fix random failed of complex matmul (#29285)

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

@@ -25,60 +25,60 @@ class TestComplexMatMulLayer(unittest.TestCase):
         if fluid.core.is_compiled_with_cuda():
             self._places.append(fluid.CUDAPlace(0))
 
-    def compare(self, x, y):
+    def compare_by_complex_api(self, x, y):
+        np_result = np.matmul(x, y)
         for place in self._places:
             with dg.guard(place):
                 x_var = dg.to_variable(x)
                 y_var = dg.to_variable(y)
                 result = paddle.complex.matmul(x_var, y_var)
-        np_result = np.matmul(x, y)
                 self.assertTrue(np.allclose(result.numpy(), np_result))
 
-    def compare_1(self, x, y):
+    def compare_by_basic_api(self, x, y):
+        np_result = np.matmul(x, y)
         for place in self._places:
             with dg.guard(place):
                 x_var = fluid.core.VarBase(
                     value=x,
-                    place=fluid.framework._current_expected_place(),
+                    place=place,
                     persistable=False,
                     zero_copy=None,
                     name='')
                 y_var = fluid.core.VarBase(
                     value=y,
-                    place=fluid.framework._current_expected_place(),
+                    place=place,
                     persistable=False,
                     zero_copy=None,
                     name='')
                 result = paddle.matmul(x_var, y_var)
-        np_result = np.matmul(x, y)
                 self.assertTrue(np.allclose(result.numpy(), np_result))
 
-    def compare_op(self, x, y):
+    def compare_op_by_complex_api(self, x, y):
+        np_result = np.matmul(x, y)
         for place in self._places:
             with dg.guard(place):
                 x_var = dg.to_variable(x)
                 y_var = dg.to_variable(y)
                 result = x_var.matmul(y_var)
-        np_result = np.matmul(x, y)
                 self.assertTrue(np.allclose(result.numpy(), np_result))
 
-    def compare_op_1(self, x, y):
+    def compare_op_by_basic_api(self, x, y):
+        np_result = np.matmul(x, y)
         for place in self._places:
             with dg.guard(place):
                 x_var = fluid.core.VarBase(
                     value=x,
-                    place=fluid.framework._current_expected_place(),
+                    place=place,
                     persistable=False,
                     zero_copy=None,
                     name='')
                 y_var = fluid.core.VarBase(
                     value=y,
-                    place=fluid.framework._current_expected_place(),
+                    place=place,
                     persistable=False,
                     zero_copy=None,
                     name='')
                 result = x_var.matmul(y_var)
-        np_result = np.matmul(x, y)
                 self.assertTrue(np.allclose(result.numpy(), np_result))
 
     def test_complex_xy(self):
@@ -88,35 +88,35 @@ class TestComplexMatMulLayer(unittest.TestCase):
         y = np.random.random(
             (2, 3, 5, 4)).astype("float32") + 1J * np.random.random(
                 (2, 3, 5, 4)).astype("float32")
-        self.compare(x, y)
-        self.compare_op(x, y)
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
+        self.compare_by_complex_api(x, y)
+        self.compare_op_by_complex_api(x, y)
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
 
     def test_complex_x(self):
         x = np.random.random(
             (2, 3, 4, 5)).astype("float32") + 1J * np.random.random(
                 (2, 3, 4, 5)).astype("float32")
         y = np.random.random((2, 3, 5, 4)).astype("float32")
-        self.compare(x, y)
-        self.compare_op(x, y)
+        self.compare_by_complex_api(x, y)
+        self.compare_op_by_complex_api(x, y)
 
     def test_complex_y(self):
         x = np.random.random((2, 3, 4, 5)).astype("float32")
         y = np.random.random(
             (2, 3, 5, 4)).astype("float32") + 1J * np.random.random(
                 (2, 3, 5, 4)).astype("float32")
-        self.compare(x, y)
+        self.compare_by_complex_api(x, y)
 
-    def test_complex128_xy(self):
+    def test_complex_xy_128(self):
         x = np.random.random(
             (2, 3, 4, 5)).astype("float64") + 1J * np.random.random(
                 (2, 3, 4, 5)).astype("float64")
         y = np.random.random(
             (2, 3, 5, 4)).astype("float64") + 1J * np.random.random(
                 (2, 3, 5, 4)).astype("float64")
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
 
     def test_complex_xy_gemv(self):
         x = np.random.random(
@@ -124,35 +124,81 @@ class TestComplexMatMulLayer(unittest.TestCase):
                 (2, 1, 100)).astype("float32")
         y = np.random.random((100)).astype("float32") + 1J * np.random.random(
             (100)).astype("float32")
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
 
         x = np.random.random(
             (2, 1, 100)).astype("float64") + 1J * np.random.random(
                 (2, 1, 100)).astype("float64")
         y = np.random.random((100)).astype("float64") + 1J * np.random.random(
             (100)).astype("float64")
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
-
-    def test_complex_xy_gemm(self):
-        x = np.random.random(
-            (1, 2, 50)).astype("float32") + 1J * np.random.random(
-                (1, 2, 50)).astype("float32")
-        y = np.random.random(
-            (1, 50, 2)).astype("float32") + 1J * np.random.random(
-                (1, 50, 2)).astype("float32")
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
 
+    def test_complex_xy_gemm_128(self):
         x = np.random.random(
             (1, 2, 50)).astype("float64") + 1J * np.random.random(
                 (1, 2, 50)).astype("float64")
         y = np.random.random(
             (1, 50, 2)).astype("float64") + 1J * np.random.random(
                 (1, 50, 2)).astype("float64")
-        self.compare_1(x, y)
-        self.compare_op_1(x, y)
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
+
+
+class TestComplexMatMulLayerGEMM(unittest.TestCase):
+    def setUp(self):
+        self._places = [fluid.CPUPlace()]
+        if fluid.core.is_compiled_with_cuda():
+            self._places.append(fluid.CUDAPlace(0))
+
+    def compare_by_basic_api(self, x, y):
+        np_result = np.matmul(x, y)
+        for place in self._places:
+            with dg.guard(place):
+                x_var = fluid.core.VarBase(
+                    value=x,
+                    place=place,
+                    persistable=False,
+                    zero_copy=None,
+                    name='')
+                y_var = fluid.core.VarBase(
+                    value=y,
+                    place=place,
+                    persistable=False,
+                    zero_copy=None,
+                    name='')
+                result = paddle.matmul(x_var, y_var)
+                self.assertTrue(np.allclose(result.numpy(), np_result))
+
+    def compare_op_by_basic_api(self, x, y):
+        np_result = np.matmul(x, y)
+        for place in self._places:
+            with dg.guard(place):
+                x_var = fluid.core.VarBase(
+                    value=x,
+                    place=place,
+                    persistable=False,
+                    zero_copy=None,
+                    name='')
+                y_var = fluid.core.VarBase(
+                    value=y,
+                    place=place,
+                    persistable=False,
+                    zero_copy=None,
+                    name='')
+                result = x_var.matmul(y_var)
+                self.assertTrue(np.allclose(result.numpy(), np_result))
+
+    def test_complex_xy_gemm_64(self):
+        x = np.random.random(
+            (1, 2, 50)).astype("float32") + 1J * np.random.random(
+                (1, 2, 50)).astype("float32")
+        y = np.random.random(
+            (1, 50, 2)).astype("float32") + 1J * np.random.random(
+                (1, 50, 2)).astype("float32")
+        self.compare_by_basic_api(x, y)
+        self.compare_op_by_basic_api(x, y)
 
 
 if __name__ == '__main__':