Incremental Training for imagenet (intel-analytics#1391)

python/dllib/src/bigdl/dllib/feature/common.py

@@ -219,9 +219,13 @@ def image_frame(cls, image_frame, memory_type="DRAM", bigdl_type="float"):
         """
         Create FeatureSet from ImageFrame.
         :param image_frame: ImageFrame
-        :param memory_type: string, DRAM or PMEM
+        :param memory_type: string, DRAM, PMEM or a Int number.
                             If it's DRAM, will cache dataset into dynamic random-access memory
                             If it's PMEM, will cache dataset into Intel Optane DC Persistent Memory
+                            If it's a Int number n, will cache dataset into disk, and only hold 1/n
+                              of the data into memory during the training. After going through the
+                              1/n, we will release the current cache, and load another 1/n into
+                              memory.
         :param bigdl_type: numeric type
         :return: A feature set
         """
@@ -249,9 +253,13 @@ def rdd(cls, rdd, memory_type="DRAM", bigdl_type="float"):
         """
         Create FeatureSet from RDD.
         :param rdd: A RDD
-        :param memory_type: string, DRAM or PMEM
+        :param memory_type: string, DRAM, PMEM or a Int number.
                             If it's DRAM, will cache dataset into dynamic random-access memory
                             If it's PMEM, will cache dataset into Intel Optane DC Persistent Memory
+                            If it's a Int number n, will cache dataset into disk, and only hold 1/n
+                              of the data into memory during the training. After going through the
+                              1/n, we will release the current cache, and load another 1/n into
+                              memory.
         :param bigdl_type:numeric type
         :return: A feature set
         """