Updated for changes in LLVM 7a45aeacf3a2.

- The deprecated CreateCall(Value*, ...) IRBuilder API has been removed.
- Renamed applyPatternsGreedily to applyPatternsAndFoldGreedily in MLIR.
- Update MLIR users after adding support for optional operands/results to ODS (upstream aba1acc89c653b2cc08cccfb754ff16994a05332)
- Other updates to BUILD files for upstream changes.

PiperOrigin-RevId: 306177884
Change-Id: Idae1009ba89caf296758748ab7aa57815d946a0c

tensorflow/compiler/mlir/lite/converter_gen.cc

@@ -496,7 +496,7 @@ static bool RuntimeVerifierWriterMain(raw_ostream &os, RecordKeeper &records) {
       auto &value = op.getOperand(i);
       // Skip from from first variadic operands for now. Else getOperand index
       // used below doesn't match.
-      if (value.isVariadic()) break;
+      if (value.isVariableLength()) break;
       if (!value.name.empty())
         verify_ctx.addSubst(value.name, formatv("op->getOperand({0})", i));
     }
@@ -504,7 +504,7 @@ static bool RuntimeVerifierWriterMain(raw_ostream &os, RecordKeeper &records) {
       auto &value = op.getResult(i);
       // Skip from from first variadic results for now. Else getResult index
       // used below doesn't match.
-      if (value.isVariadic()) break;
+      if (value.isVariableLength()) break;
       if (!value.name.empty())
         verify_ctx.addSubst(value.name, formatv("op->getResult({0})", i));
     }

tensorflow/compiler/mlir/lite/quantization/tensorflow/tf_to_quant.cc

@@ -146,7 +146,7 @@ void LegalizeTFToQuant::runOnFunction() {
   auto func = getFunction();
   auto *ctx = func.getContext();
   patterns.insert<PreparePerTensorFakeQuant, PreparePerChannelFakeQuant>(ctx);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 }  // namespace
 

tensorflow/compiler/mlir/lite/transforms/dilated_conv.cc

@@ -30,7 +30,7 @@ void IdentifyDilatedConvPass::runOnFunction() {
   patterns.insert<ConvertTFDilatedConvOp<TF::Conv2DOp>,
                   ConvertTFDilatedConvOp<TF::DepthwiseConv2dNativeOp>>(
       &getContext());
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 }  // namespace
 

tensorflow/compiler/mlir/lite/transforms/optimize.cc

@@ -711,7 +711,7 @@ void Optimize::runOnFunction() {
   TFL::populateWithGenerated(ctx, &patterns);
   patterns.insert<FuseFullyConnectedAndAdd, FuseFullyConnectedAndRelu,
                   FuseFullyConnectedAndMul>(ctx);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 
   // Fuse the binary ops with the following ops.
   patterns.insert<
@@ -719,7 +719,7 @@ void Optimize::runOnFunction() {
       FuseBinaryOpToFollowingFullyConnected, FuseConv2DAndMulWithQDQs,
       FuseDepthwiseConv2DAndMulWithQDQs, ConvertTrivialTransposeOpToReshapeOp>(
       ctx);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 }  // namespace

tensorflow/compiler/mlir/lite/transforms/optimize_functional_ops.cc

@@ -187,7 +187,7 @@ void OptimizeFunctionalOpsPass::runOnOperation() {
   patterns.insert<FoldIfOp>(&getContext(), &inlined_funcs);
 
   ModuleOp module = getOperation();
-  applyPatternsGreedily(module, patterns);
+  applyPatternsAndFoldGreedily(module, patterns);
 
   // Erase inlined functions that don't have any references.
   //

tensorflow/compiler/mlir/lite/transforms/post_quantize.cc

@@ -125,7 +125,7 @@ void PostQuantizePass::runOnFunction() {
   auto func = getFunction();
   auto* ctx = func.getContext();
   TFL::populateWithGenerated(ctx, &patterns);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 
   if (!emit_quant_adaptor_ops_) {
     RemoveQuantizationAdaptorOps(getFunction());

tensorflow/compiler/mlir/lite/transforms/prepare_quantize.cc

@@ -267,7 +267,7 @@ void PrepareQuantizePass::runOnFunction() {
     // Currently, only activation stats are imported, so narrow_range = false.
     patterns.insert<PrepareQuantStats>(8, false, false, ctx);
   }
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 
   SanityCheckAndAdjustment(func);
 

tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc

@@ -619,8 +619,8 @@ void PrepareTFPass::runOnFunction() {
 
   // This pattern was intented to uses TFL QDQs to preserve the quantization
   // parameters from the TF Quant ops, thus this pattern should run with the
-  // first `applyPatternsGreedily` method, which would otherwise removes the
-  // TF FakeQuant ops by the constant folding.
+  // first `applyPatternsAndFoldGreedily` method, which would otherwise removes
+  // the TF FakeQuant ops by the constant folding.
   patterns.insert<PreparePerTensorFakeQuant, PreparePerChannelFakeQuant>(ctx);
 
   // This pattern will try to identify and optimize for dilated convolution.
@@ -634,7 +634,7 @@ void PrepareTFPass::runOnFunction() {
   // This will allow optimizing any TF_Mul->TF_Conv in the graph
   // and any expanded from FusedBatchNorm. We need to do this
   // before converting TF_Conv to TFL_Conv
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 
   // Load the generated pattern again, so new quantization pass-through
   // will be applied.
@@ -646,7 +646,7 @@ void PrepareTFPass::runOnFunction() {
   }
   patterns.insert<TF::ConvertTFEinsumOp, ConvertTFConv2D,
                   ConvertTFDepthwiseConv2dNative, ConvertTFStridedSlice>(ctx);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 }  // namespace

tensorflow/compiler/mlir/lite/transforms/quantize.cc

@@ -88,7 +88,7 @@ void QuantizePass::runOnFunction() {
   TFL::populateWithGenerated(ctx, &patterns);
   patterns.insert<TFLFullQuantization>(
       ctx, enable_numeric_verify, error_tolerance, enable_single_layer_verify);
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 }  // namespace
 

tensorflow/compiler/mlir/tensorflow/transforms/batchmatmul_to_einsum.cc

@@ -55,7 +55,7 @@ void BatchMatMulToEinsumPass::runOnFunction() {
   patterns.insert<ConvertTFBatchMatMulToEinsumOp<TF::BatchMatMulOp>,
                   ConvertTFBatchMatMulToEinsumOp<TF::BatchMatMulV2Op>>(
       &getContext());
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 }  // namespace

tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops_pass.cc

@@ -45,7 +45,7 @@ struct DecomposeResourceOps
     OwningRewritePatternList patterns;
     mlir::TF::PopulateDecomposeResourceOpsPatterns(&getContext(), &patterns);
 
-    applyPatternsGreedily(getFunction(), patterns);
+    applyPatternsAndFoldGreedily(getFunction(), patterns);
   }
 };
 

tensorflow/compiler/mlir/tensorflow/transforms/einsum.cc

@@ -364,7 +364,7 @@ void TransformEinsumPass::runOnFunction() {
   auto func = getFunction();
 
   patterns.insert<ConvertTFEinsumOp>(&getContext());
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 static PassRegistration<TransformEinsumPass> pass(

tensorflow/compiler/mlir/tensorflow/transforms/gpu_fusion.cc

@@ -118,7 +118,7 @@ void GpuOpFusionPass::runOnFunction() {
   FuncOp func = getFunction();
   OwningRewritePatternList patterns;
   patterns.insert<ReluToFusedBatchNorm>(&getContext());
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 }  // namespace

tensorflow/compiler/mlir/tensorflow/transforms/lower_tf_pass.cc

@@ -29,7 +29,7 @@ struct LowerTF : public PassWrapper<LowerTF, FunctionPass> {
     OwningRewritePatternList patterns;
     mlir::TF::PopulateLoweringTFPatterns(&getContext(), &patterns);
 
-    applyPatternsGreedily(getFunction(), patterns);
+    applyPatternsAndFoldGreedily(getFunction(), patterns);
   }
 };
 

tensorflow/compiler/mlir/tensorflow/transforms/optimize.cc

@@ -38,7 +38,7 @@ struct TFOptimizePass : public PassWrapper<TFOptimizePass, FunctionPass> {
     OwningRewritePatternList patterns;
     auto func = getFunction();
     populateWithGenerated(&getContext(), &patterns);
-    applyPatternsGreedily(func, patterns);
+    applyPatternsAndFoldGreedily(func, patterns);
   }
 };
 

tensorflow/compiler/mlir/tensorflow/transforms/unroll_batch_matmul.cc

@@ -55,7 +55,7 @@ void UnrollBatchMatMulPass::runOnFunction() {
 
   patterns.insert<ConvertTFBatchMatMulOp<TF::BatchMatMulOp>,
                   ConvertTFBatchMatMulOp<TF::BatchMatMulV2Op>>(&getContext());
-  applyPatternsGreedily(func, patterns);
+  applyPatternsAndFoldGreedily(func, patterns);
 }
 
 }  // namespace

tensorflow/compiler/mlir/xla/operator_writer_gen.cc

@@ -81,7 +81,7 @@ static void BuildOperator(const Operator& op, raw_ostream* output) {
     // Emit an argument for an operand.
     if (auto* operand_cst = arg.dyn_cast<NamedTypeConstraint*>()) {
       // Handle a non-variadic operand.
-      if (!operand_cst->isVariadic()) {
+      if (!operand_cst->isVariableLength()) {
         os << "    auto xla_arg_" << index
            << " = value_map[*xla_op.getODSOperands(" << operand_number++
            << ").begin()];\n";
@@ -108,7 +108,7 @@ static void BuildOperator(const Operator& op, raw_ostream* output) {
 
   // If all operands are variadic, then pass the builder explicitly to xla
   // client API call
-  if (op.getNumOperands() == op.getNumVariadicOperands()) {
+  if (op.getNumOperands() == op.getNumVariableLengthOperands()) {
     os << "lowering_context.builder";
     if (op.getNumArgs() != 0) os << ", ";
   }

tensorflow/compiler/mlir/xla/transforms/legalize_to_standard.cc

@@ -198,7 +198,7 @@ void PopulateXlaToStdPatterns(OwningRewritePatternList *patterns,
 void LegalizeToStandard::runOnFunction() {
   OwningRewritePatternList patterns;
   mlir::xla_hlo::PopulateXlaToStdPatterns(&patterns, &getContext());
-  applyPatternsGreedily(getFunction(), patterns);
+  applyPatternsAndFoldGreedily(getFunction(), patterns);
 }
 
 static PassRegistration<LegalizeToStandard> legalize_pass(

tensorflow/compiler/mlir/xla/transforms/lhlo_legalize_to_affine.cc

@@ -87,7 +87,7 @@ struct LhloLegalizeToAffine
     OwningRewritePatternList patterns;
     auto func = getFunction();
     populateLHLOToAffineConversionPattern(func.getContext(), &patterns);
-    applyPatternsGreedily(func, patterns);
+    applyPatternsAndFoldGreedily(func, patterns);
   }
 };
 

tensorflow/compiler/mlir/xla/transforms/lower_complex.cc

@@ -71,7 +71,7 @@ void LowerComplex::runOnFunction() {
   OwningRewritePatternList patterns;
   mlir::xla::PopulateComplexLoweringPatterns(&getContext(), &patterns);
 
-  applyPatternsGreedily(getFunction(), patterns);
+  applyPatternsAndFoldGreedily(getFunction(), patterns);
 }
 
 static PassRegistration<LowerComplex> pass(

tensorflow/compiler/mlir/xla/transforms/lower_general_dot.cc

@@ -178,7 +178,7 @@ struct LegalizeGeneralDot
     OwningRewritePatternList patterns;
     mlir::xla_hlo::PopulateGeneralDotOpLoweringPatterns(&patterns,
                                                         &getContext());
-    applyPatternsGreedily(getFunction(), patterns);
+    applyPatternsAndFoldGreedily(getFunction(), patterns);
   }
 };
 

tensorflow/compiler/mlir/xla/transforms/unfuse_batch_norm_pass.cc

@@ -32,7 +32,7 @@ struct TestUnfuseBatchNormPass
   void runOnOperation() override {
     OwningRewritePatternList patterns;
     PopulateUnfuseBatchNormPatterns(&getContext(), &patterns);
-    applyPatternsGreedily(getOperation(), patterns);
+    applyPatternsAndFoldGreedily(getOperation(), patterns);
   }
 };
 

tensorflow/compiler/xla/service/llvm_ir/ir_builder_mixin.h

@@ -79,11 +79,31 @@ class IrBuilderMixin {
     return mixin_builder()->CreateBr(std::forward<Args>(args)...);
   }
 
+  llvm::CallInst* Call(llvm::FunctionCallee func_callee,
+                       llvm::ArrayRef<llvm::Value*> args = llvm::None,
+                       const llvm::Twine& name = "",
+                       llvm::MDNode* fp_math_tag = nullptr) {
+    return mixin_builder()->CreateCall(func_callee, args, name, fp_math_tag);
+  }
+
+  llvm::CallInst* Call(llvm::FunctionType* func_type, llvm::Value* callee,
+                       llvm::ArrayRef<llvm::Value*> args = llvm::None,
+                       const llvm::Twine& name = "",
+                       llvm::MDNode* fp_math_tag = nullptr) {
+    return mixin_builder()->CreateCall(func_type, callee, args, name,
+                                       fp_math_tag);
+  }
+
+  // DEPRECATED. LLVM is removing getPointerElementType, so calls to this must
+  // be transitioned to one of the other overloads.
   llvm::CallInst* Call(llvm::Value* callee,
                        llvm::ArrayRef<llvm::Value*> args = llvm::None,
                        const llvm::Twine& name = "",
                        llvm::MDNode* fp_math_tag = nullptr) {
-    return mixin_builder()->CreateCall(callee, args, name, fp_math_tag);
+    return mixin_builder()->CreateCall(
+        llvm::cast<llvm::FunctionType>(
+            callee->getType()->getPointerElementType()),
+        callee, args, name, fp_math_tag);
   }
 
   template <class... Args>

third_party/mlir/BUILD

@@ -2666,6 +2666,20 @@ cc_binary(
     ],
 )
 
+cc_binary(
+    name = "mlir-linalg-ods-gen",
+    srcs = glob([
+        "tools/mlir-linalg-ods-gen/mlir-linalg-ods-gen.cpp",
+    ]),
+    deps = [
+        ":IR",
+        ":Support",
+        "@llvm-project//llvm:config",
+        "@llvm-project//llvm:support",
+        "@llvm-project//llvm:tablegen",
+    ],
+)
+
 ## OpenMP dialect
 gentbl(
     name = "OpenMPOpsIncGen",