1. add set_dataset_size for MindDataset 2. modify parameter dupe_factor from 5 to 10

example/nlp_to_mindrecord/zhwiki/run.sh

@@ -83,7 +83,7 @@ for index in $(seq 0 $file_list_len); do
         --max_predictions_per_seq=20 \
         --masked_lm_prob=0.15 \
         --random_seed=12345 \
-        --dupe_factor=5 >/tmp/${output_filename[$index]}.log 2>&1 &
+        --dupe_factor=10 >/tmp/${output_filename[$index]}.log 2>&1 &   # user defined
     process_count=`ps -ef | grep create_pretraining_data_patched | grep -v grep | wc -l`
     echo "Total task: ${#file_list[*]}, processing: ${process_count}"
     if [ $process_count -ge $avaiable_core_size ]; then

example/nlp_to_mindrecord/zhwiki/run_simple.sh

@@ -44,4 +44,4 @@ python ../../../third_party/to_mindrecord/zhwiki/create_pretraining_data_patched
 --max_predictions_per_seq=20 \
 --masked_lm_prob=0.15 \
 --random_seed=12345 \
---dupe_factor=5
+--dupe_factor=10    # user defined

mindspore/dataset/engine/datasets.py

@@ -2671,20 +2671,30 @@ class MindDataset(SourceDataset):
         Return:
             Number, number of batches.
         """
-        if self.load_dataset:
-            dataset_file = [self.dataset_file]
-        else:
-            dataset_file = self.dataset_file
-        num_rows = MindRecordOp.get_num_rows(dataset_file, self.load_dataset, self.sampler, self.num_padded)
-        if self.partitions is not None and self.partitions[0] > 0:
-            if num_rows % self.partitions[0] == 0:
-                num_rows = num_rows // self.partitions[0]
+        if self._dataset_size is None:
+            if self.load_dataset:
+                dataset_file = [self.dataset_file]
             else:
-                if self.num_padded > 0:
-                    raise RuntimeError(
-                        "Dataset size plus number of padded samples is not divisible by number of shards.")
-                num_rows = num_rows // self.partitions[0] + 1
-        return num_rows
+                dataset_file = self.dataset_file
+            num_rows = MindRecordOp.get_num_rows(dataset_file, self.load_dataset, self.sampler, self.num_padded)
+            if self.partitions is not None and self.partitions[0] > 0:
+                if num_rows % self.partitions[0] == 0:
+                    num_rows = num_rows // self.partitions[0]
+                else:
+                    if self.num_padded > 0:
+                        raise RuntimeError(
+                            "Dataset size plus number of padded samples is not divisible by number of shards.")
+                    num_rows = num_rows // self.partitions[0] + 1
+            return num_rows
+        return self._dataset_size
+
+    # manually set dataset_size as a tempoary solution.
+    def set_dataset_size(self, value):
+        logger.warning("WARN_DEPRECATED: This method is deprecated. Please use get_dataset_size directly.")
+        if value >= 0:
+            self._dataset_size = value
+        else:
+            raise ValueError('set dataset_size with negative value {}'.format(value))
 
     def is_shuffled(self):
         if self.shuffle_option is None: