chore: import upstream snapshot with attribution

test/legacy_test/test_imperative_data_loader_base.py

@@ -0,0 +1,103 @@
+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+
+import paddle.nn.functional as F
+from paddle import base
+from paddle.base.reader import use_pinned_memory
+
+
+def get_random_images_and_labels(image_shape, label_shape):
+    image = np.random.random(size=image_shape).astype('float32')
+    label = np.random.random(size=label_shape).astype('int64')
+    return image, label
+
+
+def sample_generator_creator(batch_size, batch_num):
+    def __reader__():
+        for _ in range(batch_num * batch_size):
+            image, label = get_random_images_and_labels([784], [1])
+            yield image, label
+
+    return __reader__
+
+
+class TestDygraphDataLoader(unittest.TestCase):
+    def setUp(self):
+        self.batch_size = 8
+        self.batch_num = 4
+        self.epoch_num = 1
+        self.capacity = 5
+
+    def iter_loader_data(self, loader):
+        for _ in range(self.epoch_num):
+            for image, label in loader():
+                relu = F.relu(image)
+                self.assertEqual(image.shape, [self.batch_size, 784])
+                self.assertEqual(label.shape, [self.batch_size, 1])
+                self.assertEqual(relu.shape, [self.batch_size, 784])
+
+    def test_single_process_loader(self):
+        with base.dygraph.guard():
+            loader = base.io.DataLoader.from_generator(
+                capacity=self.capacity, iterable=False, use_multiprocess=False
+            )
+            loader.set_sample_generator(
+                sample_generator_creator(self.batch_size, self.batch_num),
+                batch_size=self.batch_size,
+                places=base.CPUPlace(),
+            )
+            self.iter_loader_data(loader)
+
+    def test_multi_process_loader(self):
+        with base.dygraph.guard():
+            loader = base.io.DataLoader.from_generator(
+                capacity=self.capacity, use_multiprocess=True
+            )
+            loader.set_sample_generator(
+                sample_generator_creator(self.batch_size, self.batch_num),
+                batch_size=self.batch_size,
+                places=base.CPUPlace(),
+            )
+            self.iter_loader_data(loader)
+
+    def test_generator_no_places(self):
+        with base.dygraph.guard():
+            loader = base.io.DataLoader.from_generator(capacity=self.capacity)
+            loader.set_sample_generator(
+                sample_generator_creator(self.batch_size, self.batch_num),
+                batch_size=self.batch_size,
+            )
+            self.iter_loader_data(loader)
+
+    def test_set_pin_memory(self):
+        with base.dygraph.guard():
+            use_pinned_memory(False)
+            loader = base.io.DataLoader.from_generator(
+                capacity=self.capacity, iterable=False, use_multiprocess=False
+            )
+            loader.set_sample_generator(
+                sample_generator_creator(self.batch_size, self.batch_num),
+                batch_size=self.batch_size,
+                places=base.CPUPlace(),
+            )
+            self.iter_loader_data(loader)
+            use_pinned_memory(True)
+
+
+if __name__ == '__main__':
+    unittest.main()