fix adam fp64, test=develop (#21423)

python/paddle/fluid/optimizer.py

@@ -1628,14 +1628,12 @@ class AdamOptimizer(Optimizer):
             self._add_accumulator(
                 name=self._beta1_pow_acc_str,
                 param=p,
-                dtype='float32',
                 fill_value=0.9 if isinstance(self._beta1, Variable) \
                         else self._beta1,
                 shape=[1])
             self._add_accumulator(
                 name=self._beta2_pow_acc_str,
                 param=p,
-                dtype='float32',
                 fill_value=0.999 if isinstance(self._beta2, Variable) \
                         else self._beta2,
                 shape=[1])
@@ -1835,7 +1833,6 @@ class AdamaxOptimizer(Optimizer):
             self._add_accumulator(
                 name=self._beta1_pow_acc_str,
                 param=p,
-                dtype='float32',
                 fill_value=self._beta1,
                 shape=[1])
 

python/paddle/fluid/tests/unittests/test_adam_optimizer_fp32_fp64.py

@@ -0,0 +1,66 @@
+# 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
+import paddle.fluid as fluid
+import unittest
+
+
+def get_places():
+    places = [fluid.CPUPlace()]
+    if fluid.is_compiled_with_cuda():
+        places.append(fluid.CUDAPlace(0))
+    return places
+
+
+def main_test_func(place, dtype):
+    main = fluid.Program()
+    startup = fluid.Program()
+    with fluid.program_guard(main, startup):
+        with fluid.scope_guard(fluid.Scope()):
+            x = fluid.data(name='x', shape=[None, 13], dtype=dtype)
+            y = fluid.data(name='y', shape=[None, 1], dtype=dtype)
+            y_predict = fluid.layers.fc(input=x, size=1, act=None)
+            cost = fluid.layers.square_error_cost(input=y_predict, label=y)
+            avg_cost = fluid.layers.mean(cost)
+
+            adam_optimizer = fluid.optimizer.AdamOptimizer(0.01)
+            adam_optimizer.minimize(avg_cost)
+
+            fetch_list = [avg_cost]
+            train_reader = fluid.io.batch(
+                paddle.dataset.uci_housing.train(), batch_size=1)
+            feeder = fluid.DataFeeder(place=place, feed_list=[x, y])
+            exe = fluid.Executor(place)
+            exe.run(fluid.default_startup_program())
+            for data in train_reader():
+                exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
+
+
+class AdamFp32Test(unittest.TestCase):
+    def setUp(self):
+        self.dtype = 'float32'
+
+    def test_main(self):
+        for p in get_places():
+            main_test_func(p, self.dtype)
+
+
+class AdamFp64Test(AdamFp32Test):
+    def setUp(self):
+        self.dtype = 'float64'
+
+
+if __name__ == '__main__':
+    unittest.main()