From 9abe08570ffe5e4aaa9bbd1f977455e8b0dd4491 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Thu, 9 Nov 2017 15:00:15 -0800
Subject: [PATCH] [TF:XLA] Clean up unused XLA options and functions.
PiperOrigin-RevId: 175217850
---
.../compiler/jit/kernels/xla_launch_op.cc | 1 -
.../compiler/jit/xla_compilation_cache.cc | 3 ---
tensorflow/compiler/tf2xla/xla_compiler.h | 6 ------
.../compiler/xla/client/local_client.cc | 20 -------------------
tensorflow/compiler/xla/client/local_client.h | 16 ---------------
.../compiler/xla/service/hlo_module_config.cc | 4 ++--
.../compiler/xla/service/hlo_module_config.h | 10 ----------
.../compiler/xla/service/local_service.cc | 20 -------------------
tensorflow/compiler/xla/service/service.h | 2 --
9 files changed, 2 insertions(+), 80 deletions(-)
diff --git a/tensorflow/compiler/jit/kernels/xla_launch_op.cc b/tensorflow/compiler/jit/kernels/xla_launch_op.cc
index 27c5da08c11..e481796d9e6 100644
--- a/tensorflow/compiler/jit/kernels/xla_launch_op.cc
+++ b/tensorflow/compiler/jit/kernels/xla_launch_op.cc
@@ -257,7 +257,6 @@ void XlaLocalLaunchOp::Compute(OpKernelContext* ctx) {
options.flib_def = ctx->function_library()->GetFunctionLibraryDefinition();
options.graph_def_version = ctx->function_library()->graph_def_version();
options.allow_cpu_custom_calls = (platform_id_ == gpu::host::kHostPlatformId);
- options.local_executable_has_hybrid_result = true;
const XlaCompiler::CompilationResult* kernel;
xla::LocalExecutable* executable;
diff --git a/tensorflow/compiler/jit/xla_compilation_cache.cc b/tensorflow/compiler/jit/xla_compilation_cache.cc
index 23368b6c76a..bc2eccd2779 100644
--- a/tensorflow/compiler/jit/xla_compilation_cache.cc
+++ b/tensorflow/compiler/jit/xla_compilation_cache.cc
@@ -227,10 +227,7 @@ Status XlaCompilationCache::BuildExecutable(
}
xla::ExecutableBuildOptions build_options;
build_options.set_device_ordinal(client_->default_device_ordinal());
- build_options.set_platform(client_->platform());
build_options.set_result_layout(result.xla_output_shape);
- build_options.set_has_hybrid_result(
- options.local_executable_has_hybrid_result);
auto compile_result =
client_->Compile(*result.computation, argument_layouts, build_options);
diff --git a/tensorflow/compiler/tf2xla/xla_compiler.h b/tensorflow/compiler/tf2xla/xla_compiler.h
index 4d40ca5825a..ac7d4cfb127 100644
--- a/tensorflow/compiler/tf2xla/xla_compiler.h
+++ b/tensorflow/compiler/tf2xla/xla_compiler.h
@@ -236,12 +236,6 @@ class XlaCompiler {
// to the computation.
bool allow_cpu_custom_calls = false;
- // If 'local_executable_has_hybrid_result', the top-level pointers of the
- // result tuple of compiled programs are stored in host memory and the
- // nested buffers in device memory, otherwise the whole result tuple is
- // stored in device memory.
- bool local_executable_has_hybrid_result = false;
-
// If not nullptr, populate_resource_manager is called with the
// compilation device's resource manager when the compilation
// device is created, and can be used to create metadata objects
diff --git a/tensorflow/compiler/xla/client/local_client.cc b/tensorflow/compiler/xla/client/local_client.cc
index 15c744ecd34..b50425a09c7 100644
--- a/tensorflow/compiler/xla/client/local_client.cc
+++ b/tensorflow/compiler/xla/client/local_client.cc
@@ -27,16 +27,6 @@ namespace se = ::perftools::gputools;
namespace xla {
-ExecutableBuildOptions& ExecutableBuildOptions::set_platform(
- perftools::gputools::Platform* platform) {
- platform_ = platform;
- return *this;
-}
-
-perftools::gputools::Platform* ExecutableBuildOptions::platform() const {
- return platform_;
-}
-
ExecutableBuildOptions& ExecutableBuildOptions::set_device_ordinal(
int device_ordinal) {
device_ordinal_ = device_ordinal;
@@ -56,16 +46,6 @@ const Shape* ExecutableBuildOptions::result_layout() const {
return result_layout_set_ ? &result_layout_ : nullptr;
}
-ExecutableBuildOptions& ExecutableBuildOptions::set_has_hybrid_result(
- bool has_hybrid_result) {
- has_hybrid_result_ = has_hybrid_result;
- return *this;
-}
-
-bool ExecutableBuildOptions::has_hybrid_result() const {
- return has_hybrid_result_;
-}
-
namespace {
StatusOr<Backend::StreamPtr> BorrowStreamForDevice(int device_ordinal,
Backend* backend) {
diff --git a/tensorflow/compiler/xla/client/local_client.h b/tensorflow/compiler/xla/client/local_client.h
index 9f985ed5275..e9eeaa0aa22 100644
--- a/tensorflow/compiler/xla/client/local_client.h
+++ b/tensorflow/compiler/xla/client/local_client.h
@@ -37,14 +37,6 @@ namespace xla {
// LocalClient::Compile.
class ExecutableBuildOptions {
public:
- // If set, this is the platform to build the computation for. This must match
- // the underlying platform of the service. A value of nullptr indicates the
- // option has not been set.
- //
- // TODO(b/28616830): Support multiple platforms.
- ExecutableBuildOptions& set_platform(perftools::gputools::Platform* platform);
- perftools::gputools::Platform* platform() const;
-
// If set, this is the device to build the computation for. Valid
// device_ordinal values are: 0 to # of devices - 1. These values are
// identical to the device ordinal values used by StreamExecutor. The built
@@ -61,18 +53,10 @@ class ExecutableBuildOptions {
ExecutableBuildOptions& set_result_layout(const Shape& shape_with_layout);
const Shape* result_layout() const;
- // If set, the executable will be built to output a hybrid
- // ShapedBuffer with top-level tuple pointers in host memory and
- // result buffers in device memory.
- ExecutableBuildOptions& set_has_hybrid_result(bool has_hybrid_result);
- bool has_hybrid_result() const;
-
private:
- perftools::gputools::Platform* platform_ = nullptr;
int device_ordinal_ = -1;
Shape result_layout_;
bool result_layout_set_ = false;
- bool has_hybrid_result_ = true;
};
class LocalExecutable {
diff --git a/tensorflow/compiler/xla/service/hlo_module_config.cc b/tensorflow/compiler/xla/service/hlo_module_config.cc
index 8974deb530c..822e2f1f53e 100644
--- a/tensorflow/compiler/xla/service/hlo_module_config.cc
+++ b/tensorflow/compiler/xla/service/hlo_module_config.cc
@@ -39,8 +39,8 @@ void HloModuleConfig::SetDefaultComputationLayout(
}
string HloModuleConfig::compilation_cache_key() const {
- string key = tensorflow::strings::StrCat("profiling=", hlo_profiling_enabled_,
- "::hybrid=", has_hybrid_result_);
+ string key =
+ tensorflow::strings::StrCat("profiling=", hlo_profiling_enabled_);
StrAppend(&key, "::(");
std::vector<string> params;
for (const ShapeLayout& param_layout :
diff --git a/tensorflow/compiler/xla/service/hlo_module_config.h b/tensorflow/compiler/xla/service/hlo_module_config.h
index 4a7ead9c104..a5ee895e484 100644
--- a/tensorflow/compiler/xla/service/hlo_module_config.h
+++ b/tensorflow/compiler/xla/service/hlo_module_config.h
@@ -104,16 +104,6 @@ class HloModuleConfig {
// Whether to enable HLO-level profiling.
bool hlo_profiling_enabled_ = false;
- // If this flag is true, the generated executable will return a ShapedBuffer
- // holding the result of the computation. In a ShapedBuffer, tuples have their
- // structure held in host memory and the element arrays (leaves of the tuple
- // structure) stored in device memory. The ShapedBuffer is considered "hybrid"
- // because its leaves are on device but its structure is stored on
- // host. Otherwise, if this flag is false, the generated executable will
- // return a DeviceMemoryBase where the result is held entirely in device
- // memory.
- bool has_hybrid_result_ = false;
-
// Module/graph-level seed handle.
uint64 seed_ = 0;
diff --git a/tensorflow/compiler/xla/service/local_service.cc b/tensorflow/compiler/xla/service/local_service.cc
index d4d35da9d63..06f43bd3cb2 100644
--- a/tensorflow/compiler/xla/service/local_service.cc
+++ b/tensorflow/compiler/xla/service/local_service.cc
@@ -68,26 +68,6 @@ LocalService::LocalService(const ServiceOptions& options,
std::unique_ptr<Backend> execute_backend)
: Service(options, std::move(execute_backend)) {}
-namespace {
-// Returns the space required to allocate a shape. If
-// allocate_space_for_deep_copy the space includes all sub-buffers of
-// a tuple.
-int64 RequiredSpace(const Shape& shape, bool allocate_space_for_deep_copy,
- TransferManager* transfer_manager) {
- int64 size = 0;
- // TODO(b/33492279) remove once no devices represent result tuples as
- // contiguous buffers.
- if (allocate_space_for_deep_copy) {
- ShapeUtil::ForEachSubshape(
- shape, [&size, transfer_manager](const Shape& subshape,
- const ShapeIndex& /*index*/) {
- size += transfer_manager->GetByteSizeRequirement(subshape);
- });
- }
- return size;
-}
-} // namespace
-
StatusOr<std::unique_ptr<Executable>> LocalService::CompileExecutable(
const ComputationHandle& computation,
const tensorflow::gtl::ArraySlice<const Shape*> argument_layouts,
diff --git a/tensorflow/compiler/xla/service/service.h b/tensorflow/compiler/xla/service/service.h
index 6646be2e9aa..47f4f0ade59 100644
--- a/tensorflow/compiler/xla/service/service.h
+++ b/tensorflow/compiler/xla/service/service.h
@@ -272,8 +272,6 @@ class Service : public ServiceInterface {
// Create a Hlo module config for the given program shape and arguments.
// execution_options is optional; if not given a default is used.
- // has_hybrid_result is used to initialize the same-named field in
- // HloModuleConfig -- see that class for documentation.
StatusOr<std::unique_ptr<HloModuleConfig>> CreateModuleConfig(
const ProgramShape& program_shape,
tensorflow::gtl::ArraySlice<const Shape*> argument_shapes,