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 <stdio.h>
17#include <memory>
18#include <string>
19
20#include "tensorflow/compiler/xla/client/client.h"
21#include "tensorflow/compiler/xla/client/client_library.h"
22#include "tensorflow/compiler/xla/client/computation.h"
23#include "tensorflow/compiler/xla/client/local_client.h"
24#include "tensorflow/compiler/xla/service/computation_tracker.h"
25#include "tensorflow/compiler/xla/service/service.h"
26#include "tensorflow/compiler/xla/service/session.pb.h"
27#include "tensorflow/compiler/xla/statusor.h"
28#include "tensorflow/compiler/xla/types.h"
29#include "tensorflow/compiler/xla/xla_data.pb.h"
30#include "tensorflow/core/lib/gtl/array_slice.h"
31#include "tensorflow/core/platform/env.h"
32#include "tensorflow/core/platform/init_main.h"
33#include "tensorflow/core/platform/logging.h"
34
35namespace xla {
36namespace tools {
37
38void RealMain(tensorflow::gtl::ArraySlice<char*> args, bool compile) {
39  LocalClient* client = ClientLibrary::LocalClientOrDie();
40  LocalService* local_service =
41      ClientLibrary::GetXlaService(client->platform());
42  for (char* arg : args) {
43    SessionModule session_module;
44    TF_CHECK_OK(tensorflow::ReadBinaryProto(tensorflow::Env::Default(), arg,
45                                            &session_module));
46    auto computation_status = client->LoadSnapshot(session_module);
47    if (!computation_status.ok()) {
48      fprintf(stderr, "could not load snapshot for %s: %s\n", arg,
49              computation_status.status().ToString().c_str());
50      continue;
51    }
52    Computation computation = computation_status.ConsumeValueOrDie();
53
54    if (compile) {
55      std::unique_ptr<ProgramShape> program_shape =
56          client->GetComputationShape(computation).ConsumeValueOrDie();
57
58      std::vector<const Shape*> layouts;
59      layouts.reserve(program_shape->parameters_size());
60      for (int i = 0; i < program_shape->parameters_size(); ++i) {
61        layouts.push_back(&program_shape->parameters(i));
62      }
63
64      ExecutableBuildOptions build_options;
65      build_options.set_device_ordinal(0);
66      build_options.set_result_layout(program_shape->result());
67      StatusOr<std::unique_ptr<Executable>> executable =
68          local_service->CompileExecutable(computation.handle(), layouts,
69                                           build_options);
70
71      const HloModule& module = executable.ValueOrDie()->module();
72
73      fprintf(stdout, "HLO compiled for %s backend:\n%s\n",
74              local_service->backend().platform()->Name().c_str(),
75              module.ToString(HloPrintOptions::ShortParsable()).c_str());
76    } else {
77      const ComputationTracker& tracker = local_service->computation_tracker();
78      UserComputation* user_computation =
79          tracker.Resolve(computation.handle()).ConsumeValueOrDie();
80      VersionedComputationHandle versioned_handle =
81          user_computation->GetVersionedHandle();
82      std::unique_ptr<HloModule> module =
83          tracker.BuildHloModule(versioned_handle, HloModuleConfig())
84              .ConsumeValueOrDie();
85
86      fprintf(stdout, "%s\n",
87              module->ToString(HloPrintOptions::ShortParsable()).c_str());
88    }
89  }
90}
91
92}  // namespace tools
93}  // namespace xla
94
95int main(int argc, char** argv) {
96  bool compile = false;
97  std::vector<tensorflow::Flag> flag_list = {
98      {"compile", &compile,
99       "If true, compile the computation using the default client before "
100       "dumping the HLO. Otherwise dump the raw (uncompiled) HLO."},
101  };
102  const xla::string usage = tensorflow::Flags::Usage(argv[0], flag_list);
103  bool parsed_flags_ok = tensorflow::Flags::Parse(&argc, argv, flag_list);
104  QCHECK(parsed_flags_ok) << "\n" << usage;
105
106  tensorflow::port::InitMain(usage.c_str(), &argc, &argv);
107  QCHECK(argc > 1) << "\nERROR: must specify at least one module\n" << usage;
108
109  tensorflow::gtl::ArraySlice<char*> args(argv, argc);
110  args.pop_front();  // Pop off the binary name, argv[0]
111  xla::tools::RealMain(args, compile);
112  return 0;
113}
114