minddata fix generatordataset get_dataset_size issue

mindspore/dataset/engine/datasets.py

@@ -3780,6 +3780,18 @@ class GeneratorDataset(MappableDataset):
             self.schema = schema
             if not isinstance(schema, Schema):
                 self.schema = Schema(schema)
+        # Move get dataset_size by len from parse to here, because self.source will
+        # lose attribution of '__len__' after deepcopy.
+        self.dataset_size = None
+        if hasattr(self.source, "__len__"):
+            if not self.num_shards:
+                self.dataset_size = len(self.source)
+            else:
+                self.dataset_size = math.ceil(len(self.source) / self.num_shards)
+
+            rows_from_sampler = self._get_sampler_dataset_size()
+            if rows_from_sampler is not None and rows_from_sampler < self.dataset_size:
+                self.dataset_size = rows_from_sampler
 
     def __deepcopy__(self, memodict):
         if id(self) in memodict:
@@ -3838,24 +3850,16 @@ class GeneratorDataset(MappableDataset):
         return self.sampler.is_sharded()
 
     def parse(self, children=None):
-        dataset_size = -1
+        if self.dataset_size is None:
-        if hasattr(self.source, "__len__"):
+            self.dataset_size = -1
-            if not self.num_shards:
-                dataset_size = len(self.source)
-            else:
-                dataset_size = math.ceil(len(self.source) / self.num_shards)
-
-            rows_from_sampler = self._get_sampler_dataset_size()
-            if rows_from_sampler is not None and rows_from_sampler < dataset_size:
-                dataset_size = rows_from_sampler
         if self.schema is None:
             return cde.GeneratorNode(self.source, self.column_names, self.column_types).SetGeneratorDatasetSize(
-                dataset_size) \
+                self.dataset_size) \
                 .SetNumWorkers(self.num_parallel_workers)
         schema = self.schema
         if isinstance(schema, Schema):
             schema = self.schema.cpp_schema
-        return cde.GeneratorNode(self.source, schema).SetGeneratorDatasetSize(dataset_size).SetNumWorkers(
+        return cde.GeneratorNode(self.source, schema).SetGeneratorDatasetSize(self.dataset_size).SetNumWorkers(
             self.num_parallel_workers)