Integrate LLVM up to https://github.com/llvm/llvm-project/commit/129cf84e6953

PiperOrigin-RevId: 306623856
Change-Id: I8a5a1ef0cb6152e72397dd8a93841da01b10534c

tensorflow/compiler/mlir/tensorflow/ir/tf_device.cc

@@ -40,7 +40,6 @@ limitations under the License.
 #include "mlir/IR/Value.h"  // from @llvm-project
 #include "mlir/Support/LLVM.h"  // from @llvm-project
 #include "mlir/Support/LogicalResult.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "mlir/Transforms/InliningUtils.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
 #include "tensorflow/core/platform/logging.h"
@@ -90,7 +89,7 @@ struct TFInlinerInterface : public DialectInlinerInterface {
 // are perfectly forwarded to the block's terminator.
 bool BlockWrapsSingleOp(Block* block) {
   auto body = block->without_terminator();
-  if (!has_single_element(body)) return false;
+  if (!hasSingleElement(body)) return false;
 
   Operation& wrapped_op = *body.begin();
   Operation* terminator = block->getTerminator();

tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc

@@ -41,7 +41,6 @@ limitations under the License.
 #include "mlir/IR/Types.h"  // from @llvm-project
 #include "mlir/IR/Value.h"  // from @llvm-project
 #include "mlir/Support/LogicalResult.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "mlir/Transforms/FoldUtils.h"  // from @llvm-project
 #include "mlir/Transforms/InliningUtils.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
@@ -318,7 +317,7 @@ YieldOp IslandOp::GetYield() { return llvm::cast<YieldOp>(GetBody().back()); }
 // operation results are perfectly forwarded to the islands yield.
 bool IslandOp::WrapsSingleOp() {
   auto body = GetBody().without_terminator();
-  if (!has_single_element(body)) return false;
+  if (!hasSingleElement(body)) return false;
 
   Operation &wrapped_op = *body.begin();
   YieldOp yield = GetYield();

tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc

@@ -55,7 +55,6 @@ limitations under the License.
 #include "mlir/Parser.h"  // from @llvm-project
 #include "mlir/Support/LLVM.h"  // from @llvm-project
 #include "mlir/Support/LogicalResult.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "mlir/Transforms/InliningUtils.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_structs.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

tensorflow/compiler/mlir/tensorflow/transforms/parallel_execute_to_islands.cc

@@ -237,7 +237,7 @@ LogicalResult CreateIslandsFromParallelExecute(
 // individual islands per region of parallel_execute.
 void LowerSingleIslandParallelExecuteToIslands(
     tf_executor::IslandOp island_op) {
-  if (!has_single_element(island_op.GetBody().without_terminator())) return;
+  if (!hasSingleElement(island_op.GetBody().without_terminator())) return;
 
   if (auto parallel_execute_op = llvm::dyn_cast<tf_device::ParallelExecuteOp>(
           &island_op.GetBody().front()))

tensorflow/compiler/mlir/tensorflow/transforms/promote_resources_to_args.cc

@@ -256,7 +256,7 @@ void PromoteResourcesToArgsPass::runOnOperation() {
   // This routine should only be called when control flow operations are still
   // represented with TF IfOp and WhileOp operations. In this case, there should
   // be only one basic blocks in the MLIR representation.
-  if (!has_single_element(main_func.getBlocks())) {
+  if (!hasSingleElement(main_func.getBlocks())) {
     main_func.emitError() << "expects 'main' function to have 1 block, got "
                           << main_func.getBlocks().size();
     return signalPassFailure();

tensorflow/compiler/mlir/tensorflow/transforms/replicate_to_island.cc

@@ -211,7 +211,7 @@ LogicalResult CreateIslandsFromReplicate(const Dialect* tf_dialect,
 // islands per replica of the replicate.
 LogicalResult LowerSingleIslandReplicateToIslands(
     const Dialect* tf_dialect, tf_executor::IslandOp island_op) {
-  if (!has_single_element(island_op.GetBody().without_terminator()))
+  if (!hasSingleElement(island_op.GetBody().without_terminator()))
     return success();
 
   if (auto replicate_op =

tensorflow/compiler/mlir/tensorflow/transforms/resource_op_lifting.cc

@@ -1112,7 +1112,7 @@ LogicalResult ResourceLiftingForFunctionalControlFlow(FuncOp function) {
   // This routine should only be called when control flow operations are still
   // represented with TF IfOp and WhileOp operations. In this case, there should
   // be only one basic blocks in the MLIR representation.
-  if (!has_single_element(function.getBlocks())) {
+  if (!hasSingleElement(function.getBlocks())) {
     return function.emitError()
            << "expect the function to have 1 block while it has "
            << function.getBlocks().size();

tensorflow/compiler/mlir/tensorflow/transforms/tpu_dynamic_layout_pass.cc

@@ -32,7 +32,6 @@ limitations under the License.
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Pass/PassRegistry.h"  // from @llvm-project
 #include "mlir/Support/LLVM.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

tensorflow/compiler/mlir/tensorflow/transforms/tpu_variable_runtime_reformatting.cc

@@ -38,7 +38,6 @@ limitations under the License.
 #include "mlir/IR/Value.h"  // from @llvm-project
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Pass/PassRegistry.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "mlir/Transforms/RegionUtils.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"

tensorflow/compiler/mlir/tensorflow/translate/breakup-islands.cc

@@ -26,7 +26,6 @@ limitations under the License.
 #include "mlir/IR/Value.h"  // from @llvm-project
 #include "mlir/Pass/Pass.h"  // from @llvm-project
 #include "mlir/Pass/PassRegistry.h"  // from @llvm-project
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "tensorflow/compiler/mlir/tensorflow/analysis/side_effect_analysis.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
 #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
@@ -220,7 +219,7 @@ void BreakUpIslands::BreakUpIsland(
   }
 
   // Skip islands that are already only a single op.
-  if (has_single_element(island_body)) return;
+  if (hasSingleElement(island_body)) return;
 
   auto control_type = tf_executor::ControlType::get(&getContext());
   auto island_control_inputs = llvm::to_vector<4>(island_op.controlInputs());

tensorflow/compiler/mlir/tensorflow/translate/export_graphdef.cc

@@ -143,7 +143,7 @@ Status HasSingleGraphSingleOpIslandsFunctions(mlir::ModuleOp module) {
       return mlir::WalkResult::interrupt();
     }
 
-    if (!has_single_element(block)) {
+    if (!hasSingleElement(block)) {
       status = errors::FailedPrecondition(
           kInvalidExecutorGraphMsg,
           "function does not only contain a single tf_executor.graph.");

tensorflow/compiler/mlir/tensorflow/translate/import_model.cc

@@ -1885,13 +1885,13 @@ StatusOr<mlir::OwningModuleRef> GraphDefImporter::Convert(
       auto node_name = [&](const OutputTensor& tensor) {
         ss << tensor.node->name();
       };
-      mlir::interleave(arg_nodes, ss, node_name, ",");
+      llvm::interleave(arg_nodes, ss, node_name, ",");
       auto inputs = b.getNamedAttr("inputs", b.getStringAttr(ss.str()));
       s.clear();
-      mlir::interleave(ret_nodes, ss, node_name, ",");
+      llvm::interleave(ret_nodes, ss, node_name, ",");
       auto outputs = b.getNamedAttr("outputs", b.getStringAttr(ss.str()));
       s.clear();
-      mlir::interleave(specs.control_outputs, ss, ",");
+      llvm::interleave(specs.control_outputs, ss, ",");
       auto control_outputs =
           b.getNamedAttr("control_outputs", b.getStringAttr(ss.str()));
 
@@ -1916,16 +1916,16 @@ StatusOr<mlir::OwningModuleRef> GraphDefImporter::Convert(
       mlir::Builder b(context);
       std::string s;
       llvm::raw_string_ostream ss(s);
-      mlir::interleave(
+      llvm::interleave(
           specs.inputs, ss,
           [&](const std::pair<std::string, ArrayInfo>& v) { ss << v.first; },
           ",");
       auto inputs = b.getNamedAttr("inputs", b.getStringAttr(ss.str()));
       s.clear();
-      mlir::interleave(specs.outputs, ss, ",");
+      llvm::interleave(specs.outputs, ss, ",");
       auto outputs = b.getNamedAttr("outputs", b.getStringAttr(ss.str()));
       s.clear();
-      mlir::interleave(specs.control_outputs, ss, ",");
+      llvm::interleave(specs.control_outputs, ss, ",");
       auto control_outputs =
           b.getNamedAttr("control_outputs", b.getStringAttr(ss.str()));
 

tensorflow/compiler/mlir/xla/operator_writer_gen.cc

@@ -15,6 +15,7 @@ limitations under the License.
 
 #include <sstream>
 
+#include "llvm/ADT/STLExtras.h"
 #include "llvm/ADT/Sequence.h"
 #include "llvm/ADT/StringExtras.h"
 #include "llvm/ADT/StringMap.h"
@@ -26,13 +27,12 @@ limitations under the License.
 #include "llvm/TableGen/Main.h"
 #include "llvm/TableGen/Record.h"
 #include "llvm/TableGen/TableGenBackend.h"
-#include "mlir/Support/STLExtras.h"  // from @llvm-project
 #include "mlir/TableGen/Operator.h"  // from @llvm-project
 
+using llvm::interleaveComma;
 using llvm::raw_ostream;
 using llvm::RecordKeeper;
 using llvm::StringRef;
-using mlir::interleaveComma;
 using mlir::tblgen::Attribute;
 using mlir::tblgen::NamedAttribute;
 using mlir::tblgen::NamedTypeConstraint;

tensorflow/workspace.bzl

@@ -658,8 +658,8 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""):
     )
 
     # Check out LLVM and MLIR from llvm-project.
-    LLVM_COMMIT = "37ac1c19bed7b7d22e9312dfa61e7a4506ed4e49"
-    LLVM_SHA256 = "b694cd7ed85cbc938f11534d56a326126015de21a5fec3c073dc6125bec1fc24"
+    LLVM_COMMIT = "129cf84e69537ae5c184550f94be18da738d9261"
+    LLVM_SHA256 = "4b56ff735e973ee982c4f24ab5b22d56ad0734f2d12d9c57fe1c21530a5840a0"
     LLVM_URLS = [
         "https://storage.googleapis.com/mirror.tensorflow.org/github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),
         "https://github.com/llvm/llvm-project/archive/{commit}.tar.gz".format(commit = LLVM_COMMIT),

third_party/mlir/BUILD

@@ -728,7 +728,6 @@ cc_library(
         ],
     ),
     hdrs = glob([
-        "include/mlir/ADT/*.h",
         "include/mlir/Support/*.h",
     ]),
     includes = ["include"],