diff --git a/paddle/phi/kernels/sparse/cpu/matmul_kernel.cc b/paddle/phi/kernels/sparse/cpu/matmul_kernel.cc
index 10ad848442c9d..0818b8e900a05 100644
--- a/paddle/phi/kernels/sparse/cpu/matmul_kernel.cc
+++ b/paddle/phi/kernels/sparse/cpu/matmul_kernel.cc
@@ -27,7 +27,7 @@ void CsrDenseMatmulKernel(const Context& dev_ctx,
                           const DenseTensor& y,
                           DenseTensor* out) {
   PADDLE_THROW(phi::errors::Unimplemented(
-      "Not support CPU kernel of Sparse Matmul now."));
+      "Not support CPU kernel of 'sparse.matmul' now."));
 }
 
 // TODO(zhouwei25): implement CPU kernel of " DENSE @ DENSE * CSR_MASK -> CSR"
@@ -38,7 +38,7 @@ void CsrMaskedMatmulKernel(const Context& dev_ctx,
                            const SparseCsrTensor& mask,
                            SparseCsrTensor* out) {
   PADDLE_THROW(phi::errors::Unimplemented(
-      "Not support CPU kernel of Matmul Mask As Sparse now."));
+      "Not support CPU kernel of 'sparse.masked_matmul' now."));
 }
 
 }  // namespace sparse
diff --git a/python/paddle/fluid/tests/unittests/test_sparse_mv_op.py b/python/paddle/fluid/tests/unittests/test_sparse_mv_op.py
index 3b5bf166b9544..9ac4fff85006f 100644
--- a/python/paddle/fluid/tests/unittests/test_sparse_mv_op.py
+++ b/python/paddle/fluid/tests/unittests/test_sparse_mv_op.py
@@ -22,6 +22,8 @@
 import os
 import re
 
+paddle.seed(100)
+
 
 def get_cuda_version():
     result = os.popen("nvcc --version").read()
@@ -42,6 +44,7 @@ class TestCsrMv(unittest.TestCase):
     # x: csr-matrix, y: dense-vec, out: dense-vec
     def test_mv(self):
         with _test_eager_guard():
+            paddle.set_default_dtype('float64')
             origin_x = paddle.rand([64, 32])
             mask = paddle.randint(0, 2, [64, 32])
             origin_x = origin_x * mask
@@ -76,6 +79,7 @@ class TestCooMv(unittest.TestCase):
     # x: csr-matrix, y: dense-vec, out: dense-vec
     def test_mv(self):
         with _test_eager_guard():
+            paddle.set_default_dtype('float64')
             origin_x = paddle.rand([64, 32])
             mask = paddle.randint(0, 2, [64, 32])
             origin_x = origin_x * mask