From 6a901a5f8a4155f3a918f3b00d3e4f69c5781345 Mon Sep 17 00:00:00 2001
From: looop5 <xuhui78@huawei.com>
Date: Tue, 1 Nov 2022 11:31:18 +0800
Subject: [PATCH] sync clean code

---
 .../device/cpu/kernel/index_add_cpu_kernel.cc  |  2 +-
 .../sparse_apply_adagrad_da_cpu_kernel.cc      | 18 +-----------------
 .../st/ops/graph_kernel/test_bias_add_grad.py  |  3 +++
 3 files changed, 5 insertions(+), 18 deletions(-)

diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/index_add_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/index_add_cpu_kernel.cc
index 744816dbbca..728d0595cc1 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/index_add_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/index_add_cpu_kernel.cc
@@ -191,7 +191,7 @@ bool IndexAddCpuKernelMod::LaunchKernel(const std::vector<kernel::AddressPtr> &i
   const float block_size = 1024;
   const size_t inner_block_size = 100;
   if (HasDuplicateIndex(indices, y_axis_size_)) {
-    ParallelLaunch(heavy_task_block, outer_size_, CalcSizePerThread(outer_size_), this);
+    ParallelLaunch(heavy_task_block, outer_size_, SizeToFloat(CalcSizePerThread(outer_size_)), this);
   } else if (inner_size_ > 1 && inner_size_ <= inner_block_size) {
     ParallelLaunch(task_block, y_nums_ / inner_size_, block_size / inner_size_, this);
   } else {
diff --git a/mindspore/ccsrc/plugin/device/cpu/kernel/sparse_apply_adagrad_da_cpu_kernel.cc b/mindspore/ccsrc/plugin/device/cpu/kernel/sparse_apply_adagrad_da_cpu_kernel.cc
index f24aad876cf..743104f7885 100644
--- a/mindspore/ccsrc/plugin/device/cpu/kernel/sparse_apply_adagrad_da_cpu_kernel.cc
+++ b/mindspore/ccsrc/plugin/device/cpu/kernel/sparse_apply_adagrad_da_cpu_kernel.cc
@@ -179,7 +179,7 @@ bool SparseApplyAdagradDACpuKernelMod::LaunchKernel(const std::vector<kernel::Ad
       ga[j] = ga[j] + g[k];
       da[j] = da[j] + g[k] * g[k];
       if (l1_scalar > static_cast<T>(0.0)) {
-        var[j] = static_cast<T>(-1.0) * static_cast<T>(Sign(static_cast<double>(ga[j]))) *
+        var[j] = static_cast<T>(-1.0) * static_cast<T>(Sign(static_cast<float>(ga[j]))) *
                  static_cast<T>(std::fmax(
                    static_cast<double>((static_cast<T>(std::fabs(static_cast<double>(ga[j]))) / global_step_scalar) -
                                        l1_scalar),
@@ -209,14 +209,6 @@ const std::vector<std::pair<KernelAttr, KernelRunFunc>> &SparseApplyAdagradDACpu
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, int32_t>},
     {ADD_KERNEL(Int64, Int64, Int64, Int64, Int32, Int64, Int64, Int64, Int64, Int64),
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, int64_t>},
-    {ADD_KERNEL(UInt8, UInt8, UInt8, UInt8, Int32, UInt8, UInt8, UInt8, Int64, UInt8),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, uint8_t>},
-    {ADD_KERNEL(UInt16, UInt16, UInt16, UInt16, Int32, UInt16, UInt16, UInt16, Int64, UInt16),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, uint16_t>},
-    {ADD_KERNEL(UInt32, UInt32, UInt32, UInt32, Int32, UInt32, UInt32, UInt32, Int64, UInt32),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, uint32_t>},
-    {ADD_KERNEL(UInt64, UInt64, UInt64, UInt64, Int32, UInt64, UInt64, UInt64, Int64, UInt64),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, uint64_t>},
     {ADD_KERNEL(Float16, Float16, Float16, Float16, Int32, Float16, Float16, Float16, Int64, Float16),
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int32_t, float16>},
     {ADD_KERNEL(Float32, Float32, Float32, Float32, Int32, Float32, Float32, Float32, Int64, Float32),
@@ -231,14 +223,6 @@ const std::vector<std::pair<KernelAttr, KernelRunFunc>> &SparseApplyAdagradDACpu
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, int32_t>},
     {ADD_KERNEL(Int64, Int64, Int64, Int64, Int64, Int64, Int64, Int64, Int64, Int64),
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, int64_t>},
-    {ADD_KERNEL(UInt8, UInt8, UInt8, UInt8, Int64, UInt8, UInt8, UInt8, Int64, UInt8),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, uint8_t>},
-    {ADD_KERNEL(UInt16, UInt16, UInt16, UInt16, Int64, UInt16, UInt16, UInt16, Int64, UInt16),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, uint16_t>},
-    {ADD_KERNEL(UInt32, UInt32, UInt32, UInt32, Int64, UInt32, UInt32, UInt32, Int64, UInt32),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, uint32_t>},
-    {ADD_KERNEL(UInt64, UInt64, UInt64, UInt64, Int64, UInt64, UInt64, UInt64, Int64, UInt64),
-     &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, uint64_t>},
     {ADD_KERNEL(Float16, Float16, Float16, Float16, Int64, Float16, Float16, Float16, Int64, Float16),
      &SparseApplyAdagradDACpuKernelMod::LaunchKernel<int64_t, float16>},
     {ADD_KERNEL(Float32, Float32, Float32, Float32, Int64, Float32, Float32, Float32, Int64, Float32),
diff --git a/tests/st/ops/graph_kernel/test_bias_add_grad.py b/tests/st/ops/graph_kernel/test_bias_add_grad.py
index f9b65324d65..973a0badfe3 100644
--- a/tests/st/ops/graph_kernel/test_bias_add_grad.py
+++ b/tests/st/ops/graph_kernel/test_bias_add_grad.py
@@ -20,6 +20,7 @@ from mindspore import Tensor
 from mindspore.common.api import jit
 from mindspore.ops.operations import _grad_ops as G
 
+
 class Net(nn.Cell):
     def __init__(self):
         super(Net, self).__init__()
@@ -36,6 +37,7 @@ def get_output(dout, enable_graph_kernel=False):
     output = opt(Tensor(dout))
     return output
 
+
 def test_bias_add_grad(shape, dtype):
     np.random.seed(0)
     dout = np.random.normal(0, 1, shape).astype(dtype)
@@ -50,6 +52,7 @@ def test_bias_add_grad(shape, dtype):
         atol = 1.e-3
     assert np.allclose(expect.asnumpy(), output.asnumpy(), rtol, atol, equal_nan=True)
 
+
 @pytest.mark.level1
 @pytest.mark.platform_arm_ascend_training
 @pytest.mark.platform_x86_ascend_training