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      1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
      2 
      3 Licensed under the Apache License, Version 2.0 (the "License");
      4 you may not use this file except in compliance with the License.
      5 You may obtain a copy of the License at
      6 
      7     http://www.apache.org/licenses/LICENSE-2.0
      8 
      9 Unless required by applicable law or agreed to in writing, software
     10 distributed under the License is distributed on an "AS IS" BASIS,
     11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 See the License for the specific language governing permissions and
     13 limitations under the License.
     14 ==============================================================================*/
     15 
     16 #include "tensorflow/compiler/xla/client/lib/arithmetic.h"
     17 
     18 #include <string>
     19 
     20 #include "tensorflow/compiler/xla/client/computation_builder.h"
     21 #include "tensorflow/compiler/xla/shape_util.h"
     22 #include "tensorflow/compiler/xla/status_macros.h"
     23 #include "tensorflow/compiler/xla/types.h"
     24 #include "tensorflow/compiler/xla/xla_data.pb.h"
     25 #include "tensorflow/core/lib/strings/strcat.h"
     26 
     27 namespace xla {
     28 namespace {
     29 using InstructionGenerator =
     30     ComputationDataHandle (*)(ComputationBuilder*, const ComputationDataHandle&,
     31                               const ComputationDataHandle&);
     32 
     33 Computation CreateScalarComputation(const string& name, PrimitiveType type,
     34                                     ComputationBuilder* builder,
     35                                     InstructionGenerator generator) {
     36   std::unique_ptr<ComputationBuilder> b;
     37   if (type == PRED) {
     38     b = builder->CreateSubBuilder(name);
     39   } else {
     40     b = builder->CreateSubBuilder(
     41         tensorflow::strings::StrCat(name, "_", PrimitiveType_Name(type)));
     42   }
     43 
     44   const Shape scalar = ShapeUtil::MakeShape(type, {});
     45   auto lhs = b->Parameter(0, scalar, "lhs");
     46   auto rhs = b->Parameter(1, scalar, "rhs");
     47   generator(b.get(), lhs, rhs);
     48   return b->BuildAndNoteError();
     49 }
     50 }  // namespace
     51 
     52 Computation CreateScalarAddComputation(PrimitiveType type,
     53                                        ComputationBuilder* builder) {
     54   return CreateScalarComputation(
     55       "add", type, builder,
     56       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     57          const ComputationDataHandle& rhs) { return b->Add(lhs, rhs); });
     58 }
     59 
     60 Computation CreateScalarMultiplyComputation(PrimitiveType type,
     61                                             ComputationBuilder* builder) {
     62   return CreateScalarComputation(
     63       "add", type, builder,
     64       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     65          const ComputationDataHandle& rhs) { return b->Mul(lhs, rhs); });
     66 }
     67 
     68 Computation CreateScalarGeComputation(PrimitiveType type,
     69                                       ComputationBuilder* builder) {
     70   return CreateScalarComputation(
     71       "ge", type, builder,
     72       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     73          const ComputationDataHandle& rhs) { return b->Ge(lhs, rhs); });
     74 }
     75 
     76 Computation CreateScalarMaxComputation(PrimitiveType type,
     77                                        ComputationBuilder* builder) {
     78   return CreateScalarComputation(
     79       "max", type, builder,
     80       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     81          const ComputationDataHandle& rhs) { return b->Max(lhs, rhs); });
     82 }
     83 
     84 Computation CreateScalarMinComputation(PrimitiveType type,
     85                                        ComputationBuilder* builder) {
     86   return CreateScalarComputation(
     87       "min", type, builder,
     88       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     89          const ComputationDataHandle& rhs) { return b->Min(lhs, rhs); });
     90 }
     91 
     92 Computation CreateScalarAndComputation(ComputationBuilder* builder) {
     93   return CreateScalarComputation(
     94       "and", PRED, builder,
     95       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
     96          const ComputationDataHandle& rhs) { return b->And(lhs, rhs); });
     97 }
     98 
     99 Computation CreateScalarOrComputation(ComputationBuilder* builder) {
    100   return CreateScalarComputation(
    101       "or", PRED, builder,
    102       [](ComputationBuilder* b, const ComputationDataHandle& lhs,
    103          const ComputationDataHandle& rhs) { return b->Or(lhs, rhs); });
    104 }
    105 
    106 StatusOr<ComputationDataHandle> Any(const ComputationDataHandle& predicates,
    107                                     ComputationBuilder* builder) {
    108   auto f = builder->ConstantR0<bool>(false);
    109   Computation logical_or = CreateScalarOrComputation(builder);
    110   TF_ASSIGN_OR_RETURN(std::unique_ptr<Shape> predicates_shape,
    111                       builder->GetShape(predicates));
    112   std::vector<int64> all_dimensions(ShapeUtil::Rank(*predicates_shape));
    113   std::iota(all_dimensions.begin(), all_dimensions.end(), 0);
    114   return builder->Reduce(predicates, f, logical_or, all_dimensions);
    115 }
    116 
    117 }  // namespace xla
    118