1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
|
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#include "tensorflow/compiler/xla/service/map_inliner.h"
#include <memory>
#include <utility>
#include "absl/memory/memory.h"
#include "tensorflow/compiler/xla/literal.h"
#include "tensorflow/compiler/xla/service/hlo_computation.h"
#include "tensorflow/compiler/xla/service/hlo_instruction.h"
#include "tensorflow/compiler/xla/service/hlo_matchers.h"
#include "tensorflow/compiler/xla/service/hlo_opcode.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/test.h"
#include "tensorflow/compiler/xla/tests/hlo_verified_test_base.h"
#include "tensorflow/compiler/xla/tests/literal_test_util.h"
#include "tensorflow/compiler/xla/xla_data.pb.h"
namespace op = xla::testing::opcode_matchers;
namespace xla {
namespace {
using MapInlinerTest = HloVerifiedTestBase;
// Test that `map` with `max` is transformed to `max`
TEST_F(MapInlinerTest, MapMax) {
Shape r0f32 = ShapeUtil::MakeShape(F32, {});
auto max_builder = HloComputation::Builder(TestName());
auto param1 = max_builder.AddInstruction(
HloInstruction::CreateParameter(0, r0f32, "x"));
auto param2 = max_builder.AddInstruction(
HloInstruction::CreateParameter(1, r0f32, "y"));
max_builder.AddInstruction(HloInstruction::CreateBinary(
param1->shape(), HloOpcode::kMaximum, param1, param2));
auto max_f32 = max_builder.Build();
auto builder = HloComputation::Builder("MapMaxFunction");
auto lhs = builder.AddInstruction(HloInstruction::CreateConstant(
LiteralUtil::CreateR1<float>({1, 2, 3, 4})));
auto rhs = builder.AddInstruction(HloInstruction::CreateConstant(
LiteralUtil::CreateR1<float>({4, 3, 2, 1})));
builder.AddInstruction(
HloInstruction::CreateMap(lhs->shape(), {lhs, rhs}, max_f32.get()));
auto computation = builder.Build();
auto hlo_module = CreateNewModule();
hlo_module->AddEmbeddedComputation(std::move(max_f32));
hlo_module->AddEntryComputation(std::move(computation));
MapInliner inliner;
EXPECT_TRUE(inliner.Run(hlo_module).ValueOrDie());
EXPECT_THAT(hlo_module->entry_computation()->root_instruction(),
op::Maximum(lhs, rhs));
// Verify execution on CPU.
auto result = ExecuteAndTransfer(hlo_module->Clone(), {});
auto expected = LiteralUtil::CreateR1<float>({4, 3, 3, 4});
EXPECT_TRUE(LiteralTestUtil::Equal(result, expected));
}
// Test that `constant` function is changed to `broadcast`.
TEST_F(MapInlinerTest, MapConstant) {
Shape r0f32 = ShapeUtil::MakeShape(F32, {});
auto const2_builder = HloComputation::Builder(TestName());
auto param1 = const2_builder.AddInstruction(
HloInstruction::CreateParameter(0, r0f32, "x"));
(void)param1;
const2_builder.AddInstruction(
HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(2.0f)));
auto const2_f32 = const2_builder.Build();
auto builder = HloComputation::Builder("MapConstFunction");
auto lhs = builder.AddInstruction(HloInstruction::CreateConstant(
LiteralUtil::CreateR2<float>({{1, 2, 3, 4}, {5, 6, 7, 8}})));
builder.AddInstruction(
HloInstruction::CreateMap(lhs->shape(), {lhs}, const2_f32.get()));
auto computation = builder.Build();
auto hlo_module = CreateNewModule();
hlo_module->AddEmbeddedComputation(std::move(const2_f32));
hlo_module->AddEntryComputation(std::move(computation));
HloInstruction* root = hlo_module->entry_computation()->root_instruction();
MapInliner inliner;
EXPECT_TRUE(inliner.Run(hlo_module).ValueOrDie());
root = hlo_module->entry_computation()->root_instruction();
EXPECT_THAT(root, op::Broadcast(op::Constant()));
// Verify execution on CPU.
auto result = ExecuteAndTransfer(hlo_module->Clone(), {});
auto expected = LiteralUtil::CreateR2<float>({{2, 2, 2, 2}, {2, 2, 2, 2}});
EXPECT_TRUE(LiteralTestUtil::Equal(result, expected));
}
TEST_F(MapInlinerTest, MapSubtractOppositeOrder) {
Shape r0f32 = ShapeUtil::MakeShape(F32, {});
// Note that the parameter ordinals are in the opposite order to their
// position as operands
auto max_builder = HloComputation::Builder(TestName());
auto param1 = max_builder.AddInstruction(
HloInstruction::CreateParameter(1, r0f32, "x"));
auto param2 = max_builder.AddInstruction(
HloInstruction::CreateParameter(0, r0f32, "y"));
max_builder.AddInstruction(HloInstruction::CreateBinary(
param1->shape(), HloOpcode::kSubtract, param1, param2));
auto max_f32 = max_builder.Build();
auto builder = HloComputation::Builder("MapSubFunction");
auto lhs = builder.AddInstruction(HloInstruction::CreateConstant(
LiteralUtil::CreateR1<float>({1, 2, 3, 4})));
auto rhs = builder.AddInstruction(HloInstruction::CreateConstant(
LiteralUtil::CreateR1<float>({4, 3, 2, 1})));
builder.AddInstruction(
HloInstruction::CreateMap(lhs->shape(), {lhs, rhs}, max_f32.get()));
auto computation = builder.Build();
auto hlo_module = CreateNewModule();
hlo_module->AddEmbeddedComputation(std::move(max_f32));
hlo_module->AddEntryComputation(std::move(computation));
MapInliner inliner;
EXPECT_TRUE(inliner.Run(hlo_module).ValueOrDie());
EXPECT_THAT(hlo_module->entry_computation()->root_instruction(),
op::Subtract(rhs, lhs));
// Verify execution on CPU.
auto result = ExecuteAndTransfer(hlo_module->Clone(), {});
auto expected = LiteralUtil::CreateR1<float>({3, 1, -1, -3});
EXPECT_TRUE(LiteralTestUtil::Equal(result, expected));
}
TEST_F(MapInlinerTest, MapParameter) {
Shape r0f32 = ShapeUtil::MakeShape(F32, {});
auto param_builder = HloComputation::Builder(TestName());
param_builder.AddInstruction(HloInstruction::CreateParameter(0, r0f32, "p0"));
param_builder.AddInstruction(HloInstruction::CreateParameter(1, r0f32, "p1"));
auto param_f32 = param_builder.Build();
auto builder = HloComputation::Builder("MapParamFunction");
auto lhs = builder.AddInstruction(
HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(1)));
auto rhs = builder.AddInstruction(
HloInstruction::CreateConstant(LiteralUtil::CreateR0<float>(4)));
builder.AddInstruction(
HloInstruction::CreateMap(lhs->shape(), {lhs, rhs}, param_f32.get()));
auto computation = builder.Build();
auto hlo_module = CreateNewVerifiedModule();
hlo_module->AddEmbeddedComputation(std::move(param_f32));
hlo_module->AddEntryComputation(std::move(computation));
MapInliner inliner;
EXPECT_TRUE(inliner.Run(hlo_module.get()).ValueOrDie());
EXPECT_THAT(hlo_module->entry_computation()->root_instruction(), rhs);
// Verify execution on CPU.
auto result = ExecuteAndTransfer(hlo_module->Clone(), {});
auto expected = LiteralUtil::CreateR0<float>(4);
EXPECT_TRUE(LiteralTestUtil::Equal(result, expected));
}
} // namespace
} // namespace xla
|
