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Add xla_hlo xor op.

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PiperOrigin-RevId: 278982559
Change-Id: I2c5d67da57fb2d016c126ee4cd9a504cf72ae9ec
This commit is contained in:
Prakalp Srivastava 2019-11-06 18:18:23 -08:00 committed by TensorFlower Gardener
parent c684ce6b59
commit 4e9394c478
5 changed files with 35 additions and 1 deletions
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1
tensorflow/compiler/mlir/xla/hlo_function_importer.cc
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@ -465,6 +465,7 @@ StatusOr<mlir::Operation*> HloFunctionImporter::ImportInstruction(
NoAttributeCase(kSubtract, SubOp);
NoAttributeCase(kTanh, TanhOp);
NoAttributeCase(kTuple, TupleOp);
NoAttributeCase(kXor, XorOp);
// TODO(b/129422361) Copy needs special handling because it is not defined
// in tensorflow/compiler/xla/client/xla_builder.h.
// See operation semantics in

2
tensorflow/compiler/mlir/xla/ir/hlo_ops.td
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@ -249,7 +249,6 @@ def HLO_RemOp : HLO_BinaryElementwiseOp<"remainder",
def HLO_SubOp : HLO_BinaryElementwiseOp<"sub",
[NoSideEffect, SameOperandsAndResultElementType]>, BASE_HLO_SubOp;
//===----------------------------------------------------------------------===//
// XLA binary elementwise op definitions.
//===----------------------------------------------------------------------===//
@ -266,6 +265,7 @@ class HLO_BinaryLogicalElementwiseOp<string mnemonic> :
def HLO_AndOp: HLO_BinaryLogicalElementwiseOp<"and">, BASE_HLO_AndOp;
def HLO_OrOp: HLO_BinaryLogicalElementwiseOp<"or">, BASE_HLO_OrOp;
def HLO_XorOp : HLO_BinaryLogicalElementwiseOp<"xor">, BASE_HLO_XorOp;
//===----------------------------------------------------------------------===//
// XLA control flow op definitions.

11
tensorflow/compiler/mlir/xla/ir/hlo_ops_base.td
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@ -343,6 +343,17 @@ class BASE_HLO_OrOp {
}];
}
class BASE_HLO_XorOp {
string summary = "Logical xor";
string description = [{
Returns `lhs xor rhs` element-wise.
See
https://www.tensorflow.org/xla/operation_semantics#element-wise_binary_arithmetic_operations.
}];
}
class BASE_HLO_ReduceOp {
string summary = "Reduce operator";

11
tensorflow/compiler/mlir/xla/tests/translate/ops.hlotxt
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@ -621,3 +621,14 @@ ENTRY %dummy_main (Arg_0.1: f32[]) -> f32[] {
// CHECK-NEXT: return %0 : tensor<i64>
ROOT %while.2 = s64[] while(%arg0.1), body=%loop, condition=%cond
}
// CHECK-LABEL: func @test_xor
// CHECK-SAME: ([[VAL_0:%.*]]: tensor<4xi1>, [[VAL_1:%.*]]: tensor<4xi1>) -> tensor<4xi1>
%test_xor (Arg_0.1: pred[4], Arg_1.2: pred[4]) -> pred[4] {
%Arg_0.1 = pred[4] parameter(0)
%Arg_1.2 = pred[4] parameter(1)
// CHECK: [[VAL_2:%.*]] = xla_hlo.xor [[VAL_0]], [[VAL_1]]
// CHECK: return [[VAL_2]] : tensor<4xi1>
ROOT %xor.3 = pred[4] xor(pred[4] %Arg_0.1, pred[4] %Arg_1.2)
}

11
tensorflow/compiler/mlir/xla/tests/translate/xor.mlir Normal file
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@ -0,0 +1,11 @@
// RUN: tf-mlir-translate -mlir-hlo-to-hlo-text %s | FileCheck %s
module {
func @main(%arg0: tensor<4xi1>, %arg1: tensor<4xi1>) -> tensor<4xi1> {
// CHECK: [[VAL_1:%.*]] = pred[4] parameter(0)
// CHECK: [[VAL_2:%.*]] = pred[4] parameter(1)
%0 = xla_hlo.xor %arg0, %arg1 : tensor<4xi1>
// CHECK: ROOT [[VAL_3:%.*]] = pred[4] xor(pred[4] [[VAL_1]], pred[4] [[VAL_2]])
return %0 : tensor<4xi1>
}
}