Revert "Allow Layouts to propogate to local_load" (#5237)

This is causing some performance regression. I'll investigate and reland
it.
Reverts #5219

lib/Dialect/TritonGPU/Transforms/Utility.cpp

@@ -563,8 +563,7 @@ bool canFoldIntoConversion(Operation *op, Attribute targetEncoding) {
   }
   return isa<triton::gpu::ConvertLayoutOp, arith::ConstantOp,
              triton::MakeRangeOp, triton::SplatOp, triton::HistogramOp,
-             triton::gpu::LocalAllocOp, triton::gpu::LocalLoadOp,
-             triton::gpu::LocalStoreOp>(op);
+             triton::gpu::LocalAllocOp, triton::gpu::LocalStoreOp>(op);
 }
 
 scf::ForOp replaceForOpWithNewSignature(

test/TritonGPU/combine.mlir

@@ -2685,21 +2685,3 @@ module attributes {"triton_gpu.num-warps" = 1 : i32, "triton_gpu.threads-per-war
     tt.return
   }
 }
-
-// -----
-
-#blocked = #triton_gpu.blocked<{sizePerThread = [1, 1, 1, 1, 4], threadsPerWarp = [2, 1, 16, 1, 1], warpsPerCTA = [1, 1, 2, 2, 1], order = [4, 0, 1, 2, 3]}>
-#blocked2 = #triton_gpu.blocked<{sizePerThread = [1, 1, 1, 1, 4], threadsPerWarp = [1, 1, 32, 1, 1], warpsPerCTA = [1, 1, 1, 1, 4], order = [4, 3, 2, 1, 0]}>
-#blocked1 = #triton_gpu.blocked<{sizePerThread = [1, 1, 1, 1, 4], threadsPerWarp = [2, 1, 16, 1, 1], warpsPerCTA = [1, 2, 2, 1, 1], order = [4, 0, 3, 2, 1]}>
-#shared = #triton_gpu.shared<{vec = 1, perPhase = 1, maxPhase = 1, order = [4, 0, 1, 2, 3], hasLeadingOffset = false}>
-module attributes {"triton_gpu.num-ctas" = 1 : i32, "triton_gpu.num-warps" = 4 : i32, triton_gpu.target = "cuda:100", "triton_gpu.threads-per-warp" = 32 : i32} {
-  // CHECK-LABEL: lift_convert_to_local_load
-  // CHECK-NOT: convert_layout
-  // CHECK: tt.return
-  tt.func public @lift_convert_to_local_load(%arg0 : !triton_gpu.memdesc<2x1x32x4x4xi8, #shared, #triton_gpu.shared_memory, mutable>) -> tensor<2x4x32x1x4xi8, #blocked2> {
-    %1 = triton_gpu.local_load %arg0 : !triton_gpu.memdesc<2x1x32x4x4xi8, #shared, #triton_gpu.shared_memory, mutable> -> tensor<2x1x32x4x4xi8, #blocked>
-    %2 = tt.trans %1 {order = array<i32: 0, 3, 2, 1, 4>} : tensor<2x1x32x4x4xi8, #blocked> -> tensor<2x4x32x1x4xi8, #blocked1>
-    %3 = triton_gpu.convert_layout %2 : tensor<2x4x32x1x4xi8, #blocked1> -> tensor<2x4x32x1x4xi8, #blocked2>
-    tt.return %3 : tensor<2x4x32x1x4xi8, #blocked2>
-  }
-}