!44491 fix: numpy slices dataset with diff shape datas

Merge pull request !44491 from guozhijian/fix_slice_dataset_with_diff_shape

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/dataset_node.cc

@@ -53,9 +53,10 @@ Status ComputeShuffleSize(int64_t num_files, int64_t num_devices, int64_t num_ro
   CHECK_FAIL_RETURN_UNEXPECTED(num_files != 0, "The size of dataset_files must be greater than 0.");
   int64_t avg_rows_per_file = num_rows / num_files;
 
-  *shuffle_size = shuffle_max;
-  if (avg_rows_per_file != 0 && *shuffle_size > (avg_rows_per_file * average_files_multiplier)) {
-    *shuffle_size = avg_rows_per_file * average_files_multiplier;
+  if (avg_rows_per_file != 0) {
+    *shuffle_size = std::min(avg_rows_per_file * average_files_multiplier, shuffle_max);
+  } else {
+    *shuffle_size = shuffle_max;
   }
 
   return Status::OK();

mindspore/python/mindspore/dataset/engine/datasets_user_defined.py

@@ -776,10 +776,8 @@ class _NumpySlicesDataset:
             data = self.process_dict(data)
 
         if isinstance(data, tuple):
-            self.data = ()
+            self.data = data
             data_len = len(data)
-            for i in range(data_len):
-                self.data = self.data + (np.array(data[i]),)
         else:
             self.data = (np.array(data),)
 
@@ -798,7 +796,7 @@ class _NumpySlicesDataset:
                 self.column_list.append("column_" + str(i))
 
     def __getitem__(self, index):
-        data_row = [d[index, ...] for d in self.data]
+        data_row = [d[index] for d in self.data]
         data_res = tuple(data_row)
         return data_res
 

tests/ut/python/dataset/test_dataset_numpy_slices.py

@@ -373,6 +373,50 @@ def test_numpy_slice_empty_output_shape():
     assert dataset.output_shapes() == []
 
 
+def test_numpy_slice_with_diff_shape():
+    """
+    Feature: NumpySlicesDataset
+    Description: Check if NumpySlicesDataset produces diff shape data
+    Expectation: The dataset is processed success
+    """
+    data1 = np.array([1], dtype=np.uint8)
+    data2 = np.array([5, 6], dtype=np.uint8)
+    data3 = np.array([9, 10, 11], dtype=np.uint8)
+    data4 = np.array([13, 14, 15, 16], dtype=np.uint8)
+
+    data = [data1, data2, data3, data4]
+
+    label = [1, 2, 3, 4]
+
+    dataset = de.NumpySlicesDataset((data, label), ["data", "label"], num_shards=4, shard_id=2, shuffle=False)
+
+    for item in dataset.create_dict_iterator(output_numpy=True):
+        assert (item["data"] == data3).all()
+
+
+def test_numpy_slice_with_diff_shape_dict():
+    """
+    Feature: NumpySlicesDataset
+    Description: Check if NumpySlicesDataset produces diff shape data by dict
+    Expectation: The dataset is processed success
+    """
+    data1 = np.array([1], dtype=np.uint8)
+    data2 = np.array([5, 6], dtype=np.uint8)
+    data3 = np.array([9, 10, 11], dtype=np.uint8)
+    data4 = np.array([13, 14, 15, 16], dtype=np.uint8)
+
+    data = [data1, data2, data3, data4]
+
+    label = [1, 2, 3, 4]
+
+    dict_data = {"data": data, "label": label}
+
+    dataset = de.NumpySlicesDataset(dict_data, num_shards=4, shard_id=2, shuffle=False)
+
+    for item in dataset.create_dict_iterator(output_numpy=True):
+        assert (item["data"] == data3).all()
+
+
 if __name__ == "__main__":
     test_numpy_slices_list_1()
     test_numpy_slices_list_2()
@@ -394,3 +438,5 @@ if __name__ == "__main__":
     test_numpy_slices_invalid_empty_column_names()
     test_numpy_slices_invalid_empty_data_column()
     test_numpy_slice_empty_output_shape()
+    test_numpy_slice_with_diff_shape()
+    test_numpy_slice_with_diff_shape_dict()