diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sparse_ftrl_impl.cu b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sparse_ftrl_impl.cu
index a0407d0e67..37d5c226fc 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sparse_ftrl_impl.cu
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/sparse_ftrl_impl.cu
@@ -96,8 +96,19 @@ template void CalSparseApplyFtrl<float, int>(const float *gradient, const int *i
                                              const float l1_regularization, const float l2_regularization,
                                              const float learning_rate_power, const bool use_locking, float *variable,
                                              float *accumulation, float *linear, cudaStream_t cuda_stream);
+template void CalSparseApplyFtrl<float, int64_t>(const float *gradient, const int64_t *indices, const int num_index,
+                                             const size_t n_stride, const float learning_rate,
+                                             const float l1_regularization, const float l2_regularization,
+                                             const float learning_rate_power, const bool use_locking, float *variable,
+                                             float *accumulation, float *linear, cudaStream_t cuda_stream);
 template void CalSparseApplyFtrl<half, int>(const half *gradient, const int *indices, const int num_index,
                                             const size_t n_stride, const float learning_rate,
                                             const float l1_regularization, const float l2_regularization,
                                             const float learning_rate_power, const bool use_locking, half *variable,
                                             half *accumulation, half *linear, cudaStream_t cuda_stream);
+template void CalSparseApplyFtrl<half, int64_t>(const half *gradient, const int64_t *indices, const int num_index,
+                                            const size_t n_stride, const float learning_rate,
+                                            const float l1_regularization, const float l2_regularization,
+                                            const float learning_rate_power, const bool use_locking, half *variable,
+                                            half *accumulation, half *linear, cudaStream_t cuda_stream);
+
diff --git a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_ftrl_gpu_kernel.cc b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_ftrl_gpu_kernel.cc
index 2ee596a4f0..971e93783f 100644
--- a/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_ftrl_gpu_kernel.cc
+++ b/mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_ftrl_gpu_kernel.cc
@@ -29,6 +29,17 @@ MS_REG_GPU_KERNEL_TWO(SparseApplyFtrl,
                         .AddOutputAttr(kNumberTypeFloat32)
                         .AddOutputAttr(kNumberTypeFloat32),
                       SparseFtrlGpuKernel, float, int)
+MS_REG_GPU_KERNEL_TWO(SparseApplyFtrl,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeFloat32)
+                        .AddInputAttr(kNumberTypeInt64)
+                        .AddOutputAttr(kNumberTypeFloat32)
+                        .AddOutputAttr(kNumberTypeFloat32)
+                        .AddOutputAttr(kNumberTypeFloat32),
+                      SparseFtrlGpuKernel, float, int64_t)
 MS_REG_GPU_KERNEL_TWO(SparseApplyFtrl,
                       KernelAttr()
                         .AddInputAttr(kNumberTypeFloat16)
@@ -40,5 +51,16 @@ MS_REG_GPU_KERNEL_TWO(SparseApplyFtrl,
                         .AddOutputAttr(kNumberTypeFloat16)
                         .AddOutputAttr(kNumberTypeFloat16),
                       SparseFtrlGpuKernel, half, int)
+MS_REG_GPU_KERNEL_TWO(SparseApplyFtrl,
+                      KernelAttr()
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeFloat16)
+                        .AddInputAttr(kNumberTypeInt64)
+                        .AddOutputAttr(kNumberTypeFloat16)
+                        .AddOutputAttr(kNumberTypeFloat16)
+                        .AddOutputAttr(kNumberTypeFloat16),
+                      SparseFtrlGpuKernel, half, int64_t)
 }  // namespace kernel
 }  // namespace mindspore
diff --git a/tests/st/ops/gpu/test_sparse_apply_ftrl_op.py b/tests/st/ops/gpu/test_sparse_apply_ftrl_op.py
index 9519bac4d0..09789236c9 100644
--- a/tests/st/ops/gpu/test_sparse_apply_ftrl_op.py
+++ b/tests/st/ops/gpu/test_sparse_apply_ftrl_op.py
@@ -77,9 +77,9 @@ def test_ftrl():
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
-def test_ftrl_sparse():
+def test_ftrl_sparse_int64_ind():
     gradient = Tensor(np.ones([2, 3, 3]).astype(np.float32))
-    indices = Tensor([0, 2], mstype.int32)
+    indices = Tensor([0, 2], mstype.int64)
     expect_var = np.array([[[0.291479, 0.291479, 0.291479],
                             [0.291479, 0.291479, 0.291479],
                             [0.291479, 0.291479, 0.291479]],
@@ -127,9 +127,9 @@ def test_ftrl_half():
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard
-def test_ftrl_sparse_half():
+def test_ftrl_sparse_half_int64_ind():
     gradient = Tensor(np.ones([2, 3, 3]).astype(np.float16))
-    indices = Tensor([0, 2], mstype.int32)
+    indices = Tensor([0, 2], mstype.int64)
     expect_var = np.array([[[0.291479, 0.291479, 0.291479],
                             [0.291479, 0.291479, 0.291479],
                             [0.291479, 0.291479, 0.291479]],