[BACKEND] Minor Bugfixes for SharedToDotOperand MMAv3 (triton-lang#5030)

Two bugfixes following triton-lang#5009.

- When `BLOCK_M=64` and `num_warps > 4`, the order of warps for
DotOpEncoded tensor should be M-major instead of N-major, since WGMMA
expects the 4 warps in each warp group to be stacked along the M
dimension.
- Should use `mmaBitwidth` instead of `bitwidth` when calculating
`numRep` in `SharedToDotOperandMMAv2OrV3`. This was missed in a bad
rebase.

@lezcano I encountered these bugs when attempting to locally test the
[DotOp hoisting PR](triton-lang#5003)
after rebasing (they normally would be caught by `test_core.py` but that
path was not yet enabled in the last PR). With these fixes added, I was
able to successfully validate against pytorch.

(cherry picked from commit e82dfd9)

third_party/nvidia/lib/TritonNVIDIAGPUToLLVM/ConvertLayoutOpToLLVM/SharedToDotOperandMMAv2OrV3.cpp

@@ -659,15 +659,15 @@ Value loadArg(ConversionPatternRewriter &rewriter, Location loc,
 
   int kWidth = encoding.getKWidth();
   auto numRep = mmaLayout.getMMAv2OrV3RepForOperand(
-      shapePerCTA, bitwidth, kWidth, encoding.getOpIdx());
+      shapePerCTA, mmaBitwidth, kWidth, encoding.getOpIdx());
 
   auto warpsPerCTA = mmaLayout.getWarpsPerCTA();
-  auto order = triton::gpu::getOrder(mmaLayout);
+  auto warpOrder = mmaLayout.getWarpOrder();
   Value warp = udiv(thread, i32_val(32));
   Value lane = urem(thread, i32_val(32));
 
   SmallVector<Value> multiDimWarpId =
-      delinearize(rewriter, loc, warp, warpsPerCTA, order);
+      delinearize(rewriter, loc, warp, warpsPerCTA, warpOrder);
   Value warpB = urem(multiDimWarpId[0], i32_val(shapePerCTA[0]));
   int warpsPerTile;
   Value warpM = urem(multiDimWarpId[1], i32_val(shapePerCTA[1] / 16));