repair format and type problem in split

mindspore/dataset/engine/datasets.py

@@ -613,7 +613,7 @@ class Dataset:
         # if we still need more rows, give them to the first split.
         # if we have too many rows, remove the extras from the first split that has
         # enough rows.
-        size_difference = dataset_size - absolute_sizes_sum
+        size_difference = int(dataset_size - absolute_sizes_sum)
         if size_difference > 0:
             absolute_sizes[0] += size_difference
         else:
@@ -647,10 +647,14 @@ class Dataset:
                 Datasets of size round(f1*K), round(f2*K), …, round(fn*K) where K is the size of the
                 original dataset.
                 If after rounding:
+
                     - Any size equals 0, an error will occur.
+
                     - The sum of split sizes < K, the difference will be added to the first split.
+
                     - The sum of split sizes > K, the difference will be removed from the first large
                       enough split such that it will have atleast 1 row after removing the difference.
+
             randomize (bool, optional): determines whether or not to split the data randomly (default=True).
                 If true, the data will be randomly split. Otherwise, each split will be created with
                 consecutive rows from the dataset.
@@ -1282,10 +1286,14 @@ class MappableDataset(SourceDataset):
                 Datasets of size round(f1*K), round(f2*K), …, round(fn*K) where K is the size of the
                 original dataset.
                 If after rounding:
+
                     - Any size equals 0, an error will occur.
+
                     - The sum of split sizes < K, the difference will be added to the first split.
+
                     - The sum of split sizes > K, the difference will be removed from the first large
                       enough split such that it will have atleast 1 row after removing the difference.
+
             randomize (bool, optional): determines whether or not to split the data randomly (default=True).
                 If true, the data will be randomly split. Otherwise, each split will be created with
                 consecutive rows from the dataset.