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Add flag to determine whether to do L1 optimizations and inline functions. Default is to do them. In tf_optimizer don't inline or do l1 optimizations.

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PiperOrigin-RevId: 157673614
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A. Unique TensorFlower 2017-05-31 21:24:02 -07:00 committed by TensorFlower Gardener
parent 25bb504ccd
commit d9620cab82
4 changed files with 22 additions and 13 deletions
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23
tensorflow/core/grappler/grappler_item_builder.cc
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@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and See the License for the specific language governing permissions and
limitations under the License. limitations under the License.
==============================================================================*/ ==============================================================================*/
#include "tensorflow/core/grappler/grappler_item_builder.h" #include "tensorflow/core/grappler/grappler_item_builder.h"
#include <unordered_map> #include <unordered_map>
@ -70,7 +69,8 @@ void InitializeTensor(DataType type, Tensor* tensor) {
// of the cluster type (E.g: single cpu, multiple gpu, etc) being simulated in // of the cluster type (E.g: single cpu, multiple gpu, etc) being simulated in
// order to get the correct session options and environment, and performing the // order to get the correct session options and environment, and performing the
// correct optimizations. // correct optimizations.
Status OptimizeGraph(const GraphDef& graph_def, GraphDef* output_graph_def) { Status OptimizeGraph(const GraphDef& graph_def, GraphDef* output_graph_def,
const ItemConfig& cfg) {
// Create a session option for a single GPU device. // Create a session option for a single GPU device.
SessionOptions options; SessionOptions options;
@ -94,7 +94,12 @@ Status OptimizeGraph(const GraphDef& graph_def, GraphDef* output_graph_def) {
// Optimizer options: L1 and inlining. L1 is default. // Optimizer options: L1 and inlining. L1 is default.
OptimizerOptions* optimizer_opts = OptimizerOptions* optimizer_opts =
options.config.mutable_graph_options()->mutable_optimizer_options(); options.config.mutable_graph_options()->mutable_optimizer_options();
optimizer_opts->set_do_function_inlining(true); if (cfg.apply_optimizations) {
optimizer_opts->set_opt_level(::tensorflow::OptimizerOptions_Level_L1);
} else {
optimizer_opts->set_opt_level(::tensorflow::OptimizerOptions_Level_L0);
}
optimizer_opts->set_do_function_inlining(cfg.inline_functions);
// Create the function library runtime. // Create the function library runtime.
std::unique_ptr<FunctionLibraryRuntime> flib(NewFunctionLibraryRuntime( std::unique_ptr<FunctionLibraryRuntime> flib(NewFunctionLibraryRuntime(
@ -130,13 +135,11 @@ std::unique_ptr<GrapplerItem> GrapplerItemFromMetaGraphDef(
new_item->graph = meta_graph.graph_def(); new_item->graph = meta_graph.graph_def();
// Optimize the graph (function inlining, l1 optimizations, etc). // Optimize the graph (function inlining, l1 optimizations, etc).
if (cfg.apply_optimizations) { Status optimize_status =
Status optimize_status = OptimizeGraph(meta_graph.graph_def(), &new_item->graph, cfg);
OptimizeGraph(meta_graph.graph_def(), &new_item->graph); if (!optimize_status.ok()) {
if (!optimize_status.ok()) { LOG(ERROR) << "Function optimization failed: " << optimize_status;
LOG(ERROR) << "Function optimization failed: " << optimize_status; return nullptr;
return nullptr;
}
} }
// Attempt to detect the fetch node(s). // Attempt to detect the fetch node(s).

7
tensorflow/core/grappler/grappler_item_builder.h
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@ -31,7 +31,8 @@ struct ItemConfig {
: ignore_user_placement(true), : ignore_user_placement(true),
ignore_colocation(true), ignore_colocation(true),
placeholder_unknown_output_shape_dim(-1), placeholder_unknown_output_shape_dim(-1),
apply_optimizations(true) {} apply_optimizations(true),
inline_functions(true) {}
// If true, ignore all user specified node placement. // If true, ignore all user specified node placement.
bool ignore_user_placement; bool ignore_user_placement;
@ -40,8 +41,10 @@ struct ItemConfig {
// Dimension to use if a placeholder node has an _output_shapes attribute with // Dimension to use if a placeholder node has an _output_shapes attribute with
// a dimension of -1. // a dimension of -1.
int placeholder_unknown_output_shape_dim; int placeholder_unknown_output_shape_dim;
// If true, does inlining and L1 optimizations. // If true, does L1 optimizations.
bool apply_optimizations; bool apply_optimizations;
// If true, does inlining.
bool inline_functions;
}; };
// Factory method for creating a GrapplerItem from a MetaGraphDef. // Factory method for creating a GrapplerItem from a MetaGraphDef.

1
tensorflow/core/grappler/grappler_item_builder_test.cc
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@ -70,6 +70,7 @@ std::unique_ptr<GrapplerItem> CreateGrapplerItem(const GraphDef &def,
const CollectionDef &fetches) { const CollectionDef &fetches) {
MetaGraphDef meta_def; MetaGraphDef meta_def;
ItemConfig cfg; ItemConfig cfg;
cfg.inline_functions = true;
*meta_def.mutable_graph_def() = def; *meta_def.mutable_graph_def() = def;
(*meta_def.mutable_collection_def())["train_op"] = fetches; (*meta_def.mutable_collection_def())["train_op"] = fetches;
return GrapplerItemFromMetaGraphDef("0", meta_def, cfg); return GrapplerItemFromMetaGraphDef("0", meta_def, cfg);

4
tensorflow/python/grappler/tf_optimizer.i
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@ -67,7 +67,9 @@ PyObject* TF_OptimizeGraph(
const tensorflow::RewriterConfig& rewriter_config, const tensorflow::RewriterConfig& rewriter_config,
const tensorflow::MetaGraphDef& metagraph, const tensorflow::MetaGraphDef& metagraph,
const string& graph_id, TF_Status* out_status) { const string& graph_id, TF_Status* out_status) {
const tensorflow::grappler::ItemConfig item_config; tensorflow::grappler::ItemConfig item_config;
item_config.inline_functions = false;
item_config.apply_optimizations = false;
std::unique_ptr<tensorflow::grappler::GrapplerItem> grappler_item = std::unique_ptr<tensorflow::grappler::GrapplerItem> grappler_item =
tensorflow::grappler::GrapplerItemFromMetaGraphDef(graph_id, metagraph, item_config); tensorflow::grappler::GrapplerItemFromMetaGraphDef(graph_id, metagraph, item_config);
std::unordered_map<string, tensorflow::DeviceProperties> device_map; std::unordered_map<string, tensorflow::DeviceProperties> device_map;