!94 enhance: reduce execution time for mindrecord test case

Merge pull request !94 from yanzhenxiang2020/fix_mindrecord_ut_long_time

mindspore/mindrecord/tools/mnist_to_mr.py

@@ -77,20 +77,20 @@ class MnistToMR:
 
         self.mnist_schema_json = {"label": {"type": "int64"}, "data": {"type": "bytes"}}
 
-    def _extract_images(self, filename, num_images):
+    def _extract_images(self, filename):
         """Extract the images into a 4D tensor [image index, y, x, channels]."""
         with gzip.open(filename) as bytestream:
             bytestream.read(16)
-            buf = bytestream.read(self.image_size * self.image_size * num_images * self.num_channels)
+            buf = bytestream.read()
             data = np.frombuffer(buf, dtype=np.uint8)
-            data = data.reshape(num_images, self.image_size, self.image_size, self.num_channels)
+            data = data.reshape(-1, self.image_size, self.image_size, self.num_channels)
             return data
 
-    def _extract_labels(self, filename, num_images):
+    def _extract_labels(self, filename):
         """Extract the labels into a vector of int64 label IDs."""
         with gzip.open(filename) as bytestream:
             bytestream.read(8)
-            buf = bytestream.read(1 * num_images)
+            buf = bytestream.read()
             labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)
             return labels
 
@@ -101,8 +101,8 @@ class MnistToMR:
         Yields:
             data (dict of list): mnist data list which contains dict.
         """
-        train_data = self._extract_images(self.train_data_filename_, 60000)
-        train_labels = self._extract_labels(self.train_labels_filename_, 60000)
+        train_data = self._extract_images(self.train_data_filename_)
+        train_labels = self._extract_labels(self.train_labels_filename_)
         for data, label in zip(train_data, train_labels):
             _, img = cv2.imencode(".jpeg", data)
             yield {"label": int(label), "data": img.tobytes()}
@@ -114,8 +114,8 @@ class MnistToMR:
         Yields:
             data (dict of list): mnist data list which contains dict.
         """
-        test_data = self._extract_images(self.test_data_filename_, 10000)
-        test_labels = self._extract_labels(self.test_labels_filename_, 10000)
+        test_data = self._extract_images(self.test_data_filename_)
+        test_labels = self._extract_labels(self.test_labels_filename_)
         for data, label in zip(test_data, test_labels):
             _, img = cv2.imencode(".jpeg", data)
             yield {"label": int(label), "data": img.tobytes()}

tests/ut/python/mindrecord/test_mindrecord_base.py

@@ -203,9 +203,9 @@ def test_nlp_page_reader_tutorial():
         os.remove("{}".format(x))
         os.remove("{}.db".format(x))
 
-def test_cv_file_writer_shard_num_1000():
-    """test file writer when shard num equals 1000."""
-    writer = FileWriter(CV_FILE_NAME, 1000)
+def test_cv_file_writer_shard_num_10():
+    """test file writer when shard num equals 10."""
+    writer = FileWriter(CV_FILE_NAME, 10)
     data = get_data("../data/mindrecord/testImageNetData/")
     cv_schema_json = {"file_name": {"type": "string"},
                       "label": {"type": "int64"}, "data": {"type": "bytes"}}
@@ -214,8 +214,8 @@ def test_cv_file_writer_shard_num_1000():
     writer.write_raw_data(data)
     writer.commit()
 
-    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(3, '0'))
-             for x in range(1000)]
+    paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
+            for x in range(10)]
     for x in paths:
         os.remove("{}".format(x))
         os.remove("{}.db".format(x))

tests/ut/python/mindrecord/test_mnist_to_mr.py

@@ -37,7 +37,7 @@ def read(train_name, test_name):
         count = count + 1
         if count == 1:
             logger.info("data: {}".format(x))
-    assert count == 60000
+    assert count == 20
     reader.close()
 
     count = 0
@@ -47,7 +47,7 @@ def read(train_name, test_name):
         count = count + 1
         if count == 1:
             logger.info("data: {}".format(x))
-    assert count == 10000
+    assert count == 10
     reader.close()
 
 
@@ -102,10 +102,10 @@ def test_mnist_to_mindrecord_compare_data():
                                        't10k-images-idx3-ubyte.gz')
     test_labels_filename_ = os.path.join(MNIST_DIR,
                                          't10k-labels-idx1-ubyte.gz')
-    train_data = _extract_images(train_data_filename_, 60000)
-    train_labels = _extract_labels(train_labels_filename_, 60000)
-    test_data = _extract_images(test_data_filename_, 10000)
-    test_labels = _extract_labels(test_labels_filename_, 10000)
+    train_data = _extract_images(train_data_filename_, 20)
+    train_labels = _extract_labels(train_labels_filename_, 20)
+    test_data = _extract_images(test_data_filename_, 10)
+    test_labels = _extract_labels(test_labels_filename_, 10)
 
     reader = FileReader(train_name)
     for x, data, label in zip(reader.get_next(), train_data, train_labels):