[REVIEW] Make documentation uniform for stream and memory resource params

cpp/include/cudf/binaryop.hpp

@@ -89,7 +89,7 @@ enum class binary_operator : int32_t {
  * @param lhs         The left operand scalar
  * @param rhs         The right operand column
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @return std::unique_ptr<column> Output column
  * @throw cudf::logic_error if @p lhs and @p rhs dtypes aren't numeric
  * @throw cudf::logic_error if @p output_type dtype isn't numeric
@@ -114,7 +114,7 @@ std::unique_ptr<column> binary_operation(
  * @param lhs         The left operand column
  * @param rhs         The right operand scalar
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @return std::unique_ptr<column> Output column
  * @throw cudf::logic_error if @p lhs and @p rhs dtypes aren't numeric
  * @throw cudf::logic_error if @p output_type dtype isn't numeric
@@ -138,7 +138,7 @@ std::unique_ptr<column> binary_operation(
  * @param lhs         The left operand column
  * @param rhs         The right operand column
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @return std::unique_ptr<column> Output column
  * @throw cudf::logic_error if @p lhs and @p rhs are different sizes
  * @throw cudf::logic_error if @p lhs and @p rhs dtypes aren't fixed-width
@@ -167,7 +167,7 @@ std::unique_ptr<column> binary_operation(
  * @param output_type The desired data type of the output column. It is assumed
  *                    that output_type is compatible with the output data type
  *                    of the function in the PTX code
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @return std::unique_ptr<column> Output column
  * @throw cudf::logic_error if @p lhs and @p rhs are different sizes
  * @throw cudf::logic_error if @p lhs and @p rhs dtypes aren't numeric

cpp/include/cudf/column/column.hpp

@@ -59,7 +59,7 @@ class column {
    *
    * @param other The `column` to copy
    * @param stream The stream on which to execute all allocations and copies
-   * @param mr The resource to use for all allocations
+   * @param mr Device memory resource to use for all allocations
    */
   column(column const& other,
          cudaStream_t stream,
@@ -115,7 +115,7 @@ class column {
    * @param view The view to copy
    * @param stream The stream on which all allocations and copies will be
    * executed
-   * @param mr The resource to use for all allocations
+   * @param mr Device memory resource to use for all allocations
    */
   explicit column(column_view view,
                   cudaStream_t stream                 = 0,

cpp/include/cudf/column/column_factories.hpp

@@ -241,8 +241,7 @@ std::unique_ptr<column> make_fixed_width_column(
  * (indicating a null string). The size must be the number of bytes.
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory
- *           allocation of the column's `null_mask` and children.
+ * @param mr Device memory resource used for allocation of the column's `null_mask` and children.
  */
 std::unique_ptr<column> make_strings_column(
   const rmm::device_vector<thrust::pair<const char*, size_type>>& strings,
@@ -273,8 +272,7 @@ std::unique_ptr<column> make_strings_column(
  * string_views.
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory
- *           allocation of the column's `null_mask` and children.
+ * @param mr Device memory resource used for allocation of the column's `null_mask` and children.
  */
 std::unique_ptr<column> make_strings_column(
   const rmm::device_vector<string_view>& string_views,
@@ -312,8 +310,7 @@ std::unique_ptr<column> make_strings_column(
  * first invocation of `column::null_count()`
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory
- *           allocation of the column's `null_mask` and children.
+ * @param mr Device memory resource used for allocation of the column's `null_mask` and children.
  */
 std::unique_ptr<column> make_strings_column(
   const rmm::device_vector<char>& strings,
@@ -353,8 +350,7 @@ std::unique_ptr<column> make_strings_column(
  * first invocation of `column::null_count()`
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory
- *           allocation of the column's `null_mask` and children.
+ * @param mr Device memory resource used for allocation of the column's `null_mask` and children.
  */
 std::unique_ptr<column> make_strings_column(
   const std::vector<char>& strings,
@@ -382,8 +378,7 @@ std::unique_ptr<column> make_strings_column(
  *                  Arrow format for nulls is used for interpeting this bitmask.
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory
- *           allocation of the column's `null_mask` and children.
+ * @param mr Device memory resource used for allocation of the column's `null_mask` and children.
  */
 std::unique_ptr<column> make_strings_column(
   size_type num_strings,
@@ -406,7 +401,7 @@ std::unique_ptr<column> make_strings_column(
  * @param size The number of rows for the output column.
  * @param stream Optional stream for use with all memory allocation
  *               and device kernels
- * @param mr Optional resource to use for device memory.
+ * @param mr Device memory resource used to allocate the returned column.
  */
 std::unique_ptr<column> make_column_from_scalar(
   scalar const& s,

cpp/include/cudf/concatenate.hpp

@@ -35,8 +35,7 @@ namespace cudf {
  * Returns empty `device_buffer` if the column is not nullable
  *
  * @param views Vector of column views whose bitmask will to be concatenated
- * @param mr Optional, the memory resource that will be used for allocating
- * the device memory for the new device_buffer
+ * @param mr Device memory resource used for allocating the new device_buffer
  * @return rmm::device_buffer A `device_buffer` containing the bitmasks of all
  * the column views in the views vector
  */
@@ -52,7 +51,7 @@ rmm::device_buffer concatenate_masks(
  *
  * @param columns_to_concat The column views to be concatenated into a single
  * column
- * @param mr Optional The resource to use for all allocations
+ * @param mr Device memory resource used to allocate the returned column.
  * @return Unique pointer to a single table having all the rows from the
  * elements of `columns_to_concat` respectively in the same order.
  */
@@ -83,7 +82,7 @@ std::unique_ptr<column> concatenate(
  *
  * @param tables_to_concat The table views to be concatenated into a single
  * table
- * @param mr Optional The resource to use for all allocations
+ * @param mr Device memory resource used to allocate the returned table.
  * @return Unique pointer to a single table having all the rows from the
  * elements of `tables_to_concat` respectively in the same order.
  **/

cpp/include/cudf/copying.hpp

@@ -100,7 +100,7 @@ std::unique_ptr<table> gather(
  * are to be scattered
  * @param check_bounds Optionally perform bounds checking on the values of
  * `scatter_map` and throw an error if any of its values are out of bounds.
- * @param mr The resource to use for all allocations
+ * @param mr Device memory resource used to allocate the returned table.
  * @return Result of scattering values from source to target
  */
 std::unique_ptr<table> scatter(
@@ -140,7 +140,7 @@ std::unique_ptr<table> scatter(
  * are to be scattered
  * @param check_bounds Optionally perform bounds checking on the values of
  * `scatter_map` and throw an error if any of its values are out of bounds.
- * @param mr The resource to use for all allocations
+ * @param mr Device memory resource used to allocate the returned table.
  * @return Result of scattering values from source to target
  */
 std::unique_ptr<table> scatter(
@@ -273,7 +273,7 @@ void copy_range_in_place(column_view const& source,
  * @param source_end The index of the last element in the source range
  * (exclusive)
  * @param target_begin The starting index of the target range (inclusive)
- * @param mr Memory resource to allocate the result target column.
+ * @param mr Device memory resource used to allocate the returned column.
  * @return std::unique_ptr<column> The result target column
  */
 std::unique_ptr<column> copy_range(
@@ -709,7 +709,7 @@ std::unique_ptr<table> boolean_mask_scatter(
  *
  * @param input Column view to get the element from
  * @param index Index into `input` to get the element at
- * @param mr Optional, The resource to use for all returned allocations
+ * @param mr Device memory resource used to allocate the returned scalar.
  * @return std::unique_ptr<scalar> Scalar containing the single value
  */
 std::unique_ptr<scalar> get_element(

cpp/include/cudf/detail/binaryop.hpp

@@ -34,7 +34,7 @@ namespace detail {
  * @param lhs         The left operand scalar
  * @param rhs         The right operand column
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @param stream      CUDA stream on which to execute kernels
  * @return std::unique_ptr<column> Output column
  */
@@ -59,7 +59,7 @@ std::unique_ptr<column> binary_operation(
  * @param lhs         The left operand column
  * @param rhs         The right operand scalar
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @param stream      CUDA stream on which to execute kernels
  * @return std::unique_ptr<column> Output column
  */
@@ -84,7 +84,7 @@ std::unique_ptr<column> binary_operation(
  * @param lhs         The left operand column
  * @param rhs         The right operand column
  * @param output_type The desired data type of the output column
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @param stream      CUDA stream on which to execute kernels
  * @return std::unique_ptr<column> Output column
  */
@@ -113,7 +113,7 @@ std::unique_ptr<column> binary_operation(
  * @param output_type The desired data type of the output column. It is assumed
  *                    that output_type is compatible with the output data type
  *                    of the function in the PTX code
- * @param mr          Memory resource for allocating output column
+ * @param mr          Device memory resource used to allocate the returned column
  * @param stream      CUDA stream on which to execute kernels
  * @return std::unique_ptr<column> Output column
  */

cpp/include/cudf/detail/copy_if_else.cuh

@@ -153,7 +153,7 @@ __launch_bounds__(block_size) __global__
  * @param rhs         Begin iterator of rhs range
  * @param filter      Function of type `FilterFn` which determines for index `i` where to get the
  *                    corresponding output value from
- * @param mr          Memory resource to use for allocating the output
+ * @param mr          Device memory resource used to allocate the returned column
  * @param stream      CUDA stream to perform the computation in
  * @return            A new column that contains the values from either `lhs` or `rhs` as determined
  *                    by `filter[i]`

cpp/include/cudf/detail/copy_range.cuh

@@ -255,7 +255,7 @@ void copy_range_in_place(column_view const& source,
  * @param source_end The index of the last element in the source range
  * (exclusive)
  * @param target_begin The starting index of the target range (inclusive)
- * @param mr Memory resource to allocate the result target column.
+ * @param mr Device memory resource used to allocate the returned column
  * @param stream CUDA stream to run this function
  * @return std::unique_ptr<column> The result target column
  */

cpp/include/cudf/detail/dlpack.hpp

@@ -32,7 +32,7 @@ namespace detail {
  * @throw cudf::logic_error if the any of the DLTensor fields are unsupported
  *
  * @param managed_tensor a 1D or 2D column-major (Fortran order) tensor
- * @param mr Optional resource to use for device memory allocation
+ * @param mr Device memory resource used to allocate the returned table
  * @param stream Optional stream on which to execute
  *
  * @return Table with a copy of the tensor data
@@ -56,7 +56,7 @@ std::unique_ptr<experimental::table> from_dlpack(
  * or if any of columns have non-zero null count
  *
  * @param input Table to convert to DLPack
- * @param mr Optional resource to use for device memory allocation
+ * @param mr Device memory resource used to allocate the returned DLManagedTensor
  * @param stream Optional stream on which to execute
  *
  * @return 1D or 2D DLPack tensor with a copy of the table data, or nullptr

cpp/include/cudf/detail/fill.hpp

@@ -80,7 +80,7 @@ void fill_in_place(mutable_column_view& destination,
  * @param begin The starting index of the fill range (inclusive)
  * @param end The index of the last element in the fill range (exclusive)
  * @param value The scalar value to fill
- * @param mr Memory resource to allocate the result output column
+ * @param mr Device memory resource used to allocate the returned column
  * @param stream CUDA stream to run this function
  * @return std::unique_ptr<column> The result output column
  */

cpp/include/cudf/detail/gather.cuh

@@ -112,7 +112,7 @@ struct column_gatherer_impl {
    *map
    * @param gather_map_end End of iterator range of integral values representing the gather map
    * @param nullify_out_of_bounds Nullify values in `gather_map` that are out of bounds
-   * @param mr Memory resource to use for all allocations
+   * @param mr Device memory resource used to allocate the returned column
    * @param stream CUDA stream on which to execute kernels
    */
   std::unique_ptr<column> operator()(column_view const& source_column,
@@ -171,7 +171,7 @@ struct column_gatherer_impl<string_view, MapItType> {
    *map
    * @param gather_map_end End of iterator range of integral values representing the gather map
    * @param nullify_out_of_bounds Nullify values in `gather_map` that are out of bounds
-   * @param mr Memory resource to use for all allocations
+   * @param mr Device memory resource used to allocate the returned column
    * @param stream CUDA stream on which to execute kernels
    */
   std::unique_ptr<column> operator()(column_view const& source_column,
@@ -205,7 +205,7 @@ struct column_gatherer_impl<dictionary32, MapItType> {
    * map
    * @param gather_map_end End of iterator range of integral values representing the gather map
    * @param nullify_out_of_bounds Nullify values in `gather_map` that are out of bounds
-   * @param mr Memory resource to use for all allocations
+   * @param mr Device memory resource used to allocate the returned column
    * @param stream CUDA stream on which to execute kernels
    * @return New dictionary column with gathered rows.
    */
@@ -272,7 +272,7 @@ struct column_gatherer {
    * map
    * @param gather_map_end End of iterator range of integral values representing the gather map
    * @param nullify_out_of_bounds Nullify values in `gather_map` that are out of bounds
-   * @param mr Memory resource to use for all allocations
+   * @param mr Device memory resource used to allocate the returned column
    * @param stream CUDA stream on which to execute kernels
    */
   template <typename Element, typename MapIterator>

cpp/include/cudf/detail/hashing.hpp

@@ -32,7 +32,7 @@ namespace detail {
  * @param input The table to partition
  * @param columns_to_hash Indices of input columns to hash
  * @param num_partitions The number of partitions to use
- * @param mr Optional resource to use for device memory allocation
+ * @param mr Device memory resource used to allocate the returned table
  * @param stream Optional stream to use for allocations and copies
  *
  * @returns An output table and a vector of row offsets to each partition
@@ -50,7 +50,7 @@ std::pair<std::unique_ptr<experimental::table>, std::vector<size_type>> hash_par
  * @param input The table of columns to hash
  * @param initial_hash Optional vector of initial hash values for each column.
  * If this vector is empty then each element will be hashed as-is.
- * @param mr Optional resource to use for device memory allocation
+ * @param mr Device memory resource used to allocate the returned column
  * @param stream Optional stream to use for allocations and copies
  *
  * @returns A column where each row is the hash of a column from the input