use paddle.text.datasets.UCIHousing (#1999)

Co-authored-by: co63oc <[email protected]>

Author: co63oc

backends/npu/tests/unittests/test_adadelta_op_npu.py

@@ -188,14 +188,12 @@ def test_adadelta(self):
             rms_optimizer.minimize(avg_cost)
 
             fetch_list = [avg_cost]
-            train_reader = paddle.batch(
-                paddle.dataset.uci_housing.train(), batch_size=1
-            )
+            uci_housing = paddle.text.datasets.UCIHousing(mode="train")
             feeder = base.DataFeeder(place=place, feed_list=[x, y])
             exe = base.Executor(place)
             exe.run(base.default_startup_program())
-            for data in train_reader():
-                exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
+            for data in uci_housing:
+                exe.run(main, feed=feeder.feed([data]), fetch_list=fetch_list)
 
     def test_raise_error(self):
         self.assertRaises(ValueError, paddle.optimizer.Adadelta, None)

backends/sdaa/tests/unittests/test_momentum_op_sdaa.py

@@ -143,14 +143,12 @@ def test_momentum(self):
             rms_optimizer.minimize(avg_cost)
 
             fetch_list = [avg_cost]
-            train_reader = paddle.batch(
-                paddle.dataset.uci_housing.train(), batch_size=1
-            )
+            uci_housing = paddle.text.datasets.UCIHousing(mode="train")
             feeder = base.DataFeeder(place=place, feed_list=[x, y])
             exe = base.Executor(place)
             exe.run(base.default_startup_program())
-            for data in train_reader():
-                exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
+            for data in uci_housing:
+                exe.run(main, feed=feeder.feed([data]), fetch_list=fetch_list)
 
     def test_raise_error(self):
         self.assertRaises(ValueError, paddle.optimizer.Momentum, learning_rate=None)
@@ -267,14 +265,12 @@ def test_momentum_static(self):
             momentum_optimizer.minimize(avg_cost)
 
             fetch_list = [avg_cost]
-            train_reader = paddle.batch(
-                paddle.dataset.uci_housing.train(), batch_size=1
-            )
+            uci_housing = paddle.text.datasets.UCIHousing(mode="train")
             feeder = base.DataFeeder(place=place, feed_list=[x, y])
             exe = base.Executor(place)
             exe.run(base.default_startup_program())
-            for data in train_reader():
-                exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
+            for data in uci_housing:
+                exe.run(main, feed=feeder.feed([data]), fetch_list=fetch_list)
 
 
 class TestMomentumOpVsMomentumOpWithDecayAPI(unittest.TestCase):