Lower tf.OutfeedEnqueueTuple op to XLA HLO.

OutfeedEnqueueTuple is lowered to HLO tuple, after_all and outfeed ops. after_all op is emitted to generate XLA token required by outfeed op.

PiperOrigin-RevId: 288399352
Change-Id: If56424b044e631f64837b39c8758dce9999ed4ab

tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td

@@ -3919,6 +3919,21 @@ output =
   }];
 }
 
+def TF_OutfeedEnqueueTupleOp : TF_Op<"OutfeedEnqueueTuple", []> {
+  let summary = "Enqueue multiple Tensor values on the computation outfeed.";
+
+  let description = [{
+  }];
+
+  let arguments = (ins
+    Variadic<TF_Tensor>:$inputs
+  );
+
+  let results = (outs);
+
+  TF_DerivedOperandTypeListAttr dtypes = TF_DerivedOperandTypeListAttr<0>;
+}
+
 def TF_PackOp : TF_Op<"Pack", [NoSideEffect]> {
   let summary = [{
 Packs a list of `N` rank-`R` tensors into one rank-`(R+1)` tensor.

tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir

@@ -1253,6 +1253,20 @@ func @one_hot(%indices: tensor<3xi32>, %on_value: tensor<f32>, %off_value: tenso
   return %result : tensor<3x5xf32>
 }
 
+//===----------------------------------------------------------------------===//
+// tf.OutfeedEnqueueTuple legalization
+//===----------------------------------------------------------------------===//
+
+// CHECK-LABEL: func @outfeed_enqueue_tuple
+// CHECK-SAME: [[VAL_0:%.*]]: tensor<3xi32>, [[VAL_1:%.*]]: tensor<4xf32>)
+func @outfeed_enqueue_tuple(%data_1: tensor<3xi32>, %data_2: tensor<4xf32>) -> () {
+// CHECK: [[TUPLE:%.*]] = "xla_hlo.tuple"([[VAL_0]], [[VAL_1]]) : (tensor<3xi32>, tensor<4xf32>) -> tuple<tensor<3xi32>, tensor<4xf32>>
+// CHECK: [[AFTER_ALL:%.*]] = "xla_hlo.after_all"() : () -> !xla_hlo.token
+// CHECK: "xla_hlo.outfeed"([[TUPLE]], [[AFTER_ALL]]) {outfeed_config = ""} : (tuple<tensor<3xi32>, tensor<4xf32>>, !xla_hlo.token) -> !xla_hlo.token
+  "tf.OutfeedEnqueueTuple"(%data_1, %data_2) : (tensor<3xi32>, tensor<4xf32>) -> ()
+  return
+}
+
 //===----------------------------------------------------------------------===//
 // Pack op legalizations.
 //===----------------------------------------------------------------------===//

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

@@ -2480,6 +2480,41 @@ class ConvertOneHotOp : public OpRewritePattern<TF::OneHotOp> {
   }
 };
 
+// Converts tf.OutfeedEnqueueTuple to XLA HLO tuple, after_all and outfeed ops.
+//
+// XLA HLO outfeed op expects a token, which we generate by emitting an
+// after_all op.
+//
+// For example the following IR:
+// "tf.OutfeedEnqueueTuple"(%val_1, %val_2) : (tensor<3xi32>, tensor<4xf32>) ->
+//      ()
+//
+// would be lowered to
+//
+// %tuple = "xla_hlo.tuple"(%val_1, %val_2) : (tensor<3xi32>, tensor<4xf32>) ->
+//      tuple<tensor<3xi32>, tensor<4xf32>>
+// %token = "xla_hlo.after_all"() : () -> !xla_hlo.token
+// %outfeed_token = "xla_hlo.outfeed"(%tuple, %token) {outfeed_config = ""} :
+//      (tuple<tensor<3xi32>, tensor<4xf32>>, !xla_hlo.token) -> !xla_hlo.token
+//
+class ConvertOutfeedEnqueueTupleOp
+    : public OpRewritePattern<TF::OutfeedEnqueueTupleOp> {
+ public:
+  using OpRewritePattern::OpRewritePattern;
+
+  PatternMatchResult matchAndRewrite(TF::OutfeedEnqueueTupleOp op,
+                                     PatternRewriter &rewriter) const override {
+    auto token_type = xla_hlo::TokenType::get(rewriter.getContext());
+    auto tuple = rewriter.create<TupleOp>(op.getLoc(), op.inputs());
+    auto afterall =
+        rewriter.create<AfterAllOp>(op.getLoc(), token_type, ValueRange());
+    rewriter.create<OutfeedOp>(op.getLoc(), token_type, tuple, afterall,
+                               /*outfeed_config=*/rewriter.getStringAttr(""));
+    rewriter.eraseOp(op);
+    return matchSuccess();
+  }
+};
+
 // Converts tf.TopKV2 to XLA HLO iota, sort, and slice ops when k is a constant.
 //
 // tf.TopKV2 sorts along last dimension of the input tensor and then returns
@@ -2770,8 +2805,8 @@ LogicalResult legalizeTF(Operation *op, bool allow_partial_conversion) {
       ConvertFusedBatchNormGradOp, ConvertFusedBatchNormGradV2Op,
       ConvertFusedBatchNormGradV3Op, ConvertFusedBatchNormV3Op, ConvertMaxOp,
       ConvertMaxPoolOp, ConvertMaxPoolGradOp, ConvertMeanOp, ConvertOneHotOp,
-      ConvertRangeOp, ConvertSigmoidOp, ConvertSizeOp,
-      ConvertSoftmaxOp<TF::LogSoftmaxOp, true>,
+      ConvertOutfeedEnqueueTupleOp, ConvertRangeOp, ConvertSigmoidOp,
+      ConvertSizeOp, ConvertSoftmaxOp<TF::LogSoftmaxOp, true>,
       ConvertSoftmaxOp<TF::SoftmaxOp, false>, ConvertSplitOp, ConvertSplitVOp,
       ConvertStridedSliceOp, ConvertStridedSliceGradOp, ConvertSumOp,
       ConvertTensorScatterUpdateOp, ConvertTileOp, ConvertTopKV2Op,