1/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2
3Licensed under the Apache License, Version 2.0 (the "License");
4you may not use this file except in compliance with the License.
5You may obtain a copy of the License at
6
7    http://www.apache.org/licenses/LICENSE-2.0
8
9Unless required by applicable law or agreed to in writing, software
10distributed under the License is distributed on an "AS IS" BASIS,
11WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12See the License for the specific language governing permissions and
13limitations under the License.
14==============================================================================*/
15
16#include "tensorflow/compiler/xla/service/local_service.h"
17
18#include <string>
19#include <utility>
20#include <vector>
21
22#include "tensorflow/compiler/xla/client/executable_build_options.h"
23#include "tensorflow/compiler/xla/execution_options_util.h"
24#include "tensorflow/compiler/xla/ptr_util.h"
25#include "tensorflow/compiler/xla/service/backend.h"
26#include "tensorflow/compiler/xla/service/computation_layout.h"
27#include "tensorflow/compiler/xla/service/computation_tracker.h"
28#include "tensorflow/compiler/xla/service/executable.h"
29#include "tensorflow/compiler/xla/service/hlo_computation.h"
30#include "tensorflow/compiler/xla/service/hlo_execution_profile.h"
31#include "tensorflow/compiler/xla/service/hlo_module.h"
32#include "tensorflow/compiler/xla/service/hlo_module_config.h"
33#include "tensorflow/compiler/xla/service/platform_util.h"
34#include "tensorflow/compiler/xla/service/user_computation.h"
35#include "tensorflow/compiler/xla/service/versioned_computation_handle.h"
36#include "tensorflow/compiler/xla/shape_layout.h"
37#include "tensorflow/compiler/xla/shape_util.h"
38#include "tensorflow/compiler/xla/status_macros.h"
39#include "tensorflow/compiler/xla/types.h"
40#include "tensorflow/compiler/xla/util.h"
41#include "tensorflow/core/lib/gtl/cleanup.h"
42#include "tensorflow/core/lib/strings/strcat.h"
43#include "tensorflow/core/platform/logging.h"
44#include "tensorflow/core/platform/stream_executor_no_cuda.h"
45
46namespace se = ::perftools::gputools;
47
48namespace xla {
49
50/* static */ StatusOr<std::unique_ptr<LocalService>> LocalService::NewService(
51    const ServiceOptions& options) {
52  perftools::gputools::Platform* platform = options.platform();
53  if (platform == nullptr) {
54    TF_ASSIGN_OR_RETURN(platform, PlatformUtil::GetDefaultPlatform());
55  }
56
57  BackendOptions backend_options;
58  backend_options.set_platform(platform).set_intra_op_parallelism_threads(
59      options.intra_op_parallelism_threads());
60  TF_ASSIGN_OR_RETURN(std::unique_ptr<Backend> backend,
61                      Backend::CreateBackend(backend_options));
62
63  std::unique_ptr<LocalService> service(
64      new LocalService(options, std::move(backend)));
65  return std::move(service);
66}
67
68LocalService::LocalService(const ServiceOptions& options,
69                           std::unique_ptr<Backend> execute_backend)
70    : Service(options, std::move(execute_backend)) {}
71
72StatusOr<std::unique_ptr<Executable>> LocalService::CompileExecutable(
73    const ComputationHandle& computation,
74    const tensorflow::gtl::ArraySlice<const Shape*> argument_layouts,
75    const ExecutableBuildOptions& build_options) {
76  TF_ASSIGN_OR_RETURN(UserComputation * user_computation,
77                      computation_tracker_.Resolve(computation));
78  VersionedComputationHandle versioned_handle =
79      user_computation->GetVersionedHandle();
80
81  TF_ASSIGN_OR_RETURN(
82      std::shared_ptr<const ProgramShape> program_shape,
83      user_computation->ComputeProgramShape(versioned_handle.version));
84
85  // Validate incoming layouts.
86  if (argument_layouts.size() != program_shape->parameters_size()) {
87    return InvalidArgument(
88        "Invalid number of arguments for computation: expected %d, got %zu.",
89        program_shape->parameters_size(), argument_layouts.size());
90  }
91  for (int i = 0; i < argument_layouts.size(); ++i) {
92    const Shape& argument_shape = *argument_layouts[i];
93    TF_RETURN_IF_ERROR(ShapeUtil::ValidateShape(argument_shape));
94    if (!ShapeUtil::Compatible(argument_shape, program_shape->parameters(i))) {
95      tensorflow::gtl::optional<const OpMetadata*> metadata =
96          user_computation->ParameterMetadata(i);
97      auto metadata_string = [&metadata]() -> string {
98        if (!metadata.has_value()) {
99          return "";
100        }
101        CHECK(metadata.value() != nullptr);
102        const OpMetadata& m = *metadata.value();
103        if (!m.source_file().empty()) {
104          return tensorflow::strings::Printf(
105              " (%s:%d)", m.source_file().c_str(), m.source_line());
106        }
107        return "";
108      };
109      return InvalidArgument(
110          "Invalid argument shape for argument %d%s, expected %s, got %s.", i,
111          metadata_string().c_str(),
112          ShapeUtil::HumanString(program_shape->parameters(i)).c_str(),
113          ShapeUtil::HumanString(argument_shape).c_str());
114    }
115  }
116  if (build_options.result_layout() != nullptr) {
117    TF_RETURN_IF_ERROR(ValidateResultShapeWithLayout(
118        *build_options.result_layout(), program_shape->result()));
119  }
120
121  ExecutionOptions execution_options = CreateDefaultExecutionOptions();
122  if (build_options.generate_hlo_graph().has_value()) {
123    execution_options.mutable_debug_options()->set_xla_generate_hlo_graph(
124        build_options.generate_hlo_graph().value());
125  }
126  if (build_options.result_layout() != nullptr) {
127    *execution_options.mutable_shape_with_output_layout() =
128        *build_options.result_layout();
129  } else {
130    *execution_options.mutable_shape_with_output_layout() =
131        program_shape->result();
132    LayoutUtil::SetToDefaultLayout(
133        execution_options.mutable_shape_with_output_layout());
134  }
135  TF_ASSIGN_OR_RETURN(
136      std::unique_ptr<HloModuleConfig> module_config,
137      CreateModuleConfig(*program_shape, argument_layouts, &execution_options,
138                         *user_computation));
139
140  TF_ASSIGN_OR_RETURN(
141      se::StreamExecutor * executor,
142      execute_backend_->stream_executor(build_options.device_ordinal()));
143
144  return BuildExecutable(versioned_handle, std::move(module_config),
145                         execute_backend_.get(), executor,
146                         build_options.device_allocator());
147}
148
149StatusOr<int> LocalService::ReplicaNumberToDeviceOrdinal(int replica_number) {
150  return backend().computation_placer()->DeviceId(
151      replica_number, /*computation=*/0, options_.number_of_replicas(),
152      /*computation_count=*/1);
153}
154
155}  // namespace xla
156