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
|
/* 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/local_service.h"
#include <string>
#include <utility>
#include <vector>
#include "tensorflow/compiler/xla/execution_options_util.h"
#include "tensorflow/compiler/xla/ptr_util.h"
#include "tensorflow/compiler/xla/service/backend.h"
#include "tensorflow/compiler/xla/service/computation_layout.h"
#include "tensorflow/compiler/xla/service/computation_tracker.h"
#include "tensorflow/compiler/xla/service/executable.h"
#include "tensorflow/compiler/xla/service/hlo_computation.h"
#include "tensorflow/compiler/xla/service/hlo_execution_profile.h"
#include "tensorflow/compiler/xla/service/hlo_module.h"
#include "tensorflow/compiler/xla/service/hlo_module_config.h"
#include "tensorflow/compiler/xla/service/platform_util.h"
#include "tensorflow/compiler/xla/service/user_computation.h"
#include "tensorflow/compiler/xla/service/versioned_computation_handle.h"
#include "tensorflow/compiler/xla/shape_layout.h"
#include "tensorflow/compiler/xla/shape_util.h"
#include "tensorflow/compiler/xla/status_macros.h"
#include "tensorflow/compiler/xla/types.h"
#include "tensorflow/compiler/xla/util.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/lib/strings/strcat.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/stream_executor_no_cuda.h"
namespace se = ::perftools::gputools;
namespace xla {
/* static */ StatusOr<std::unique_ptr<LocalService>> LocalService::NewService(
const ServiceOptions& options) {
perftools::gputools::Platform* platform = options.platform();
if (platform == nullptr) {
TF_ASSIGN_OR_RETURN(platform, PlatformUtil::GetDefaultPlatform());
}
BackendOptions backend_options;
backend_options.set_platform(platform).set_intra_op_parallelism_threads(
options.intra_op_parallelism_threads());
TF_ASSIGN_OR_RETURN(std::unique_ptr<Backend> backend,
Backend::CreateBackend(backend_options));
std::unique_ptr<LocalService> service(
new LocalService(options, std::move(backend)));
return std::move(service);
}
LocalService::LocalService(const ServiceOptions& options,
std::unique_ptr<Backend> execute_backend)
: Service(options, std::move(execute_backend)) {}
namespace {
// Returns the space required to allocate a shape. If
// allocate_space_for_deep_copy the space includes all sub-buffers of
// a tuple.
int64 RequiredSpace(const Shape& shape, bool allocate_space_for_deep_copy,
TransferManager* transfer_manager) {
int64 size = 0;
// TODO(b/33492279) remove once no devices represent result tuples as
// contiguous buffers.
if (allocate_space_for_deep_copy) {
ShapeUtil::ForEachSubshape(
shape, [&size, transfer_manager](const Shape& subshape,
const ShapeIndex& /*index*/) {
size += transfer_manager->GetByteSizeRequirement(subshape);
});
}
return size;
}
} // namespace
StatusOr<std::unique_ptr<Executable>> LocalService::CompileExecutable(
const ComputationHandle& computation,
const tensorflow::gtl::ArraySlice<const Shape*> argument_layouts,
const Shape* result_layout, int device_ordinal) {
TF_ASSIGN_OR_RETURN(UserComputation * user_computation,
computation_tracker_.Resolve(computation));
VersionedComputationHandle versioned_handle =
user_computation->GetVersionedHandle();
TF_ASSIGN_OR_RETURN(
std::shared_ptr<const ProgramShape> program_shape,
user_computation->ComputeProgramShape(versioned_handle.version));
// Validate incoming layouts.
if (argument_layouts.size() != program_shape->parameters_size()) {
return InvalidArgument(
"invalid number of arguments for computation: expected %d, got %zu",
program_shape->parameters_size(), argument_layouts.size());
}
for (int i = 0; i < argument_layouts.size(); ++i) {
const Shape& argument_shape = *argument_layouts[i];
TF_RETURN_IF_ERROR(ShapeUtil::ValidateShape(argument_shape));
if (!ShapeUtil::Compatible(argument_shape, program_shape->parameters(i))) {
return InvalidArgument(
"invalid argument shape for argument %d, expected %s, got %s", i,
ShapeUtil::HumanString(program_shape->parameters(i)).c_str(),
ShapeUtil::HumanString(argument_shape).c_str());
}
}
if (result_layout != nullptr) {
TF_RETURN_IF_ERROR(
ValidateResultShapeWithLayout(*result_layout, program_shape->result()));
}
ExecutionOptions execution_options = CreateDefaultExecutionOptions();
if (result_layout != nullptr) {
*execution_options.mutable_shape_with_output_layout() = *result_layout;
} else {
*execution_options.mutable_shape_with_output_layout() =
program_shape->result();
LayoutUtil::SetToDefaultLayout(
execution_options.mutable_shape_with_output_layout());
}
TF_ASSIGN_OR_RETURN(
std::unique_ptr<HloModuleConfig> module_config,
CreateModuleConfig(*program_shape, argument_layouts, &execution_options));
TF_ASSIGN_OR_RETURN(se::StreamExecutor * executor,
execute_backend_->stream_executor(device_ordinal));
std::vector<perftools::gputools::DeviceMemoryBase> argument_buffers(
argument_layouts.size());
return BuildExecutable(versioned_handle, std::move(module_config),
argument_buffers, execute_backend_.get(), executor);
}
} // namespace xla
|
