1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #include "tensorflow/compiler/xla/service/hlo_pass_pipeline.h" 17 18 #include <functional> 19 20 #include "tensorflow/compiler/xla/service/hlo_graph_dumper.h" 21 #include "tensorflow/compiler/xla/service/hlo_proto_util.h" 22 #include "tensorflow/compiler/xla/status_macros.h" 23 #include "tensorflow/compiler/xla/types.h" 24 #include "tensorflow/compiler/xla/util.h" 25 #include "tensorflow/core/lib/gtl/flatset.h" 26 #include "tensorflow/core/lib/strings/str_util.h" 27 #include "tensorflow/core/lib/strings/strcat.h" 28 #include "tensorflow/core/platform/logging.h" 29 30 using ::tensorflow::strings::StrAppend; 31 using ::tensorflow::strings::StrCat; 32 33 namespace xla { 34 35 namespace { 36 void DumpModuleGraph(const HloModule& module, const string& message) { 37 hlo_graph_dumper::MaybeDumpHloModule(module, message); 38 VLOG(3) << "HLO " << message << ":"; 39 XLA_VLOG_LINES(3, module.ToString()); 40 } 41 42 void DumpModuleProto(const HloModule& module, const string& dump_to, 43 const string& pipeline_name, const string& pass_name) { 44 static tensorflow::mutex mu(tensorflow::LINKER_INITIALIZED); 45 static auto* const module_id_to_pass_number = 46 new tensorflow::gtl::FlatMap<int64, int64>(); 47 48 tensorflow::mutex_lock lock(mu); 49 const int64 pass_number = (*module_id_to_pass_number)[module.unique_id()]++; 50 51 const string mod_name = SanitizeFileName(tensorflow::strings::Printf( 52 "module_%04d.%04lld.%s.after_%s", module.unique_id(), pass_number, 53 pipeline_name.c_str(), pass_name.c_str())); 54 55 TF_QCHECK_OK(protobuf_util::DumpProtoToDirectory(MakeHloProto(module), 56 dump_to, mod_name)); 57 } 58 } // namespace 59 60 StatusOr<bool> HloPassPipeline::Run(HloModule* module) { 61 run_called_ = true; 62 63 VLOG(1) << "Running HLO pass pipeline " << name(); 64 65 auto repeated_field = 66 module->config().debug_options().xla_disable_hlo_passes(); 67 tensorflow::gtl::FlatSet<string> disabled_passes(repeated_field.begin(), 68 repeated_field.end()); 69 if (!disabled_passes.empty()) { 70 VLOG(1) << "Passes disabled by --xla_disable_hlo_passes: " 71 << tensorflow::str_util::Join(disabled_passes, ", "); 72 } 73 74 auto run_invariant_checkers = [this, 75 module](const string& message) -> Status { 76 for (auto& invariant_checker : invariant_checkers_) { 77 VLOG(1) << " Invariant checker " << invariant_checker->name(); 78 StatusOr<bool> changed_status = invariant_checker->Run(module); 79 VLOG(1) << " Invariant checker done " << invariant_checker->name(); 80 if (!changed_status.ok()) { 81 VLOG(2) << "Module failed invariant check:"; 82 XLA_VLOG_LINES(2, module->ToString()); 83 return Status(changed_status.status().code(), 84 StrCat(changed_status.status().error_message(), 85 "\n\nFailed ", message)); 86 } 87 TF_RET_CHECK(!changed_status.ValueOrDie()) 88 << "invariant checkers must not change the graph"; 89 } 90 return Status::OK(); 91 }; 92 93 string prefix = name().ToString() + ": pipeline start"; 94 bool changed = false; 95 string message; 96 TF_RETURN_IF_ERROR( 97 run_invariant_checkers(StrCat("before running pipeline: ", name()))); 98 const string xla_dump_per_pass_hlo_proto_to = 99 module->config().debug_options().xla_dump_per_pass_hlo_proto_to(); 100 if (!xla_dump_per_pass_hlo_proto_to.empty()) { 101 DumpModuleProto(*module, xla_dump_per_pass_hlo_proto_to, name().ToString(), 102 "pipeline_start"); 103 } 104 105 for (auto& pass : passes_) { 106 if (disabled_passes.count(pass->name().ToString()) > 0) { 107 VLOG(1) << " Skipping HLO pass " << pass->name() 108 << ", disabled by --xla_disable_hlo_passes"; 109 continue; 110 } 111 112 VLOG(1) << " HLO pass " << pass->name(); 113 114 // Emit label containing: "after foo-pass, before bar-pass". 115 message.clear(); 116 StrAppend(&message, prefix, ", before ", pass->name()); 117 DumpModuleGraph(*module, message); 118 119 TF_ASSIGN_OR_RETURN(bool changed_this_pass, pass->Run(module)); 120 TF_RETURN_IF_ERROR( 121 run_invariant_checkers(StrCat("after running pass: ", pass->name()))); 122 if (!xla_dump_per_pass_hlo_proto_to.empty()) { 123 DumpModuleProto(*module, xla_dump_per_pass_hlo_proto_to, 124 name().ToString(), pass->name().ToString()); 125 } 126 127 changed |= changed_this_pass; 128 prefix.clear(); 129 StrAppend(&prefix, name(), ": after ", pass->name()); 130 } 131 DumpModuleGraph(*module, prefix + ", pipeline end"); 132 return changed; 133 } 134 135 } // namespace xla 136
