1 files changed, 0 insertions, 123 deletions
diff --git a/tensorflow/compiler/plugin/executor/compiler.cc b/tensorflow/compiler/plugin/executor/compiler.cc
deleted file mode 100644
index 893ff152f0..0000000000
--- a/tensorflow/compiler/plugin/executor/compiler.cc
+++ /dev/null
@@ -1,123 +0,0 @@
-/* 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 <stdlib.h>
-#include <fstream>
-
-#include "tensorflow/compiler/plugin/executor/compiler.h"
-#include "tensorflow/compiler/plugin/executor/executable.h"
-
-#include "tensorflow/compiler/xla/service/algebraic_simplifier.h"
-#include "tensorflow/compiler/xla/service/flatten_call_graph.h"
-#include "tensorflow/compiler/xla/service/hlo_constant_folding.h"
-#include "tensorflow/compiler/xla/service/hlo_cse.h"
-#include "tensorflow/compiler/xla/service/hlo_dce.h"
-#include "tensorflow/compiler/xla/service/hlo_pass_fix.h"
-#include "tensorflow/compiler/xla/service/hlo_pass_pipeline.h"
-#include "tensorflow/compiler/xla/service/hlo_subcomputation_unification.h"
-#include "tensorflow/compiler/xla/service/inliner.h"
-#include "tensorflow/compiler/xla/service/reshape_mover.h"
-#include "tensorflow/compiler/xla/status_macros.h"
-
-#include "tensorflow/stream_executor/lib/initialize.h"
-#include "tensorflow/stream_executor/lib/strcat.h"
-
-#include "tensorflow/core/lib/core/errors.h"
-
-namespace se = ::perftools::gputools;
-namespace sep = ::perftools::gputools::executorplugin;
-namespace port = ::perftools::gputools::port;
-
-namespace xla {
-namespace executorplugin {
-
-/*
- * Run optimization passes on the module.  The graph is transformed by
- * each pass in the optimization pipeline.  The service subdirectory
- * contains useful optimization passes.
- */
-Status ExecutorCompiler::RunHloOptimization(HloModule* hlo_module,
-                                            HloDumper dump_hlo) {
-  HloPassPipeline pipeline("Executor", dump_hlo);
-  pipeline.AddPass<Inliner>();
-  pipeline.AddPass<HloSubcomputationUnification>();
-  pipeline.AddPass<HloCSE>(false);
-
-  pipeline.AddPass<HloPassFix<AlgebraicSimplifier>>(
-      false, [](const Shape&, const Shape&) { return false; });
-  pipeline.AddPass<ReshapeMover>();
-  pipeline.AddPass<HloConstantFolding>();
-  pipeline.AddPass<HloCSE>(true);
-
-  pipeline.AddPass<HloDCE>();
-  pipeline.AddPass<FlattenCallGraph>();
-  return pipeline.Run(hlo_module).status();
-}
-
-StatusOr<std::unique_ptr<Executable>> ExecutorCompiler::Compile(
-        std::unique_ptr<HloModule> hlo_module, HloDumper dump_hlo,
-        se::StreamExecutor* stream_exec) {
-  TF_RET_CHECK(stream_exec != nullptr);
-
-  VLOG(1) << "Generate graph " << hlo_module->name();
-
-  TF_RETURN_IF_ERROR(RunHloOptimization(hlo_module.get(), dump_hlo));
-
-  // Typically you would visit the HLO graph, building up a compiled equivalent
-  // In this case we are using an Hlo evaluator at execution time, so we don't
-  // need to compile anything
-
-  // Create executable from only the Hlo module
-  std::unique_ptr<Executable> executable;
-  executable.reset(new ExecutorExecutable(std::move(hlo_module)));
-
-  return std::move(executable);
-}
-
-StatusOr<std::vector<std::unique_ptr<Executable>>> ExecutorCompiler::Compile(
-        std::vector<std::unique_ptr<HloModule>> hlo_modules,
-        HloDumper dump_hlos, std::vector<se::StreamExecutor*> stream_execs) {
-
-  return tensorflow::errors::Unimplemented(
-      "Compilation of multiple HLO modules is not supported on Executor.");
-}
-
-StatusOr<std::vector<std::unique_ptr<AotCompilationResult>>>
-ExecutorCompiler::CompileAheadOfTime(
-    std::vector<std::unique_ptr<HloModule>> hlo_modules,
-    HloDumper dump_hlo, const AotCompilationOptions& aot_options) {
-
-  return tensorflow::errors::InvalidArgument(
-      "AOT compilation not supported on Executor");
-}
-
-se::Platform::Id ExecutorCompiler::PlatformId() const {
-  return sep::kExecutorPlatformId;
-}
-
-HloCostAnalysis::ShapeSizeFunction
-ExecutorCompiler::ShapeSizeBytesFunction() const {
-  return ExecutorExecutable::ShapeSizeBytes;
-}
-
-
-}  // namespace executorplugin
-}  // namespace xla
-
-REGISTER_MODULE_INITIALIZER(executor_compiler, {
-  xla::Compiler::RegisterCompilerFactory(sep::kExecutorPlatformId, []() {
-    return xla::MakeUnique<xla::executorplugin::ExecutorCompiler>();
-  });
-});