Fix @param doc comments.

examples/models/llama2/custom_ops/op_sdpa.cpp

@@ -702,21 +702,21 @@ Tensor& flash_attention_kernel_out(
 
 /*
   Input params
-  @params[in]: q_projected: Projected query with query weights.
+  @param[in] q_projected Projected query with query weights.
   Format [n_layers, batch size, seq_len, num heads, head dim]
-  @params[in]: k_projected: Projected query with key weights.
+  @param[in] k_projected Projected query with key weights.
   Format [n_layers, batch size, seq_len, num heads, head dim]
-  @params[in]: v_projected: Projected query with value weights.
+  @param[in] v_projected Projected query with value weights.
   Format [n_layers, batch size, seq_len, num heads, head dim]
-  @params[in]: key_cache: Cache of previous k_projected.
+  @param[in] key_cache Cache of previous k_projected.
   Format [n_layers, batch size, max_seq_len, num heads, head dim]
-  @params[in]: key_cache: Cache of previous v_projected.
+  @param[in] key_cache Cache of previous v_projected.
   Format [n_layers, batch size, max_seq_len, num heads, head dim]
   ....
-  @params[in] layer_id: which layer this call belongs to.
+  @param[in] layer_id which layer this call belongs to.
   Used to updated appropriate entry of kv cache
-  @params[in]: start_pos: sequence position
-  @params[in]: seq_len: Seq length. e.g. seq_len dim of q_projected.
+  @param[in] start_pos sequence position
+  @param[in] seq_len Seq length. e.g. seq_len dim of q_projected.
 */
 Tensor& sdpa_with_kv_cache_out(
     RuntimeContext& ctx,

extension/aten_util/aten_bridge.cpp

@@ -124,8 +124,8 @@ c10::ScalarType execuTorchtoTorchScalarType(torch::executor::ScalarType type) {
  * assumption , a strong one, that, such memory is arena allocated whose
  * lifetime is tied to model's lifetime, we assume that memory is not leaked as
  * it is freed when arean is freed.
- * @param[in] aten_tensor: Input at::Tensor
- * @param[in/out] mutable_et: ETensor whose underlying memory now will alias to
+ * @param[in] aten_tensor Input at::Tensor
+ * @param[in/out] mutable_et ETensor whose underlying memory now will alias to
  * aten_tensor
  */
 void alias_etensor_to_attensor(

extension/aten_util/aten_bridge.h

@@ -26,16 +26,16 @@ torch::executor::ScalarType torchToExecuTorchScalarType(caffe2::TypeMeta type);
 c10::ScalarType execuTorchtoTorchScalarType(torch::executor::ScalarType type);
 
 /*
- * @param[in] aten_tensor: Input at::Tensor
- * @param[in/out] mutable_et: ETensor whose underlying memory now will alias to
+ * @param[in] aten_tensor Input at::Tensor
+ * @param[in,out] mutable_et ETensor whose underlying memory now will alias to
  * aten_tensor
  */
 void alias_etensor_to_attensor(at::Tensor& at, torch::executor::Tensor& et);
 
 /*
- * @param[in] et: ETensor whose underlying memory now will alias to returned
+ * @param[in] et ETensor whose underlying memory now will alias to returned
  * output tensor
- * @param[ret] aten_tensor: output at::Tensor
+ * @param[ret] aten_tensor output at::Tensor
  * Notes:
  * It is owned by the caller of alias_attensor_to_etensor.
  * Lifetime of tensor meta must be >= to that of the returned tensor since

kernels/portable/cpu/util/transpose_util.h

@@ -38,19 +38,19 @@ namespace {
  * Increments an N dimensional index like x[0,0,0] to x[0, 0, 1] to x[0, 0, 2]
  * to x[0, 1, 0] to x[0, 1, 1] etc...
  *
- * @param index: An array of the same size as sizes. This stores the "counter"
+ * @param index An array of the same size as sizes. This stores the "counter"
  * being incremented.
  *
- * @param new_sizes: The output tensor dimensions. Allows us to compute the
+ * @param new_sizes The output tensor dimensions. Allows us to compute the
  * offset into the input tensor.
  *
- * @param non_one_indices: A list of indices into index that contain non-1
+ * @param non_one_indices A list of indices into index that contain non-1
  * dimension values. This allows us to eliminate an O(dim) factor from the
  * runtime in case many dimensions have a value of 1.
  *
- * @param new_strides: Strides corresponding to new_sizes.
+ * @param new_strides Strides corresponding to new_sizes.
  *
- * @param offset: The computed offset to index into the input tensor's memory
+ * @param offset The computed offset to index into the input tensor's memory
  * array.
  */
 inline void increment_index_and_offset(

runtime/core/portable_type/tensor_impl.h

@@ -86,16 +86,16 @@ class TensorImpl {
   TensorImpl() = delete;
 
   /**
-   * @param type: The type of the data (int, float, bool).
-   * @param dim: Number of dimensions, and the length of the `sizes` array.
-   * @param sizes: Sizes of the tensor at each dimension. Must contain `dim`
+   * @param type The type of the data (int, float, bool).
+   * @param dim Number of dimensions, and the length of the `sizes` array.
+   * @param sizes Sizes of the tensor at each dimension. Must contain `dim`
    *     entries.
-   * @param data: Pointer to the data, whose size is determined by `type`,
+   * @param data Pointer to the data, whose size is determined by `type`,
    *     `dim`, and `sizes`. The tensor will not own this memory.
-   * @param dim_order: Order in which dimensions are laid out in memory.
-   * @param strides: Strides of the tensor at each dimension. Must contain `dim`
+   * @param dim_order Order in which dimensions are laid out in memory.
+   * @param strides Strides of the tensor at each dimension. Must contain `dim`
    *     entries.
-   * @param dynamism: The mutability of the shape of the tensor.
+   * @param dynamism The mutability of the shape of the tensor.
    */
   TensorImpl(
       ScalarType type,