[0-size Tensor No.110] Add 0-size Tensor support for paddle.linalg.matrix_power API.

paddle/phi/kernels/impl/matrix_power_grad_kernel_impl.h

@@ -193,6 +193,10 @@ void MatrixPowerGradKernel(const Context& ctx,
   auto Out = &out;
   auto dOut = &out_grad;
   auto dX = x_grad;
+  if (x_grad && x_grad->numel() == 0) {
+    ctx.template Alloc<T>(x_grad);
+    return;
+  }
 
   MatrixPowerGradFunction<Context, T>(X, Out, dOut, n, dX, ctx);
 }

test/legacy_test/test_matrix_power_op.py

@@ -216,6 +216,69 @@ def config(self):
         self.n = 32
 
 
+class TestMatrixPowerOpZeroSize(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [0, 0]
+        self.dtype = "float32"
+        self.n = 32
+
+
+class TestMatrixPowerOpZeroSize1(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [0, 0]
+        self.dtype = "float32"
+        self.n = 0
+
+
+class TestMatrixPowerOpZeroSize2(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [0, 0]
+        self.dtype = "float32"
+        self.n = -1
+
+
+class TestMatrixPowerOpBatchedZeroSize1(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 0, 4, 4]
+        self.dtype = "float32"
+        self.n = 4
+
+
+class TestMatrixPowerOpBatchedZeroSize2(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 0, 4, 4]
+        self.dtype = "float32"
+        self.n = 0
+
+
+class TestMatrixPowerOpBatchedZeroSize3(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 0, 4, 4]
+        self.dtype = "float32"
+        self.n = -1
+
+
+class TestMatrixPowerOpBatchedZeroSize4(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 6, 0, 0]
+        self.dtype = "float32"
+        self.n = 1
+
+
+class TestMatrixPowerOpBatchedZeroSize5(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 6, 0, 0]
+        self.dtype = "float32"
+        self.n = 0
+
+
+class TestMatrixPowerOpBatchedZeroSize6(TestMatrixPowerOp):
+    def config(self):
+        self.matrix_shape = [2, 6, 0, 0]
+        self.dtype = "float32"
+        self.n = -1
+
+
 @unittest.skipIf(
     core.is_compiled_with_xpu(),
     "Skip complex due to lack of mean support",
@@ -563,7 +626,7 @@ def _test_matrix_power_empty_static(self, place):
                 self.assertEqual(res[0].shape, (0, 0))
                 self.assertEqual(res[1].shape, (2, 3, 0, 0))
 
-    def _test_matrix_power_empty_dynamtic(self):
+    def _test_matrix_power_empty_dynamic(self):
         with dygraph_guard():
             x2 = paddle.full((0, 6), 1.0, dtype='float32')
             x3 = paddle.full((6, 0), 1.0, dtype='float32')
@@ -581,7 +644,7 @@ def _test_matrix_power_empty_dynamtic(self):
     def test_matrix_power_empty_tensor(self):
         for place in self._get_places():
             self._test_matrix_power_empty_static(place)
-        self._test_matrix_power_empty_dynamtic()
+        self._test_matrix_power_empty_dynamic()
 
 
 if __name__ == "__main__":