[rocm-libraries] ROCm/rocm-libraries#6399 (commit 13bf528)

[CK][CK TILE] Modify elementwise kernel template signature to
 accept independent type arguments (#6399)

## Motivation

modify elementwise kernel template signature to fix cshuffle epilogue
build error

## Technical Details

Encountered a build error while building conv fallback kernel with
dispatcher.
Error: Type mismatch in `ElementWiseKernel::operator()` where the
template required all three parameters (lens, input_strides,
output_strides) to be the same type, but the CShuffle epilogue was
passing them with different tuple element types.

Solution: Modified the template signature in elementwise_kernel.hpp to
accept three independent type parameters:

Changed from single typename `Dims` to typename `DimsLens`, typename
`DimsInStrides`, typename `DimsOutStrides`
Updated references to `Dims::size()` to use the appropriate specific
type

## Test Plan

- Test with dispatcher conv unit tests
- Relying on CI tests

## Test Result
- Dispatcher unit tests passed
- Relying on CI tests

## Submission Checklist

- [x] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.

Author: yraparti

include/ck_tile/ops/elementwise/kernel/elementwise_kernel.hpp

@@ -27,10 +27,13 @@ struct ElementWiseKernel
         return is_wave32() ? kBlockSize / 2 : kBlockSize;
     }
 
-    template <typename... XDataType, typename Dims>
-    CK_TILE_DEVICE void operator()(const Dims lens,
-                                   const Dims input_strides,
-                                   const Dims output_strides,
+    template <typename... XDataType,
+              typename DimsLens,
+              typename DimsInStrides,
+              typename DimsOutStrides>
+    CK_TILE_DEVICE void operator()(const DimsLens lens,
+                                   const DimsInStrides input_strides,
+                                   const DimsOutStrides output_strides,
                                    const tuple<XDataType...>& input_tensors,
                                    YDataType* p_y) const
     {
@@ -49,10 +52,11 @@ struct ElementWiseKernel
                     input_tensors.get(i), lens, input_strides, number<S::kVectorM>{}, number<1>{});
 
                 const auto transformed_tensor = pad_tensor_view(
-                    transform_tensor_view(tensor_view,
-                                          ck_tile::make_tuple(merge_transform),
-                                          ck_tile::make_tuple(make_index_sequence<Dims::size()>{}),
-                                          ck_tile::make_tuple(sequence<0>{})),
+                    transform_tensor_view(
+                        tensor_view,
+                        ck_tile::make_tuple(merge_transform),
+                        ck_tile::make_tuple(make_index_sequence<DimsLens::size()>{}),
+                        ck_tile::make_tuple(sequence<0>{})),
                     ck_tile::make_tuple(number<S::kBlockM>{}),
                     sequence<Problem::kPad>{});
 
@@ -86,13 +90,14 @@ struct ElementWiseKernel
         const auto y_m_n = make_naive_tensor_view<address_space_enum::global>(
             p_y, lens, output_strides, number<S::kVectorM>{});
 
-        const auto transformed_y_m_n = pad_tensor_view(
-            transform_tensor_view(y_m_n,
-                                  ck_tile::make_tuple(merge_transform),
-                                  ck_tile::make_tuple(make_index_sequence<Dims::size()>{}),
-                                  ck_tile::make_tuple(sequence<0>{})),
-            ck_tile::make_tuple(number<S::kBlockM>{}),
-            sequence<Problem::kPad>{});
+        const auto transformed_y_m_n =
+            pad_tensor_view(transform_tensor_view(
+                                y_m_n,
+                                ck_tile::make_tuple(merge_transform),
+                                ck_tile::make_tuple(make_index_sequence<DimsOutStrides::size()>{}),
+                                ck_tile::make_tuple(sequence<0>{})),
+                            ck_tile::make_tuple(number<S::kBlockM>{}),
+                            sequence<Problem::kPad>{});
 
         auto y_window = make_tile_window(transformed_y_m_n,
                                          make_tuple(number<S::kBlockM>{}),