获取xlacompile.patch补丁文件
用户安装完xlacompile.patch补丁，编译成xlacompile工具后，该工具可以将有控制流的V1网络模型转成函数类的V2网络模型。
将如下代码复制到文件中，并另存为xlacompile.patch，然后上传到Linux服务器tensorflow-1.15.0路径下：
---
WORKSPACE | 7 +
tensorflow/compiler/aot/BUILD | 27 ++++
tensorflow/compiler/aot/xlacompile_main.cc | 170 +++++++++++++++++++++
tensorflow/compiler/tf2xla/tf2xla.cc | 6 +
tensorflow/compiler/tf2xla/tf2xla.h | 4 +
5 files changed, 195 insertions(+)
create mode 100644 tensorflow/compiler/aot/xlacompile_main.cc
diff --git a/WORKSPACE b/WORKSPACE
index 74ea14d..d2265f9 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -34,6 +34,13 @@ load(
bazel_toolchains_repositories()
+http_archive(
+ name = "io_bazel_rules_docker",
+ sha256 = "6287241e033d247e9da5ff705dd6ef526bac39ae82f3d17de1b69f8cb313f9cd",
+ strip_prefix = "rules_docker-0.14.3",
+ urls = ["https://github.com/bazelbuild/rules_docker/releases/download/v0.14.3/rules_docker-v0.14.3.tar.gz"],
+)
+
load(
"@io_bazel_rules_docker//repositories:repositories.bzl",
container_repositories = "repositories",
diff --git a/tensorflow/compiler/aot/BUILD b/tensorflow/compiler/aot/BUILD
index f871115..b2620db 100644
--- a/tensorflow/compiler/aot/BUILD
+++ b/tensorflow/compiler/aot/BUILD
@@ -106,6 +106,33 @@ cc_library(
],
)
+tf_cc_binary(
+ name = "xlacompile",
+ visibility = ["//visibility:public"],
+ deps = [":xlacompile_main"],
+)
+
+cc_library(
+ name = "xlacompile_main",
+ srcs = ["xlacompile_main.cc"],
+ visibility = ["//visibility:public"],
+ deps = [
+ ":tfcompile_lib",
+ "//tensorflow/compiler/tf2xla:tf2xla_proto",
+ "//tensorflow/compiler/tf2xla:tf2xla_util",
+ "//tensorflow/compiler/xla:debug_options_flags",
+ "//tensorflow/compiler/xla/service:compiler",
+ "//tensorflow/core:core_cpu",
+ "//tensorflow/core:core_cpu_internal",
+ "//tensorflow/core:framework",
+ "//tensorflow/core:framework_internal",
+ "//tensorflow/core:graph",
+ "//tensorflow/core:lib",
+ "//tensorflow/core:protos_all_cc",
+ "@com_google_absl//absl/strings",
+ ],
+)
+
# NOTE: Most end-to-end tests are in the "tests" subdirectory, to ensure that
# tfcompile.bzl correctly handles usage from outside of the package that it is
# defined in.
diff --git a/tensorflow/compiler/aot/xlacompile_main.cc b/tensorflow/compiler/aot/xlacompile_main.cc
new file mode 100644
index 0000000..bc795ef
--- /dev/null
+++ b/tensorflow/compiler/aot/xlacompile_main.cc
@@ -0,0 +1,170 @@
+/* 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 <memory>
+#include <string>
+#include <utility>
+#include <vector>
+#include <map>
+
+#include "tensorflow/compiler/aot/flags.h"
+#include "tensorflow/compiler/tf2xla/tf2xla.h"
+#include "tensorflow/compiler/tf2xla/tf2xla_util.h"
+#include "tensorflow/core/platform/init_main.h"
+
+namespace tensorflow {
+namespace xlacompile {
+
+const char kUsageHeader[] =
+ "xlacompile performs ahead-of-time compilation of a TensorFlow graph,\n"
+ "resulting in an object file compiled for your target architecture, and a\n"
+ "header file that gives access to the functionality in the object file.\n"
+ "A typical invocation looks like this:\n"
+ "\n"
+ " $ xlacompile --graph=mygraph.pb --config=config.pbtxt --output=output.pbtxt\n"
+ "\n";
+
+void AppendMainFlags(std::vector<Flag>* flag_list, tfcompile::MainFlags* flags) {
+ const std::vector<Flag> tmp = {
+ {"graph", &flags->graph,
+ "Input GraphDef file. If the file ends in '.pbtxt' it is expected to "
+ "be in the human-readable proto text format, otherwise it is expected "
+ "to be in the proto binary format."},
+ {"config", &flags->config,
+ "Input file containing Config proto. If the file ends in '.pbtxt' it "
+ "is expected to be in the human-readable proto text format, otherwise "
+ "it is expected to be in the proto binary format."},
+ {"output", &flags->out_session_module,
+ "Output session module proto. Will generate '.pb' and '.pbtxt' file."},
+ };
+ flag_list->insert(flag_list->end(), tmp.begin(), tmp.end());
+}
+
+Status ReadProtoFile(const string& fname, protobuf::Message* proto) {
+ if (absl::EndsWith(fname, ".pbtxt")) {
+ return ReadTextProto(Env::Default(), fname, proto);
+ } else {
+ return ReadBinaryProto(Env::Default(), fname, proto);
+ }
+}
+
+Status Main(tfcompile::MainFlags& flags) {
+ // Process config.
+ tf2xla::Config config;
+ if (flags.config.empty()) {
+ return errors::InvalidArgument("Must specify --config");
+ }
+ TF_RETURN_IF_ERROR(ReadProtoFile(flags.config, &config));
+ TF_RETURN_IF_ERROR(ValidateConfig(config));
+ if (flags.dump_fetch_nodes) {
+ std::set<string> nodes;
+ for (const tf2xla::Fetch& fetch : config.fetch()) {
+ nodes.insert(fetch.id().node_name());
+ }
+ std::cout << absl::StrJoin(nodes, ",");
+ return Status::OK();
+ }
+
+ // Read and initialize the graph.
+ if (flags.graph.empty()) {
+ return errors::InvalidArgument("Must specify --graph");
+ }
+ if (flags.out_session_module.empty()) {
+ return errors::InvalidArgument("Must specify --output");
+ }
+
+ string output_pb_bin = flags.out_session_module + ".pb";
+ string output_pb_txt = flags.out_session_module + ".pbtxt";
+ if (output_pb_bin == flags.config || output_pb_bin == flags.graph ||
+ output_pb_txt == flags.config || output_pb_txt == flags.graph) {
+ return errors::InvalidArgument("Must different --config --graph --output");
+ }
+
+ GraphDef graph_def;
+ TF_RETURN_IF_ERROR(ReadProtoFile(flags.graph, &graph_def));
+ std::unique_ptr<Graph> graph;
+ TF_RETURN_IF_ERROR(ConvertGraphDefToXla(graph_def, config, graph));
+
+ std::map<string, string> arg_name_maps;
+ GraphDef new_graph_def;
+ graph->ToGraphDef(&new_graph_def);
+ // Delete _class attribute for: expects to be colocated with unknown node
+ for (int i = 0; i < new_graph_def.node_size(); ++i) {
+ NodeDef *node = new_graph_def.mutable_node(i);
+ node->mutable_attr()->erase("_class");
+ if (node->op() == "_Retval") {
+ node->set_name(absl::StrCat(node->attr().at("index").i(), "_Retval"));
+ }
+ if (node->op() == "_Arg") {
+ const string name = node->name();
+ node->set_name(absl::StrCat(node->attr().at("index").i(), "_Arg"));
+ arg_name_maps[name] = node->name();
+ }
+ }
+
+ for (int i = 0; i < new_graph_def.node_size() && !arg_name_maps.empty(); ++i) {
+ NodeDef *node = new_graph_def.mutable_node(i);
+ for (int j = 0; j < node->input_size(); ++j) {
+ auto it = arg_name_maps.find(node->input(j));
+ if (it != arg_name_maps.end()) {
+ *node->mutable_input(j) = it->second;
+ }
+ }
+ }
+
+ TF_RETURN_IF_ERROR(WriteBinaryProto(Env::Default(), output_pb_bin, new_graph_def));
+ std::cerr << "Successfully convert: " << output_pb_bin << "\n";
+ TF_RETURN_IF_ERROR(WriteTextProto(Env::Default(), output_pb_txt, new_graph_def));
+ std::cerr << "Successfully convert: " << output_pb_txt << "\n";
+ return Status::OK();
+}
+
+} // end namespace xlacompile
+} // end namespace tensorflow
+
+int main(int argc, char** argv) {
+ tensorflow::tfcompile::MainFlags flags;
+ flags.target_triple = "x86_64-pc-linux";
+ flags.out_function_object = "out_model.o";
+ flags.out_metadata_object = "out_helper.o";
+ flags.out_header = "out.h";
+ flags.entry_point = "entry";
+
+ std::vector<tensorflow::Flag> flag_list;
+ tensorflow::xlacompile::AppendMainFlags(&flag_list, &flags);
+
+ tensorflow::string usage = tensorflow::xlacompile::kUsageHeader;
+ usage += tensorflow::Flags::Usage(argv[0], flag_list);
+ if (argc > 1 && absl::string_view(argv[1]) == "--help") {
+ std::cerr << usage << "\n";
+ return 0;
+ }
+ bool parsed_flags_ok = tensorflow::Flags::Parse(&argc, argv, flag_list);
+ QCHECK(parsed_flags_ok) << "\n" << usage;
+
+ tensorflow::port::InitMain(usage.c_str(), &argc, &argv);
+ QCHECK(argc == 1) << "\nERROR: This command does not take any arguments "
+ "other than flags\n\n"
+ << usage;
+ tensorflow::Status status = tensorflow::xlacompile::Main(flags);
+ if (status.code() == tensorflow::error::INVALID_ARGUMENT) {
+ std::cerr << "INVALID ARGUMENTS: " << status.error_message() << "\n\n"
+ << usage;
+ return 1;
+ } else {
+ TF_QCHECK_OK(status);
+ }
+ return 0;
+}
diff --git a/tensorflow/compiler/tf2xla/tf2xla.cc b/tensorflow/compiler/tf2xla/tf2xla.cc
index 3c2b256..3872776 100644
--- a/tensorflow/compiler/tf2xla/tf2xla.cc
+++ b/tensorflow/compiler/tf2xla/tf2xla.cc
@@ -410,4 +410,10 @@ Status ConvertGraphDefToXla(const GraphDef& graph_def,
return Status::OK();
}
+Status ConvertGraphDefToXla(const GraphDef &graph_def,
+ const tf2xla::Config &config,
+ std::unique_ptr<Graph> &graph) {
+ return InitGraph(graph_def, config, &graph);
+}
+
} // namespace tensorflow
diff --git a/tensorflow/compiler/tf2xla/tf2xla.h b/tensorflow/compiler/tf2xla/tf2xla.h
index 432a12a..969500c 100644
--- a/tensorflow/compiler/tf2xla/tf2xla.h
+++ b/tensorflow/compiler/tf2xla/tf2xla.h
@@ -20,6 +20,7 @@ limitations under the License.
#include "tensorflow/compiler/xla/client/client.h"
#include "tensorflow/compiler/xla/client/xla_computation.h"
#include "tensorflow/core/framework/graph.pb.h"
+#include "tensorflow/core/graph/graph.h"
namespace tensorflow {
@@ -34,6 +35,9 @@ Status ConvertGraphDefToXla(const GraphDef& graph_def,
const tf2xla::Config& config, xla::Client* client,
xla::XlaComputation* computation);
+Status ConvertGraphDefToXla(const GraphDef &graph_def,
+ const tf2xla::Config &config,
+ std::unique_ptr<Graph> &graph);
} // namespace tensorflow
#endif // TENSORFLOW_COMPILER_TF2XLA_TF2XLA_H_
--
1.8.3.1
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