fix bug when int or float is numpy type

mindspore/mindrecord/shardwriter.py

@@ -29,6 +29,7 @@ class ShardWriter:
 
     The class would write MindRecord File series.
     """
+
     def __init__(self):
         self._writer = ms.ShardWriter()
         self._header = None
@@ -161,7 +162,7 @@ class ShardWriter:
             if row_blob:
                 blob_data.append(list(row_blob))
             # filter raw data according to schema
-            row_raw = {field: item[field]
+            row_raw = {field: self._convert_np_types(item[field])
                        for field in self._header.schema.keys() - self._header.blob_fields if field in item}
             if row_raw:
                 raw_data.append(row_raw)
@@ -172,6 +173,12 @@ class ShardWriter:
             raise MRMWriteDatasetError
         return ret
 
+    def _convert_np_types(self, val):
+        """convert numpy type to python primitive type"""
+        if isinstance(val, (np.int32, np.int64, np.float32, np.float64)):
+            return val.item()
+        return val
+
     def _merge_blob(self, blob_data):
         """
         Merge multiple blob data whose type is bytes or ndarray

tests/ut/python/dataset/test_minddataset.py

@@ -1853,3 +1853,42 @@ def test_write_with_float32_float64_float32_array_float64_array_and_MindDataset(
 
     os.remove("{}".format(mindrecord_file_name))
     os.remove("{}.db".format(mindrecord_file_name))
+
+def test_numpy_generic():
+
+    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+             for x in range(FILES_NUM)]
+    for x in paths:
+        if os.path.exists("{}".format(x)):
+            os.remove("{}".format(x))
+        if os.path.exists("{}.db".format(x)):
+            os.remove("{}.db".format(x))
+    writer = FileWriter(CV_FILE_NAME, FILES_NUM)
+    cv_schema_json = {"label1": {"type": "int32"}, "label2": {"type": "int64"},
+                      "label3": {"type": "float32"}, "label4": {"type": "float64"}}
+    data = []
+    for idx in range(10):
+        row = {}
+        row['label1'] = np.int32(idx)
+        row['label2'] = np.int64(idx*10)
+        row['label3'] = np.float32(idx+0.12345)
+        row['label4'] = np.float64(idx+0.12345789)
+        data.append(row)
+    writer.add_schema(cv_schema_json, "img_schema")
+    writer.write_raw_data(data)
+    writer.commit()
+
+    num_readers = 4
+    data_set = ds.MindDataset(CV_FILE_NAME + "0", None, num_readers, shuffle=False)
+    assert data_set.get_dataset_size() == 10
+    idx = 0
+    for item in data_set.create_dict_iterator():
+        assert item['label1'] == item['label1']
+        assert item['label2'] == item['label2']
+        assert item['label3'] == item['label3']
+        assert item['label4'] == item['label4']
+        idx += 1
+    assert idx == 10
+    for x in paths:
+        os.remove("{}".format(x))
+        os.remove("{}.db".format(x))