update unittest accuracy to float64 for relu, prelu, maxout (#22273)

paddle/fluid/operators/maxout_op.cc

@@ -118,7 +118,9 @@ REGISTER_OPERATOR(
     paddle::framework::DefaultGradOpMaker<paddle::imperative::OpBase, true>);
 REGISTER_OPERATOR(maxout_grad, ops::MaxOutOpGrad);
 REGISTER_OP_CPU_KERNEL(
-    maxout, ops::MaxOutKernel<paddle::platform::CPUDeviceContext, float>);
+    maxout, ops::MaxOutKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::MaxOutKernel<paddle::platform::CPUDeviceContext, double>);
 REGISTER_OP_CPU_KERNEL(
     maxout_grad,
-    ops::MaxOutGradKernel<paddle::platform::CPUDeviceContext, float>);
+    ops::MaxOutGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::MaxOutGradKernel<paddle::platform::CPUDeviceContext, double>);

paddle/fluid/operators/prelu_op.cc

@@ -161,7 +161,8 @@ REGISTER_OPERATOR(prelu, ops::PReluOp, ops::PReluOpMaker,
                   ops::PReluGradOpMaker<paddle::imperative::OpBase>);
 REGISTER_OPERATOR(prelu_grad, ops::PReluGradOp);
 REGISTER_OP_CPU_KERNEL(
-    prelu, ops::PReluKernel<paddle::platform::CPUDeviceContext, float>);
+    prelu, ops::PReluKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::PReluKernel<paddle::platform::CPUDeviceContext, double>);
 REGISTER_OP_CPU_KERNEL(
-    prelu_grad,
-    ops::PReluGradKernel<paddle::platform::CPUDeviceContext, float>);
+    prelu_grad, ops::PReluGradKernel<paddle::platform::CPUDeviceContext, float>,
+    ops::PReluGradKernel<paddle::platform::CPUDeviceContext, double>);

python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py

@@ -17,7 +17,7 @@ from __future__ import print_function
 import unittest
 import numpy as np
 import paddle.fluid.core as core
-from paddle.fluid.tests.unittests.op_test import OpTest
+from paddle.fluid.tests.unittests.op_test import OpTest, skip_check_grad_ci
 from paddle.fluid.tests.unittests.test_activation_op import TestRelu, TestTanh, TestSqrt, TestAbs, TestLeakyRelu
 from mkldnn_op_test import check_if_mkldnn_primitives_exist_in_bwd
 
@@ -111,6 +111,7 @@ class TestMKLDNNAbsDim2(TestAbs):
             ['X'], 'Out', max_relative_error=0.007, check_dygraph=False)
 
 
+@skip_check_grad_ci(reason="Use float32 in mkldnn relu op.")
 class TestMKLDNNReluDim4(TestRelu):
     def setUp(self):
         super(TestMKLDNNReluDim4, self).setUp()

python/paddle/fluid/tests/unittests/ngraph/test_activation_ngraph_op.py

@@ -17,10 +17,11 @@ from __future__ import print_function
 import unittest, sys
 sys.path.append("../")
 import numpy as np
-from op_test import OpTest
+from op_test import OpTest, skip_check_grad_ci
 from test_activation_op import TestAbs, TestGelu, TestSigmoid, TestSquare, TestRelu, TestTanh
 
 
+@skip_check_grad_ci(reason="Use float32 in ngraph relu op.")
 class TestNGRAPHReluDim4(TestRelu):
     def setUp(self):
         super(TestNGRAPHReluDim4, self).setUp()

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

@@ -34,14 +34,13 @@ class TestMaxOutOp(OpTest):
     def setUp(self):
         self.op_type = "maxout"
         self.init_test_case()
-        input = np.random.random(self.shape).astype("float32")
-        output = self.MaxOut_forward_naive(input, self.groups,
-                                           self.axis).astype("float32")
+        input = np.random.random(self.shape)
+        output = self.MaxOut_forward_naive(input, self.groups, self.axis)
 
         self.inputs = {'X': input}
         self.attrs = {'groups': self.groups, 'axis': self.axis}
 
-        self.outputs = {'Out': output.astype('float32')}
+        self.outputs = {'Out': output}
 
     def test_check_output(self):
         self.check_output()

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

@@ -26,20 +26,18 @@ class PReluTest(OpTest):
         self.init_attr()
         self.op_type = "prelu"
 
-        x_np = np.random.uniform(-1, 1, self.x_shape).astype("float32")
+        x_np = np.random.uniform(-1, 1, self.x_shape)
         # Since zero point in prelu is not differentiable, avoid randomize
         # zero.
         x_np[np.abs(x_np) < 0.005] = 0.02
 
         if self.attrs == {'mode': "all"}:
-            alpha_np = np.random.rand(1).astype("float32")
-            self.inputs = {'X': x_np, 'Alpha': alpha_np}
+            alpha_np = np.random.uniform(-1, -0.5, (1))
         elif self.attrs == {'mode': "channel"}:
-            alpha_np = np.random.rand(1, x_np.shape[1], 1, 1).astype("float32")
-            self.inputs = {'X': x_np, 'Alpha': alpha_np}
+            alpha_np = np.random.uniform(-1, -0.5, (1, x_np.shape[1], 1, 1))
         else:
-            alpha_np = np.random.rand(1, x_np.shape[1], x_np.shape[2],
-                                      x_np.shape[3]).astype("float32")
+            alpha_np = np.random.uniform(-1, -0.5, \
+                (1, x_np.shape[1], x_np.shape[2], x_np.shape[3]))
         self.inputs = {'X': x_np, 'Alpha': alpha_np}
 
         out_np = np.maximum(self.inputs['X'], 0.)

python/paddle/fluid/tests/unittests/white_list/op_accuracy_white_list.py

@@ -46,7 +46,6 @@ NO_FP64_CHECK_GRAD_OP_LIST = [
     'matmul', \
     'max_pool2d_with_index', \
     'max_pool3d_with_index', \
-    'maxout', \
     'minus', \
     'modified_huber_loss', \
     'mul', \
@@ -56,12 +55,10 @@ NO_FP64_CHECK_GRAD_OP_LIST = [
     'pad_constant_like', \
     'pool2d', \
     'pool3d', \
-    'prelu', \
     'prroi_pool', \
     'rank_loss', \
     'reduce_max', \
     'reduce_min', \
-    'relu', \
     'reshape2', \
     'roi_perspective_transform', \
     'row_conv', \