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/service/batchnorm_expander.h" 17 18 #include <memory> 19 #include <utility> 20 21 #include "tensorflow/compiler/xla/layout_util.h" 22 #include "tensorflow/compiler/xla/literal_util.h" 23 #include "tensorflow/compiler/xla/ptr_util.h" 24 #include "tensorflow/compiler/xla/service/hlo_computation.h" 25 #include "tensorflow/compiler/xla/service/hlo_instruction.h" 26 #include "tensorflow/compiler/xla/service/hlo_matchers.h" 27 #include "tensorflow/compiler/xla/service/hlo_opcode.h" 28 #include "tensorflow/compiler/xla/service/hlo_pass_fix.h" 29 #include "tensorflow/compiler/xla/shape_util.h" 30 #include "tensorflow/compiler/xla/test.h" 31 #include "tensorflow/compiler/xla/tests/hlo_test_base.h" 32 #include "tensorflow/compiler/xla/types.h" 33 #include "tensorflow/compiler/xla/xla_data.pb.h" 34 #include "tensorflow/core/lib/strings/str_util.h" 35 36 namespace xla { 37 namespace { 38 39 using BatchNormExpanderTest = HloTestBase; 40 41 // Test that we expand BatchNormTraining. 42 TEST_F(BatchNormExpanderTest, BatchNormTraining) { 43 Shape input_shape = ShapeUtil::MakeShape(F32, {2, 2, 2, 2}); 44 Shape scale_shape = ShapeUtil::MakeShape(F32, {2}); 45 Shape offset_shape = ShapeUtil::MakeShape(F32, {2}); 46 47 HloComputation::Builder builder(TestName()); 48 HloInstruction* param0 = builder.AddInstruction( 49 HloInstruction::CreateParameter(0, input_shape, "activiation")); 50 51 HloInstruction* param1 = builder.AddInstruction( 52 HloInstruction::CreateParameter(1, scale_shape, "scale")); 53 54 HloInstruction* param2 = builder.AddInstruction( 55 HloInstruction::CreateParameter(2, offset_shape, "offset")); 56 57 builder.AddInstruction(HloInstruction::CreateBatchNormTraining( 58 ShapeUtil::MakeTupleShape({input_shape, scale_shape, offset_shape}), 59 param0, param1, param2, 60 /*epsilon=*/0.001, /*feature_index=*/3)); 61 62 auto module = CreateNewModule(); 63 auto computation = module->AddEntryComputation(builder.Build()); 64 HloInstruction* root = computation->root_instruction(); 65 EXPECT_EQ(root->opcode(), HloOpcode::kBatchNormTraining); 66 BatchNormExpander rewriter(/*rewrite_training_op=*/true, 67 /*rewrite_inference_op=*/true, 68 /*rewrite_grad_op=*/true); 69 ASSERT_TRUE(rewriter.Run(module.get()).ValueOrDie()); 70 root = computation->root_instruction(); 71 // Make sure this operation is expanded. 72 EXPECT_EQ(root->opcode(), HloOpcode::kTuple); 73 } 74 75 // Test that we expand BatchNormGrad. 76 TEST_F(BatchNormExpanderTest, BatchNormGrad) { 77 Shape input_shape = ShapeUtil::MakeShape(F32, {2, 2, 2, 2}); 78 Shape scale_shape = ShapeUtil::MakeShape(F32, {2}); 79 Shape mean_shape = ShapeUtil::MakeShape(F32, {2}); 80 Shape var_shape = ShapeUtil::MakeShape(F32, {2}); 81 Shape grad_output_shape = ShapeUtil::MakeShape(F32, {2, 2, 2, 2}); 82 83 HloComputation::Builder builder(TestName()); 84 HloInstruction* param0 = builder.AddInstruction( 85 HloInstruction::CreateParameter(0, input_shape, "activation")); 86 87 HloInstruction* param1 = builder.AddInstruction( 88 HloInstruction::CreateParameter(1, scale_shape, "scale")); 89 90 HloInstruction* param2 = builder.AddInstruction( 91 HloInstruction::CreateParameter(2, mean_shape, "mean")); 92 93 HloInstruction* param3 = builder.AddInstruction( 94 HloInstruction::CreateParameter(3, var_shape, "var")); 95 96 HloInstruction* param4 = builder.AddInstruction( 97 HloInstruction::CreateParameter(4, grad_output_shape, "grad_output")); 98 99 builder.AddInstruction(HloInstruction::CreateBatchNormGrad( 100 ShapeUtil::MakeTupleShape({input_shape, scale_shape, mean_shape}), param0, 101 param1, param2, param3, param4, 102 /*epsilon=*/0.001, /*feature_index=*/3)); 103 104 auto module = CreateNewModule(); 105 auto computation = module->AddEntryComputation(builder.Build()); 106 HloInstruction* root = computation->root_instruction(); 107 EXPECT_EQ(root->opcode(), HloOpcode::kBatchNormGrad); 108 BatchNormExpander rewriter(/*rewrite_training_op=*/true, 109 /*rewrite_inference_op=*/true, 110 /*rewrite_grad_op=*/true); 111 ASSERT_TRUE(rewriter.Run(module.get()).ValueOrDie()); 112 root = computation->root_instruction(); 113 // Make sure this operation is expanded. 114 EXPECT_EQ(root->opcode(), HloOpcode::kTuple); 115 } 116 117 } // namespace 118 } // namespace xla 119
