Fix typos eaqul equal(#72858)

co63oc · web-flow · commit 322ed3e94fc4 · 2025-05-22T17:56:45.000+08:00
diff --git a/paddle/phi/kernels/sparse/gpu/addmm_kernel.cu b/paddle/phi/kernels/sparse/gpu/addmm_kernel.cu
@@ -62,33 +62,33 @@ void AddmmKernelImpl(const Context& dev_ctx,
     PADDLE_ENFORCE_EQ(input_dim[i],
                       x_dim[i],
                       common::errors::InvalidArgument(
-                          "input.dim[%d] and x.dim[%d] must be eaqul.", i, i));
+                          "input.dim[%d] and x.dim[%d] must be equal.", i, i));
     PADDLE_ENFORCE_EQ(input_dim[i],
                       y_dim[i],
                       common::errors::InvalidArgument(
-                          "input.dim[%d] and y.dim[%d] must be eaqul.", i, i));
+                          "input.dim[%d] and y.dim[%d] must be equal.", i, i));
   }
 
   PADDLE_ENFORCE_GE(
       input_dim[rank - 2],
       x_dim[rank - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(input) and Input(x) is not suitable for matmul "
-          "opetation, input_dim[-2] must be equal to x_dim[-2]."));
+          "operation, input_dim[-2] must be equal to x_dim[-2]."));
 
   PADDLE_ENFORCE_GE(
       input_dim[rank - 1],
       y_dim[rank - 1],
       common::errors::PreconditionNotMet(
           "The shape of Input(input) and Input(y) is not suitable for matmul "
-          "opetation, input_dim[-1] must be equal to y_dim[-1]."));
+          "operation, input_dim[-1] must be equal to y_dim[-1]."));
 
   PADDLE_ENFORCE_GE(
       x_dim[rank - 1],
       y_dim[rank - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, x_dim[-1] must be equal to y_dim[-2]."));
+          "operation, x_dim[-1] must be equal to y_dim[-2]."));
 
   phi::Copy(dev_ctx, input, dev_ctx.GetPlace(), false, out);
 
diff --git a/paddle/phi/kernels/sparse/gpu/conv_kernel.cu b/paddle/phi/kernels/sparse/gpu/conv_kernel.cu
@@ -326,8 +326,8 @@ void Conv3dCooGPUKernel(const GPUContext& dev_ctx,
  * x: the input SparseCooTensor, shape is (N, D, H, W, C)
  * kernel: the weight data, shape is (D, H, W, C, OC)
  * out: the output SparseCooTensor, shape is (N, D, H, W, OC)
- * rulebook: return rulebook if key is not vailed else return nullptr
- * counter: return counter if key is not vailed else return nullptr
+ * rulebook: return rulebook if key is not valid else return nullptr
+ * counter: return counter if key is not valid else return nullptr
  **/
 template <typename T, typename Context>
 void Conv3dCooKernel(const Context& dev_ctx,
diff --git a/paddle/phi/kernels/sparse/gpu/conv_kernel_igemm.cu b/paddle/phi/kernels/sparse/gpu/conv_kernel_igemm.cu
@@ -170,8 +170,8 @@ void Conv3dImplicitGemmGPUKernel(const GPUContext& dev_ctx,
  * x: the input SparseCooTensor, shape is (N, D, H, W, C)
  * kernel: the weight data, shape is (D, H, W, C, OC)
  * out: the output SparseCooTensor, shape is (N, D, H, W, OC)
- * rulebook: return rulebook if key is not vailed else return nullptr
- * counter: return counter if key is not vailed else return nullptr
+ * rulebook: return rulebook if key is not valid else return nullptr
+ * counter: return counter if key is not valid else return nullptr
  **/
 template <typename T, typename Context>
 void Conv3dImplicitGemmKernel(const Context& dev_ctx,
diff --git a/paddle/phi/kernels/sparse/gpu/convolution.cu.h b/paddle/phi/kernels/sparse/gpu/convolution.cu.h
@@ -376,7 +376,7 @@ int ProductRuleBook(const Context& dev_ctx,
     // At present, the intermediate output index is generated by normal
     // convolution,
     // and then the intermediate output index is subtracted from the input index
-    // to obain the rulebook.
+    // to obtain the rulebook.
 
     // call lower_bound to get the real index of out_index
     const IntT* in_indices_ptr = in_indices.data<IntT>();
diff --git a/paddle/phi/kernels/sparse/gpu/matmul_kernel.cu b/paddle/phi/kernels/sparse/gpu/matmul_kernel.cu
@@ -63,15 +63,15 @@ void MatmulKernelImpl(const Context& dev_ctx,
     PADDLE_ENFORCE_EQ(xdim_vec[i],
                       ydim_vec[i],
                       common::errors::InvalidArgument(
-                          "x.dim[%d] and x.dim[%d] must be eaqul.", i, i));
+                          "x.dim[%d] and x.dim[%d] must be equal.", i, i));
   }
 
   PADDLE_ENFORCE_GE(
       xdim_vec[x_ndims - 1],
       ydim_vec[y_ndims - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, x_dim[-1] must be equal to y_dim[-2]."));
+          "operation, x_dim[-1] must be equal to y_dim[-2]."));
 
   // InferMeta of DenseTensor 'out'
   std::vector<int64_t> out_dim_vec(ydim_vec);
@@ -149,15 +149,15 @@ void MatmulCsrCsrKernel(const Context& dev_ctx,
     PADDLE_ENFORCE_EQ(xdim_vec[i],
                       ydim_vec[i],
                       common::errors::InvalidArgument(
-                          "x.dim[%d] and x.dim[%d] must be eaqul.", i, i));
+                          "x.dim[%d] and x.dim[%d] must be equal.", i, i));
   }
 
   PADDLE_ENFORCE_GE(
       xdim_vec[x_ndims - 1],
       ydim_vec[y_ndims - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, x_dim[-1] must be equal to y_dim[-2]."));
+          "operation, x_dim[-1] must be equal to y_dim[-2]."));
 
   auto sparse_blas = phi::funcs::sparse::GetSparseBlas<Context, T>(dev_ctx);
   sparse_blas.SPGEMM(
@@ -240,21 +240,21 @@ void MaskedMatmulCsrKernel(const Context& dev_ctx,
       ydim_vec[y_ndims - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, x_dim[-1] must be equal to y_dim[-2]."));
+          "operation, x_dim[-1] must be equal to y_dim[-2]."));
 
   PADDLE_ENFORCE_EQ(
       maskdim_vec[mask_ndims - 2],
       xdim_vec[x_ndims - 2],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, mask_dim[-2] must be equal to x_dim[-2]."));
+          "operation, mask_dim[-2] must be equal to x_dim[-2]."));
 
   PADDLE_ENFORCE_EQ(
       maskdim_vec[mask_ndims - 1],
       ydim_vec[y_ndims - 1],
       common::errors::PreconditionNotMet(
           "The shape of Input(x) and Input(y) is not suitable for matmul "
-          "opetation, mask_dim[-1] must be equal to y_dim[-1]."));
+          "operation, mask_dim[-1] must be equal to y_dim[-1]."));
 
   // InferMeta of SparseCsrTensor 'out', CreateLikeInferMeta
   EmptyLikeCsrKernel<T, Context>(dev_ctx, mask, out);
diff --git a/paddle/phi/kernels/sparse/gpu/mv_kernel.cu b/paddle/phi/kernels/sparse/gpu/mv_kernel.cu
@@ -46,7 +46,7 @@ void MvKernelImpl(const Context& dev_ctx,
                     vec_dim[vec_ndims - 1],
                     common::errors::PreconditionNotMet(
                         "The shape of Input(x) and Input(vec) is not "
-                        "suitable for mv opetation, "
+                        "suitable for mv operation, "
                         "x_dim[-1] must be equal to vec_dim[-1]."));
   std::vector<int64_t> out_dim = {x_dim[x_ndims - 2]};
   out->Resize(common::make_ddim(out_dim));
diff --git a/paddle/phi/kernels/sparse/gpu/slice_grad_kernel.cu b/paddle/phi/kernels/sparse/gpu/slice_grad_kernel.cu
@@ -223,9 +223,9 @@ void SliceCsrGrad2D(const Context& dev_ctx,
                                                    0);
 }
 
-__global__ void GetCsrInputCrowsPart1CudaKernl(const int64_t n_rows,
-                                               const int64_t dim0_idx,
-                                               int64_t* dx_crows_data) {
+__global__ void GetCsrInputCrowsPart1CudaKernel(const int64_t n_rows,
+                                                const int64_t dim0_idx,
+                                                int64_t* dx_crows_data) {
   CUDA_KERNEL_LOOP_TYPE(j, n_rows + 1, int64_t) {
     dx_crows_data[dim0_idx * (n_rows + 1) + j] = 0;
   }
@@ -270,10 +270,10 @@ void SliceCsrGrad3D(const Context& dev_ctx,
   for (int64_t i = 0; i < dim0; ++i) {
     if (i < starts[0] || i >= ends[0]) {
       config = phi::backends::gpu::GetGpuLaunchConfig1D(dev_ctx, n_rows + 1, 1);
-      GetCsrInputCrowsPart1CudaKernl<<<config.block_per_grid.x,
-                                       config.thread_per_block.x,
-                                       0,
-                                       dev_ctx.stream()>>>(
+      GetCsrInputCrowsPart1CudaKernel<<<config.block_per_grid.x,
+                                        config.thread_per_block.x,
+                                        0,
+                                        dev_ctx.stream()>>>(
           n_rows, i, dx_crows_data);
     } else {
       int64_t dx_crows_offset = i * (n_rows + 1);
diff --git a/paddle/phi/kernels/stride/strided_slice_kernel.cc b/paddle/phi/kernels/stride/strided_slice_kernel.cc
@@ -99,7 +99,7 @@ void StridedSliceRawStridedKernel(const Context& dev_ctx,
   auto tmp_dim = DDim(output_dims.data(), static_cast<int>(output_dims.size()));
   // if (product(meta.dims) > 0 && meta.dims != tmp_dim) {
   //   PADDLE_THROW(
-  //       common::errors::Fatal("Striede_slice kernel stride compute diff,
+  //       common::errors::Fatal("strided_slice kernel stride compute diff,
   //       infer "
   //                          "shape is %s, but compute is %s.",
   //                          meta.dims,
