🚚 Refactor: moved uint8 support for sign to PaddlePaddle#59514

PommesPeter · Nov 29, 2023 · e11eeca · e11eeca
1 parent e86aeee
commit e11eeca
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Showing 5 changed files with 11 additions and 31 deletions.
diff --git a/paddle/phi/kernels/cpu/sign_kernel.cc b/paddle/phi/kernels/cpu/sign_kernel.cc
@@ -25,7 +25,6 @@ PD_REGISTER_KERNEL(sign,
                    CPU,
                    ALL_LAYOUT,
                    phi::SignKernel,
-                   uint8_t,
                    int8_t,
                    int16_t,
                    int32_t,

diff --git a/paddle/phi/kernels/funcs/eigen/sign.cc b/paddle/phi/kernels/funcs/eigen/sign.cc
@@ -29,7 +29,6 @@ struct EigenSign<Eigen::DefaultDevice, T> {
   }
 };
 
-template struct EigenSign<Eigen::DefaultDevice, uint8_t>;
 template struct EigenSign<Eigen::DefaultDevice, int8_t>;
 template struct EigenSign<Eigen::DefaultDevice, int16_t>;
 template struct EigenSign<Eigen::DefaultDevice, int32_t>;

diff --git a/paddle/phi/kernels/funcs/eigen/sign.cu b/paddle/phi/kernels/funcs/eigen/sign.cu
@@ -29,7 +29,6 @@ struct EigenSign<Eigen::GpuDevice, T> {
   }
 };
 
-template struct EigenSign<Eigen::GpuDevice, uint8_t>;
 template struct EigenSign<Eigen::GpuDevice, int8_t>;
 template struct EigenSign<Eigen::GpuDevice, int16_t>;
 template struct EigenSign<Eigen::GpuDevice, int32_t>;

diff --git a/paddle/phi/kernels/gpu/sign_kernel.cu.cc b/paddle/phi/kernels/gpu/sign_kernel.cu.cc
@@ -25,7 +25,6 @@ PD_REGISTER_KERNEL(sign,
                    GPU,
                    ALL_LAYOUT,
                    phi::SignKernel,
-                   uint8_t,
                    int8_t,
                    int16_t,
                    int32_t,

diff --git a/test/legacy_test/test_sign_op.py b/test/legacy_test/test_sign_op.py
@@ -93,64 +93,48 @@ def test_dygraph(self):
             self.assertEqual((np_z == z_expected).all(), True)
 
     def test_static(self):
-        np_input1 = np.random.uniform(-10, 10, (12, 10)).astype("int8")
-        np_input2 = np.random.uniform(-10, 10, (12, 10)).astype("uint8")
-        np_input3 = np.random.uniform(-10, 10, (12, 10)).astype("int16")
-        np_input4 = np.random.uniform(-10, 10, (12, 10)).astype("int32")
-        np_input5 = np.random.uniform(-10, 10, (12, 10)).astype("int64")
-        np_out1 = np.sign(np_input1)
+        np_input2 = np.random.uniform(-10, 10, (12, 10)).astype("int16")
+        np_input3 = np.random.uniform(-10, 10, (12, 10)).astype("int32")
+        np_input4 = np.random.uniform(-10, 10, (12, 10)).astype("int64")
         np_out2 = np.sign(np_input2)
         np_out3 = np.sign(np_input3)
         np_out4 = np.sign(np_input4)
-        np_out5 = np.sign(np_input5)
 
         def run(place):
             with program_guard(Program(), Program()):
                 # The input type of sign_op must be Variable or numpy.ndarray.
                 input1 = 12
                 self.assertRaises(TypeError, paddle.tensor.math.sign, input1)
                 # The result of sign_op must correct.
-                input1 = paddle.static.data(
-                    name='input1', shape=[12, 10], dtype="int8"
-                )
                 input2 = paddle.static.data(
-                    name='input2', shape=[12, 10], dtype="uint8"
+                    name='input2', shape=[12, 10], dtype="int16"
                 )
                 input3 = paddle.static.data(
-                    name='input3', shape=[12, 10], dtype="int16"
+                    name='input3', shape=[12, 10], dtype="int32"
                 )
                 input4 = paddle.static.data(
-                    name='input4', shape=[12, 10], dtype="int32"
-                )
-                input5 = paddle.static.data(
-                    name='input5', shape=[12, 10], dtype="int64"
+                    name='input4', shape=[12, 10], dtype="int64"
                 )
-                out1 = paddle.sign(input1)
                 out2 = paddle.sign(input2)
                 out3 = paddle.sign(input3)
                 out4 = paddle.sign(input4)
-                out5 = paddle.sign(input5)
                 exe = paddle.static.Executor(place)
-                res1, res2, res3, res4, res5 = exe.run(
+                res2, res3, res4 = exe.run(
                     paddle.static.default_main_program(),
                     feed={
-                        "input1": np_input1,
                         "input2": np_input2,
                         "input3": np_input3,
                         "input4": np_input4,
-                        "input5": np_input5,
                     },
-                    fetch_list=[out1, out2, out3, out4, out5],
+                    fetch_list=[out2, out3, out4],
                 )
-                self.assertEqual((res1 == np_out1).all(), True)
                 self.assertEqual((res2 == np_out2).all(), True)
                 self.assertEqual((res3 == np_out3).all(), True)
                 self.assertEqual((res4 == np_out4).all(), True)
-                self.assertEqual((res5 == np_out5).all(), True)
-                input6 = paddle.static.data(
-                    name='input6', shape=[-1, 4], dtype="float16"
+                input5 = paddle.static.data(
+                    name='input5', shape=[-1, 4], dtype="float16"
                 )
-                paddle.sign(input6)
+                paddle.sign(input5)
 
         for place in self.place:
             run(place)