))
 
         self.process_type = process_type
         super().__init__(instruments, start_time, end_time, data_loader, **kwargs)
@@ -354,15 +374,16 @@ class DataHandlerLP(DataHandler):
         # init raw data
         super().init(enable_cache=enable_cache)
 
-        if init_type == DataHandlerLP.IT_FIT_IND:
-            self.fit()
-            self.process_data()
-        elif init_type == DataHandlerLP.IT_LS:
-            self.process_data()
-        elif init_type == DataHandlerLP.IT_FIT_SEQ:
-            self.fit_process_data()
-        else:
-            raise NotImplementedError(f"This type of input is not supported")
+        with TimeInspector.logt("fit & process data"):
+            if init_type == DataHandlerLP.IT_FIT_IND:
+                self.fit()
+                self.process_data()
+            elif init_type == DataHandlerLP.IT_LS:
+                self.process_data()
+            elif init_type == DataHandlerLP.IT_FIT_SEQ:
+                self.fit_process_data()
+            else:
+                raise NotImplementedError(f"This type of input is not supported")
 
         # TODO: Be able to cache handler data. Save the memory for data processing
 
@@ -396,7 +417,7 @@ class DataHandlerLP(DataHandler):
         pd.DataFrame:
         """
         df = self._get_df_by_key(data_key)
-        df = fetch_df_by_index(df, selector, level)
+        df = fetch_df_by_index(df, selector, level, fetch_orig=self.fetch_orig)
         return self._fetch_df_by_col(df, col_set)
 
     def get_cols(self, col_set=DataHandler.CS_ALL, data_key: str = DK_I) -> list:
diff --git a/qlib/data/dataset/utils.py b/qlib/data/dataset/utils.py
index 8ee199bc0..85a5e8389 100644
--- a/qlib/data/dataset/utils.py
+++ b/qlib/data/dataset/utils.py
@@ -32,7 +32,7 @@ def get_level_index(df: pd.DataFrame, level=Union[str, int]) -> int:
 
 
 def fetch_df_by_index(
-    df: pd.DataFrame, selector: Union[pd.Timestamp, slice, str, list], level: Union[str, int]
+    df: pd.DataFrame, selector: Union[pd.Timestamp, slice, str, list], level: Union[str, int], fetch_orig=True,
 ) -> pd.DataFrame:
     """
     fetch data from `data` with `selector` and `level`
@@ -52,6 +52,11 @@ def fetch_df_by_index(
     idx_slc = (selector, slice(None, None))
     if get_level_index(df, level) == 1:
         idx_slc = idx_slc[1], idx_slc[0]
-    return df.loc[
-        pd.IndexSlice[idx_slc],
-    ]  # This could be faster than df.loc(axis=0)[idx_slc]
+    if fetch_orig:
+        for slc in idx_slc:
+            if slc != slice(None, None):
+                return df.loc[pd.IndexSlice[idx_slc],]
+        else:
+            return df
+    else:
+        return df.loc[pd.IndexSlice[idx_slc],]
diff --git a/qlib/workflow/utils.py b/qlib/workflow/utils.py
index d4594d28e..f5a73a157 100644
--- a/qlib/workflow/utils.py
+++ b/qlib/workflow/utils.py
@@ -5,9 +5,9 @@ import sys, traceback, signal, atexit
 from . import R
 from .recorder import Recorder
 from ..log import get_module_logger
-
 logger = get_module_logger("workflow", "INFO")
 
+
 # function to handle the experiment when unusual program ending occurs
 def experiment_exit_handler():
     """
@@ -31,10 +31,12 @@ def experiment_exception_hook(type, value, tb):
     value: Exception's value
     tb: Exception's traceback
     """
-    error_msg = "An exception has been raised.\n" f"Type: {type}\n"
+    error_msg = f"An exception has been raised[{type.__name__}: {value}]."
     logger.error(error_msg)
+
+    # Same as original format
     traceback.print_tb(tb)
-    logger.error(f"Value: {value}")
+    print(f"{type.__name__}: {value}")
 
     R.end_exp(recorder_status=Recorder.STATUS_FA)