ptrendx commented on a change in pull request #16979: [Bugfix] [Numpy] Add
`kAddTo` and kNullOp to Transpose
URL: https://github.com/apache/incubator-mxnet/pull/16979#discussion_r354438866
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File path: src/operator/tensor/pseudo2DTranspose_op-inl.cuh
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@@ -39,22 +39,29 @@ namespace mxnet {
namespace op {
namespace cuda {
-
-template <typename DType, typename CType>
+/*!
+ * \brief The `transpose_pseudo2D` based on chosen vectorized types. It
transpose an array of
+ * shape (k, m, n) to (k, n, m)
+ * \param out Pointer to output memory.
+ * \param inp Pointer to input memory.
+ * \param m First of tensor dimensions.
+ * \param n Second of tensor dimensions.
+ * \param nIterY The number of iterations in the y-dim of the thread to cover
all rows. (1-->m)
+ * \param nIterZ The number of iterations in the z-dim of the thread to cover
all rows. (1-->m)
+ * \tparam DType Data type
+ * \tparam CType The type to load the data.
+ * \tparam TSR the vectorized ratio.
+ * \tparam is_addto Whether to perform out += transpose(data) or out =
transpose(data)
+ */
+template <typename DType, typename CType, int TSR, bool is_addto>
__global__ void transpose_pseudo2D(DType* out, DType* inp,
const index_t m, const index_t n,
const index_t nIterY, const index_t nIterZ)
{
- const index_t TSR = sizeof(CType)/sizeof(DType); // TypeSizeRatio
Review comment:
Why did you move this to template argument? It should be fine here (you can
even make it `constexpr`).
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