!9949 add testcase and minor fix for SparseApplyProximalAdagrad/Ftrl

From: @TFbunny
Reviewed-by: @liangchenghui,@linqingke
Signed-off-by: @liangchenghui

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_apply_proximal_adagrad_kernel.h

@@ -32,15 +32,7 @@ namespace kernel {
 template <typename T>
 class SparseApplyProximalAdagradKernel : public GpuKernel {
  public:
-  SparseApplyProximalAdagradKernel()
-      : variable_size_(0),
-        accumulation_size_(0),
-        learning_rate_size_(0),
-        l1_regularization_size_(0),
-        l2_regularization_size_(0),
-        gradient_size_(0),
-        indices_size_(0) {}
-
+  SparseApplyProximalAdagradKernel() { ResetResource(); }
   ~SparseApplyProximalAdagradKernel() override = default;
 
   const std::vector<size_t> &GetInputSizeList() const override { return input_size_list_; }
@@ -121,6 +113,19 @@ class SparseApplyProximalAdagradKernel : public GpuKernel {
     output_size_list_.push_back(accumulation_size_);
   }
 
+  void ResetResource() noexcept override {
+    variable_size_ = 0;
+    accumulation_size_ = 0;
+    learning_rate_size_ = 0;
+    l1_regularization_size_ = 0;
+    l2_regularization_size_ = 0;
+    gradient_size_ = 0;
+    indices_size_ = 0;
+    input_size_list_.clear();
+    output_size_list_.clear();
+    workspace_size_list_.clear();
+  }
+
  private:
   size_t variable_size_;
   size_t accumulation_size_;

mindspore/ccsrc/backend/kernel_compiler/gpu/nn/sparse_ftrl_gpu_kernel.h

@@ -97,6 +97,18 @@ class SparseFtrlGpuKernel : public GpuKernel {
     return true;
   }
 
+ protected:
+  void InitSizeLists() override {
+    input_size_list_.push_back(variable_size_);
+    input_size_list_.push_back(accumulation_size_);
+    input_size_list_.push_back(linear_size_);
+    input_size_list_.push_back(gradient_size_);
+    input_size_list_.push_back(indices_size_);
+    output_size_list_.push_back(0);
+    output_size_list_.push_back(0);
+    output_size_list_.push_back(0);
+  }
+
   void ResetResource() noexcept override {
     variable_size_ = 0;
     accumulation_size_ = 0;
@@ -115,18 +127,6 @@ class SparseFtrlGpuKernel : public GpuKernel {
     workspace_size_list_.clear();
   }
 
- protected:
-  void InitSizeLists() override {
-    input_size_list_.push_back(variable_size_);
-    input_size_list_.push_back(accumulation_size_);
-    input_size_list_.push_back(linear_size_);
-    input_size_list_.push_back(gradient_size_);
-    input_size_list_.push_back(indices_size_);
-    output_size_list_.push_back(0);
-    output_size_list_.push_back(0);
-    output_size_list_.push_back(0);
-  }
-
  private:
   size_t variable_size_;
   size_t accumulation_size_;

tests/st/ops/gpu/test_sparse_apply_proximal_adagrad_op.py

@@ -62,6 +62,28 @@ def test_small_shape():
     np.testing.assert_array_almost_equal(output1.asnumpy(), expect1)
     np.testing.assert_array_almost_equal(output2.asnumpy(), expect2)
 
+@pytest.mark.level0
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.env_onecard
+def test_small_shape_input_update():
+    var = Tensor(np.arange(9).reshape(3, 3).astype(np.float32))
+    accum = Tensor(np.zeros(9).reshape(3, 3).astype(np.float32))
+    lr = 1.0
+    l1 = 1.0
+    l2 = 0.0
+    grad = Tensor(np.ones(9).reshape(3, 3).astype(np.float32) * 8)
+    indices = Tensor(np.array([1, 0, 2], np.int32))
+    net = Net(var, accum, lr, l1, l2)
+    net(grad, indices)
+    expect1 = np.array([[-0.875, 0., 0.875],
+                        [1.875, 2.875, 3.875],
+                        [4.875, 5.875, 6.875]])
+    expect2 = np.array([[64., 64., 64.],
+                        [64., 64., 64.],
+                        [64., 64., 64.]])
+    np.testing.assert_array_almost_equal(net.var.data.asnumpy(), expect1)
+    np.testing.assert_array_almost_equal(net.accum.data.asnumpy(), expect2)
+
 @pytest.mark.level0
 @pytest.mark.platform_x86_gpu_training
 @pytest.mark.env_onecard