Fix the Errors with unexpected indentation when building Qlib's documentation (#1352)

* Fix ERROR: Unexpected indentation in qlib/data/dataset/handler.py

* Fix ERROR: Unexpected indentation in qlib/data/dataset/__init__.py

* Fix ERROR: Unexpected indentation in ../qlib/data/cache.py

* Fix ERROR: Unexpected indentation in qlib/model/meta/task.py

* Fix ERROR: Unexpected indentation in qlib/model/meta/dataset.py

* Fix ERROR: Unexpected indentation in qlib/workflow/online/manager.py

* Fix ERROR: Unexpected indentation in qlib/workflow/online/update.py

* Fix ERROR: Unexpected indentation in /qlib/workflow/__init__.py

* Fix ERROR: Unexpected indentation in qlib/data/base.py

* Fix ERROR: Unexpected indentation in qlib/data/dataset/loader.py

* Fix ERROR: Unexpected indentation in qlib/contrib/evaluate.py

* Fix ERROR: Unexpected indentation in qlib/workflow/record_temp.py

* Fix ERROR: Unexpected indentation in qlib/workflow/task/gen.py

* Fix ERROR: Unexpected indentation in qlib/strategy/base.py

* Fix qlib/data/dataset/handler.py

* Retest

qlib/model/meta/dataset.py

@@ -12,11 +12,15 @@ class MetaTaskDataset(Serializable, metaclass=abc.ABCMeta):
     A dataset fetching the data in a meta-level.
 
     A Meta Dataset is responsible for
+
     - input tasks(e.g. Qlib tasks) and prepare meta tasks
+
         - meta task contains more information than normal tasks (e.g. input data for meta model)
 
     The learnt pattern could transfer to other meta dataset. The following cases should be supported
+
     - A meta-model trained on meta-dataset A and then applied to meta-dataset B
+
         - Some pattern are shared between meta-dataset A and B, so meta-input on meta-dataset A are used when meta model are applied on meta-dataset-B
     """
 

qlib/model/meta/task.py

@@ -11,9 +11,11 @@ class MetaTask:
     It serves as a component as in MetaDatasetDS
 
     The data processing is different
+
     - the processed input may be different between training and testing
+
         - When training, the X, y, X_test, y_test in training tasks are necessary (# PROC_MODE_FULL #)
-                                                but not necessary in test tasks. (# PROC_MODE_TEST #)
+          but not necessary in test tasks. (# PROC_MODE_TEST #)
         - When the meta model can be transferred into other dataset, only meta_info is necessary  (# PROC_MODE_TRANSFER #)
     """
 
@@ -24,6 +26,7 @@ class MetaTask:
     def __init__(self, task: dict, meta_info: object, mode: str = PROC_MODE_FULL):
         """
         The `__init__` func is responsible for
+
         - store the task
         - store the origin input data for
         - process the input data for meta data