diff --git a/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_multi_freq.yaml b/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_multi_freq.yaml
index 9bedf241d..dde58f293 100644
--- a/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_multi_freq.yaml
+++ b/examples/benchmarks/LightGBM/workflow_config_lightgbm_Alpha158_multi_freq.yaml
@@ -20,7 +20,7 @@ data_handler_config: &data_handler_config
     sample_config:
         feature:
             - class: ResampleProcessor
-              moudle_path: features_sample.py
+              module_path: features_sample.py
               kwargs:
                   freq: 1d
                   hour: 13
diff --git a/qlib/data/data.py b/qlib/data/data.py
index 31c4ac6a8..e8fb52849 100644
--- a/qlib/data/data.py
+++ b/qlib/data/data.py
@@ -548,7 +548,7 @@ class DatasetProvider(abc.ABC):
             for _processor in inst_processors if isinstance(inst_processors, (list, tuple, set)) else [inst_processors]:
                 _processor = init_instance_by_config(_processor, accept_types=InstProcessor)
                 data = _processor(data)
-            return data
+        return data
 
 
 class LocalCalendarProvider(CalendarProvider):
diff --git a/qlib/data/dataset/loader.py b/qlib/data/dataset/loader.py
index 0b77d3a1d..4b4df2eb6 100644
--- a/qlib/data/dataset/loader.py
+++ b/qlib/data/dataset/loader.py
@@ -217,9 +217,8 @@ class QlibDataLoader(DLWParser):
             warnings.warn("`filter_pipe` is not None, but it will not be used with `instruments` as list")
 
         freq = self.freq[gp_name] if self.can_sample else self.freq
-        df = D.features(
-            instruments, exprs, start_time, end_time, freq=freq, inst_processors=self.sample_config.get(freq, None)
-        )
+        inst_processor = self.sample_config.get(gp_name, None) if self.can_sample else None
+        df = D.features(instruments, exprs, start_time, end_time, freq=freq, inst_processors=inst_processor)
         df.columns = names
         if self.swap_level:
             df = df.swaplevel().sort_index()  # NOTE: if swaplevel, return <datetime, instrument>