[LLVM Integrate] Bump llvm, torch-mlir, stablehlo

deps.bzl

@@ -22,8 +22,8 @@ def third_party_deps():
             path = local_llvm_repo_path(),
         )
     else:
-        LLVM_COMMIT = "f9031f00f2c90bc0af274b45ec3e169b5250a688"
-        LLVM_SHA256 = "695896a5c3b4011043c27a43ac17079ee725e2d72e3b664868f09626a187daf3"
+        LLVM_COMMIT = "6c64c8a6f3f77c30745c751d4163ff6bf2fc323b"
+        LLVM_SHA256 = "a27f8452e8a4267acb7bf59ea4dae012cec22e37624a67206b927985554e3640"
         http_archive(
             name = "llvm-raw",
             build_file_content = "# empty",
@@ -39,8 +39,8 @@ def third_party_deps():
             path = local_torch_mlir_repo_path(),
         )
     else:
-        TORCH_MLIR_COMMIT = "98e08023bbf71e00ab81e980eac9f7c96f1f24b4"
-        TORCH_MLIR_SHA256 = "b3bac5863c73dc97bde06a032a928fe0fe586c44c8005bdbb3edd9def056ef0d"
+        TORCH_MLIR_COMMIT = "30c519369ed7eabad0282d0f874500a9b41fcbbd"
+        TORCH_MLIR_SHA256 = "9598ab5bb4a75cd63a078fccb19b380f753906153a92ff7ee5dca3eba93deba5"
         http_archive(
             name = "torch-mlir-raw",
             build_file_content = "# empty",
@@ -55,8 +55,8 @@ def third_party_deps():
             path = local_stablehlo_repo_path(),
         )
     else:
-        STABLEHLO_COMMIT = "c28d55e91b4a5daaff18a33ce7e9bbd0f171256a"
-        STABLEHLO_SHA256 = "b7c18132c092ec60604e8869685a745a2b31fc1edfc64caf5b19ddce0f1cee60"
+        STABLEHLO_COMMIT = "6e403b1aa6a71f5eaa09cc720e4ad42f692745e6"
+        STABLEHLO_SHA256 = "5b6a207f7c41aa986866103a4929e7146acff05830234df5714a45c7100cae3c"
         http_archive(
             name = "stablehlo",
             sha256 = STABLEHLO_SHA256,

include/mlir-tcp/Dialect/IR/TcpOps.h

@@ -10,7 +10,7 @@
 #pragma once
 
 #include "mlir/Dialect/Func/IR/FuncOps.h"
-#include "mlir/Dialect/Quant/QuantTypes.h"
+#include "mlir/Dialect/Quant/IR/QuantTypes.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/BuiltinTypes.h"
 #include "mlir/IR/Dialect.h"

lib/Dialect/IR/TcpTilingInterfaceImpl.cpp

@@ -143,7 +143,8 @@ struct SliceOpTiling
         getValueOrCreateConstantIndexOp(b, loc, sizes), sliceOp.getStrides());
 
     return TilingResult{{returnSliceOp},
-                        SmallVector<Value>(returnSliceOp->getResults())};
+                        SmallVector<Value>(returnSliceOp->getResults()),
+                        {extractOp}};
   }
 
   LogicalResult

temp.mlir

@@ -0,0 +1,35 @@
+func.func @fuse_tcp_slice(%arg0: tensor<40x40xf32>) -> tensor<32x32xf32> {
+    %shape40 = tensor.empty() : tensor<40x40xf32>
+
+    %0 = linalg.elemwise_binary ins(%arg0, %arg0 : tensor<40x40xf32>, tensor<40x40xf32>)
+                             outs(%shape40: tensor<40x40xf32>) -> tensor<40x40xf32>
+
+    %c32 = arith.constant 32 : index
+    %c16 = arith.constant 16 : index
+    %c3 = arith.constant 3 : index
+    %c5 = arith.constant 5 : index
+    %c1 = arith.constant 1 : index
+    %slice = tcp.slice %0 starts ( %c3, %c5 ) sizes ( %c32, %c32 ) strides ( %c1, %c1 ) : tensor<40x40xf32> -> tensor<32x32xf32>
+
+    %shape = tensor.empty() : tensor<32x32xf32>
+    %ret = linalg.elemwise_unary ins(%slice: tensor<32x32xf32>) outs(%shape: tensor<32x32xf32>) -> tensor<32x32xf32>
+
+    return %ret : tensor<32x32xf32>
+}
+
+module attributes {transform.with_named_sequence} {
+  transform.named_sequence @__transform_main(%arg0: !transform.any_op {transform.readonly}) {
+    %unary = transform.structured.match ops{["linalg.elemwise_unary"]} in %arg0 : (!transform.any_op) -> !transform.any_op
+
+    %1, %loops:2 = transform.structured.fuse %unary {tile_sizes = [1, 1], tile_interchange = [0, 1]}
+      : (!transform.any_op) -> (!transform.any_op, !transform.any_op, !transform.any_op)
+
+    %func_op = transform.structured.match ops{["func.func"]} in %arg0 : (!transform.any_op) -> !transform.op<"func.func">
+    transform.apply_patterns to %func_op {
+      transform.apply_patterns.tensor.fold_tensor_empty
+      transform.apply_patterns.tensor.fold_tensor_subset_ops
+    } : !transform.op<"func.func">
+
+    transform.yield
+  }
+}