CUDA: Factor out and re-use block_reduce function (#18785)

* CUDA: Refactor and expose two_stage_warp_reduce_* function

* Use `two_stage_warp_reduce` also in softmax kernel, move smem out of it

Moving smem out of `__device__` function to `__global__` function
allows for explicit smem reuse, as either compiler or cuda rt seem to not
free it afterwards (`cudaFuncSetAttribute` fails when not accounting for
it once for each call to two_stage_warp_reduce)

* Update ggml/src/ggml-cuda/common.cuh

Co-authored-by: Aman Gupta <amangupta052@gmail.com>

* Use two_stage_warp_reduce in group_norm_f32

* Use two_stage_warp_reduce in rms_norm_f32

* Fix smem calculation which expects bytes

* Make `two_stage_warp_reduce` accept all values warp_reduce accepts

Also integrate it into norm_f32 function

* Use two_stage_warp_reduce in l2_norm_f32

* Use type traits for block reduction for better legibility

Also adresss other requests by @am17an such as variable renaming

* Make norm tests cover all cuda paths

* Mark columns % WARP_SIZE !=0 as supported for RMS_NORM_BACK

Unit-tests passed locally, let's see if they pass in the CI as well

* Use `enum class` for `block_reduce_method`

This is more type-safe than plain enum

* Rename variables as suggested in code review by @am17an

* Rename two_stage_warp_reduce -> block_reduce

* Fix trailing whitespace in common.cuh

* Make condition of static_assert type-dependent

This delays evaluation until the template is actually instantiated.
Otherwise, some compilers may evaluate the assert when parsing the
template, resulting in build errors as observed here:

https://github.com/ggml-org/llama.cpp/actions/runs/20960323123/job/60235530068?pr=18785

* Inline definitions

---------

Co-authored-by: Aman Gupta <amangupta052@gmail.com>

ggml/src/ggml-cuda/ggml-cuda.cu

@@ -4551,7 +4551,7 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
         case GGML_OP_L2_NORM:
             return true;
         case GGML_OP_RMS_NORM_BACK:
-            return ggml_is_contiguous(op->src[0]) && op->ne[0] % WARP_SIZE == 0;
+            return ggml_is_contiguous(op->src[0]);
             break;
         case GGML_OP_NONE:
         case GGML_OP_RESHAPE: