Add py_reader combination unittest (#19923)

* add py_reader combination unittest,test=develop

* follow huihuang's comments, test=develop

python/paddle/fluid/tests/unittests/test_py_reader_combination.py

+# 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 paddle.fluid as fluid
+import unittest
+import numpy as np
+
+
+class TestPyReaderCombination(unittest.TestCase):
+    def setUp(self):
+        self.n1 = 10
+        self.n2 = 20
+        self.batch_size = 2
+
+    def create_reader(self, batch_num):
+        def __impl__():
+            for _ in range(batch_num):
+                image = np.random.uniform(
+                    low=-1, high=1, size=[batch_num, 784]).astype('float32')
+                label = np.random.random_integers(
+                    low=0, high=9, size=[batch_num, 1]).astype('int64')
+                yield image, label
+
+        return __impl__
+
+    def assertFeedVarEqual(self, reader_list_data, py_reader_dict_data):
+        image1 = reader_list_data[0]
+        label1 = reader_list_data[1]
+
+        image2 = np.array(py_reader_dict_data[0]['image'])
+        label2 = np.array(py_reader_dict_data[0]['label'])
+        self.assertTrue(np.array_equal(image1, image2))
+        self.assertTrue(np.array_equal(label1, label2))
+
+    def main_impl(self, place):
+        with fluid.program_guard(fluid.Program(), fluid.Program()):
+            image = fluid.layers.data(
+                name='image', dtype='float32', shape=[784])
+            label = fluid.layers.data(name='label', dtype='int64', shape=[1])
+
+            py_reader1 = fluid.io.PyReader(
+                feed_list=[image, label], capacity=16, iterable=True)
+            py_reader2 = fluid.io.PyReader(
+                feed_list=[image, label], capacity=16, iterable=True)
+
+            reader1 = fluid.io.cache(self.create_reader(self.n1))
+            reader2 = fluid.io.cache(self.create_reader(self.n2))
+            py_reader1.decorate_batch_generator(reader1, places=place)
+            py_reader2.decorate_batch_generator(reader2, places=place)
+
+            for _ in range(10):
+                max_num = min(self.n1, self.n2)
+                batch_num = 0
+                for reader_np1, py_reader_dict1, reader_np2, py_reader_dict2 in zip(
+                        reader1(), py_reader1(), reader2(), py_reader2()):
+                    self.assertFeedVarEqual(reader_np1, py_reader_dict1)
+                    self.assertFeedVarEqual(reader_np2, py_reader_dict2)
+                    batch_num += 1
+
+                self.assertEqual(batch_num, max_num)
+
+    def get_places(self):
+        if fluid.is_compiled_with_cuda():
+            return [fluid.CUDAPlace(0), fluid.CPUPlace()]
+        else:
+            return [fluid.CPUPlace()]
+
+    def test_main(self):
+        for p in self.get_places():
+            self.main_impl(p)
+
+
+class TestPyReaderCombination2(TestPyReaderCombination):
+    def setUp(self):
+        self.n1 = 20
+        self.n2 = 10
+        self.batch_size = 2
+
+
+class TestPyReaderCombination3(TestPyReaderCombination):
+    def setUp(self):
+        self.n1 = 10
+        self.n2 = 10
+        self.batch_size = 2
+
+
+if __name__ == '__main__':
+    unittest.main()