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
182
183
184
185
186
187
188
189
|
/* Copyright 2018 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/hlo_element_type_converter.h"
#include "tensorflow/compiler/xla/service/hlo_matchers.h"
#include "tensorflow/compiler/xla/tests/hlo_test_base.h"
namespace xla {
namespace {
namespace op = xla::testing::opcode_matchers;
using ::testing::Contains;
using ::testing::ElementsAre;
using ::testing::Eq;
using ::testing::Not;
using ::testing::ResultOf;
class HloElementTypeConverterTest : public HloTestBase {
public:
std::unique_ptr<HloModule> CreateModuleFromHloString(
const string& hlo_string) {
return HloRunner::CreateModuleFromString(hlo_string,
GetDebugOptionsForTest())
.ValueOrDie();
}
};
TEST_F(HloElementTypeConverterTest, CustomCallsNotConverted) {
const string& hlo_string = R"(
HloModule custom_call
ENTRY CustomCall {
constant = bf16[1]{0} constant({12345})
ROOT custom-call = bf16[1,2,3]{0,2,1} custom-call(constant),
custom_call_target="foo"
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_FALSE(converted);
}
TEST_F(HloElementTypeConverterTest, InfeedsOutfeedsNotConverted) {
const string& hlo_string = R"(
HloModule InfeedOutfeed
ENTRY RoundTrip16MiBR1.v2 {
token = token[] after-all()
infeed = (bf16[4]{0}, token[]) infeed(token)
ROOT infeed.data = bf16[4]{0} get-tuple-element(infeed), index=0
outfeed = token[] outfeed(infeed.data, token)
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_FALSE(converted);
}
TEST_F(HloElementTypeConverterTest, OperationsInNestedTuplesConverted) {
const string& hlo_string = R"(
HloModule NestedTuples
ENTRY NestedTuples.v5 {
constant.4 = bf16[] constant(42)
constant.2 = f32[2]{0} constant({1, 2})
constant.3 = bf16[] constant(42)
add = bf16[] add(constant.2, constant.3)
tuple = (f32[2]{0}, bf16[]) tuple(constant.2, add)
constant.5 = bf16[2]{0} constant({22, 44})
ROOT tuple.1 = ((f32[2]{0}, bf16[]), bf16[2]{0}) tuple(tuple, constant.5)
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_TRUE(converted);
const HloInstruction* bf16_op =
module->entry_computation()->root_instruction()->operand(0)->operand(1);
EXPECT_THAT(bf16_op, op::Convert(op::Add(op::Constant(), op::Convert())));
}
TEST_F(HloElementTypeConverterTest, BatchNormGradBF16Converted) {
const string& hlo_string = R"(
HloModule BatchNormGrad
ENTRY BatchNormGrad.v6 {
constant.4 = bf16[2,2,2,1]{3,2,1,0} constant(bf16[2,2,2,1] { { /*i0=0*/
{ /*i1=0*/ {0}, {0} }, { /*i1=1*/ {0}, {0} } }, { /*i0=1*/ { /*i1=0*/ {0},
{0} }, { /*i1=1*/ {0}, {0} } } })
constant.5 = bf16[2]{0} constant({1, 1})
constant.6 = bf16[2]{0} constant({0, 0})
constant.7 = bf16[2]{0} constant({1, 1})
constant.8 = bf16[2,2,2,1]{3,2,1,0} constant(bf16[2,2,2,1] { { /*i0=0*/
{ /*i1=0*/ {1}, {2} }, { /*i1=1*/ {3}, {4} } }, { /*i0=1*/ { /*i1=0*/
{5}, {6} }, { /*i1=1*/ {7}, {8} } } })
ROOT batch-norm-grad = (bf16[2,2,2,1]{3,2,1,0}, bf16[2]{0}, bf16[2]{0})
batch-norm-grad(constant.4, constant.5, constant.6, constant.7,
constant.8), epsilon=0, feature_index=2
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_TRUE(converted);
const HloInstruction* tuple_instr =
module->entry_computation()->root_instruction();
::testing::Matcher<const ::xla::HloInstruction*> batch_norm =
op::BatchNormGrad();
EXPECT_THAT(tuple_instr,
op::Tuple(op::Convert(op::GetTupleElement(batch_norm, 0)),
op::Convert(op::GetTupleElement(batch_norm, 1)),
op::Convert(op::GetTupleElement(batch_norm, 2))));
}
TEST_F(HloElementTypeConverterTest, RngIsRemoved) {
const string& hlo_string = R"(
HloModule RngIsRemoved
ENTRY main {
constant.3 = bf16[] constant(0)
constant.4 = bf16[] constant(1)
ROOT rng = bf16[1,1000,20]{2,1,0} rng(constant.3, constant.4), distribution=rng_uniform
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_TRUE(converted);
std::function<bool(const HloInstruction*)> is_bf16_rng =
[](const HloInstruction* inst) {
return inst->shape().element_type() == BF16 &&
inst->opcode() == HloOpcode::kRng;
};
EXPECT_THAT(module->entry_computation()->instructions(),
Not(Contains(ResultOf(is_bf16_rng, Eq(true)))));
}
TEST_F(HloElementTypeConverterTest, RngCtrlDep) {
const string& hlo_string = R"(
HloModule RngIsRemoved
ENTRY main {
constant.3 = bf16[] constant(0)
constant.4 = bf16[] constant(1)
rng0 = bf16[1,2000,20]{2,1,0} rng(constant.3, constant.4), distribution=rng_uniform
ROOT rng1 = bf16[1,1000,20]{2,1,0} rng(constant.3, constant.4), control-predecessors={%rng0}, distribution=rng_uniform
}
)";
auto module = CreateModuleFromHloString(hlo_string);
HloElementTypeConverter type_converter(BF16, F32);
TF_ASSERT_OK_AND_ASSIGN(bool converted, type_converter.Run(module.get()));
EXPECT_TRUE(converted);
HloInstruction *rng0, *rng1;
for (auto* inst : module->entry_computation()->instructions()) {
if (inst->opcode() == HloOpcode::kRng) {
const Shape& shape = inst->shape();
ASSERT_EQ(shape.dimensions_size(), 3);
ASSERT_TRUE(shape.dimensions(1) == 2000 || shape.dimensions(1) == 1000);
if (shape.dimensions(1) == 2000) {
rng0 = inst;
} else {
rng1 = inst;
}
}
}
EXPECT_THAT(rng0->control_successors(), ElementsAre(rng1));
EXPECT_THAT(rng1->control_predecessors(), ElementsAre(rng0));
}
} // namespace
} // namespace xla
|
