Fix DECALRE DECLARE

paddle/phi/kernels/compare_kernel.h

@@ -18,29 +18,29 @@ limitations under the License. */
 
 namespace phi {
 
-#define DECALRE_COMPARE_KERNEL(name)      \
+#define DECLARE_COMPARE_KERNEL(name)      \
   template <typename T, typename Context> \
   void name##Kernel(const Context& ctx,   \
                     const DenseTensor& x, \
                     const DenseTensor& y, \
                     DenseTensor* out);
 
-DECALRE_COMPARE_KERNEL(LessThan)
-DECALRE_COMPARE_KERNEL(LessEqual)
-DECALRE_COMPARE_KERNEL(GreaterThan)
-DECALRE_COMPARE_KERNEL(GreaterEqual)
-DECALRE_COMPARE_KERNEL(Equal)
-DECALRE_COMPARE_KERNEL(NotEqual)
-#undef DECALRE_COMPARE_KERNEL
+DECLARE_COMPARE_KERNEL(LessThan)
+DECLARE_COMPARE_KERNEL(LessEqual)
+DECLARE_COMPARE_KERNEL(GreaterThan)
+DECLARE_COMPARE_KERNEL(GreaterEqual)
+DECLARE_COMPARE_KERNEL(Equal)
+DECLARE_COMPARE_KERNEL(NotEqual)
+#undef DECLARE_COMPARE_KERNEL
 
-#define DECALRE_COMPARE_ALL_KERNEL(compare_all)  \
+#define DECLARE_COMPARE_ALL_KERNEL(compare_all)  \
   template <typename T, typename Context>        \
   void compare_all##Kernel(const Context& ctx,   \
                            const DenseTensor& x, \
                            const DenseTensor& y, \
                            DenseTensor* out);
 
-DECALRE_COMPARE_ALL_KERNEL(EqualAll)
-#undef DECALRE_COMPARE_KERNEL
+DECLARE_COMPARE_ALL_KERNEL(EqualAll)
+#undef DECLARE_COMPARE_KERNEL
 
 }  // namespace phi

paddle/phi/kernels/impl/slogdeterminant_grad_kernel_impl.h

@@ -98,7 +98,7 @@ void SlogDeterminantGradKernel(const Context& dev_ctx,
   auto grad_vec = out_grad.Split(1, 0);
   auto det_grad = grad_vec[1];
 
-  // remmove useless first dimension
+  // remove useless first dimension
   int det_grad_size = det_grad.dims().size();
   std::vector<int> det_grad_vec;
   for (int i = 1; i < det_grad_size; ++i) {

paddle/phi/kernels/impl/solve_grad_kernel_impl.h

@@ -34,7 +34,7 @@ limitations under the License. */
 namespace phi {
 
 template <typename Context, typename T>
-struct ReduceSumForSolvelGrad {
+struct ReduceSumForSolveGrad {
   void operator()(const Context& dev_ctx,
                   const DenseTensor& input,
                   DenseTensor* output,
@@ -43,7 +43,7 @@ struct ReduceSumForSolvelGrad {
 };
 
 template <typename T>
-struct ReduceSumForSolvelGrad<CPUContext, T> {
+struct ReduceSumForSolveGrad<CPUContext, T> {
   void operator()(const CPUContext& dev_ctx,
                   const DenseTensor& input,
                   DenseTensor* output,
@@ -58,7 +58,7 @@ struct ReduceSumForSolvelGrad<CPUContext, T> {
 
 #if defined(__NVCC__) || defined(__HIPCC__)
 template <typename T>
-struct ReduceSumForSolvelGrad<GPUContext, T> {
+struct ReduceSumForSolveGrad<GPUContext, T> {
   void operator()(const GPUContext& dev_ctx,
                   const DenseTensor& input,
                   DenseTensor* output,
@@ -210,7 +210,7 @@ void SolveGradKernel(const Context& dev_ctx,
         if (dy_help.dims().size() != dy->dims().size()) {
           keep_dim = false;
         }
-        ReduceSumForSolvelGrad<Context, T>()(
+        ReduceSumForSolveGrad<Context, T>()(
             dev_ctx, dy_help, dy, dy_reduce_dims, keep_dim);
       }
       dy->Resize(y.dims());
@@ -257,7 +257,7 @@ void SolveGradKernel(const Context& dev_ctx,
         if (dx_help.dims().size() != dx->dims().size()) {
           keep_dim = false;
         }
-        ReduceSumForSolvelGrad<Context, T>()(
+        ReduceSumForSolveGrad<Context, T>()(
             dev_ctx, dx_help, dx, dx_reduce_dims, keep_dim);
       }
       dx->Resize(x.dims());

paddle/phi/kernels/impl/triangular_solve_grad_kernel_impl.h

@@ -55,7 +55,7 @@ void TriangularSolveGradKernel(const Context& dev_ctx,
         x.data<T>(), x.numel(), dev_ctx.template Alloc<T>(&x_conj));
     x_for_range(x_functor);
 
-    // reuse forward to get dy_bst, and the result has been broadcated already.
+    // reuse forward to get dy_bst, and the result has been broadcasted already.
     TriangularSolveKernel<T, Context>(
         dev_ctx, x_conj, dout, upper, !transpose, unitriangular, &dy_bst);
 

paddle/phi/kernels/impl/warprnnt_kernel_impl.h

@@ -115,7 +115,7 @@ class WarpRNNTFunctor {
    * \param D                 number of vocab symbols, w/ blank.
    * \param B                 number of example.
    * \param blank             blank label used in rnnt loss function.
-   * \param cpu_losss         loss of each example in CPU memory.
+   * \param cpu_loss         loss of each example in CPU memory.
    */
   void operator()(const Context& dev_ctx,
                   const T* input,

paddle/phi/kernels/onednn/conv_grad_kernel.cc

@@ -96,7 +96,7 @@ void ConvGradKernel(const Context& dev_ctx,
               handler.AcquireDiffDstMemoryWithReorderFromWeightsPrimitive(
                   &out_grad);
 
-          // For convoluition with groups write filter grad into
+          // For convolution with groups write filter grad into
           // oneDNN buffer and then we reorder it into filter_grad tensor
           int g = std::max(groups, 1);
           auto diff_weights_memory_p =

paddle/phi/kernels/primitive/functor_primitives_xpu2.h

@@ -184,7 +184,7 @@ struct DivFunctor<T,
   inline T initial() { return static_cast<T>(1.0f); }
 
   inline HOSTDEVICE T operator()(const T& a, const T& b) const {
-    // For int32/int64, need to check whether the divison is zero.
+    // For int32/int64, need to check whether the division is zero.
     PADDLE_ENFORCE_NE(b,
                       0,
                       phi::errors::InvalidArgument(

paddle/phi/kernels/sparse/cpu/conv_kernel.cc

@@ -137,7 +137,7 @@ void Conv3dCooCPUKernel(const CPUContext& dev_ctx,
   Gather<T, IntT>(
       x.values().data<T>(), rulebook_ptr + n, n, in_channels, in_features_ptr);
 
-  // 3. call gemm for every werght
+  // 3. call gemm for every weight
   auto blas = phi::funcs::GetBlas<CPUContext, T>(dev_ctx);
   int offset = 0;
   for (int i = 0; i < kernel_size; i++) {

paddle/phi/kernels/sparse/cpu/softmax_kernel.cc

@@ -160,7 +160,7 @@ void SoftmaxCooCPUKernel(const Context& dev_ctx,
   }
 }
 
-// cpu kerenel
+// cpu kernel
 template <typename T, typename Context>
 void SoftmaxCooKernel(const Context& dev_ctx,
                       const SparseCooTensor& x,

paddle/phi/kernels/stride/slice_kernel.cc

@@ -75,7 +75,7 @@ void SliceStridedKernel(const Context& ctx,
       }
     }
     if (FLAGS_set_to_1d && new_shape.size() == 0) {
-      // NOTE(zoooo0820): Hack procssing to 1-D, when axes decrease to 0-D in
+      // NOTE(zoooo0820): Hack processing to 1-D, when axes decrease to 0-D in
       // slice. This will remove in release 2.6.
       new_shape.push_back(1);
       new_stride.push_back(0);