From 82f2f084268d80c242596116f77a4224fc4e3a0e Mon Sep 17 00:00:00 2001 From: "A. Unique TensorFlower" Date: Wed, 28 Mar 2018 14:59:53 -0700 Subject: [PATCH] Automated g4 rollback of changelist 190801044 PiperOrigin-RevId: 190839672 --- .../grappler/optimizers/arithmetic_optimizer.cc | 49 ++++++++++------------ .../grappler/optimizers/arithmetic_optimizer.h | 1 - .../grappler/optimizers/graph_optimizer_stage.cc | 4 -- .../grappler/optimizers/graph_optimizer_stage.h | 3 -- 4 files changed, 21 insertions(+), 36 deletions(-) diff --git a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc index 629872b..5dd0b6f 100644 --- a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc +++ b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.cc @@ -196,6 +196,8 @@ void SetSourceDataType(DataType dtype, NodeDef* node) { bool IsNumberType(DataType dtype) { return kNumberTypes.Contains(dtype); } +const char kOutputShapesAttr[] = "_output_shapes"; + // Shape is symbolically defined if it has a known rank, and each dimension is // defined, or is an unknown symbol (dim.size <= -2). bool ShapeIsSymbolicallyDefined(const TensorShapeProto& shape) { @@ -232,19 +234,16 @@ bool ShapesSymbolicallyEqual(const OpInfo::TensorProperties& left, // Returns whether `reshape` is an identity op. The tensor that `reshape` // reshapes is the `output_pos`-th output of node `input`. bool ReshapeIsIdentity(const NodeDef& reshape, const NodeDef& input, - const int output_pos, - const GraphProperties& graph_properties) { - const std::vector& reshape_props = - graph_properties.GetOutputProperties(reshape.name()); - const std::vector& input_props = - graph_properties.GetOutputProperties(input.name()); - if (reshape_props.empty() || input_props.empty() || - input_props.size() <= output_pos) { + const int output_pos) { + if (!reshape.attr().count(kOutputShapesAttr) || + !input.attr().count(kOutputShapesAttr)) { return false; } - const PartialTensorShape& src_shape = input_props[output_pos].shape(); - const PartialTensorShape& dst_shape = reshape_props[0].shape(); + PartialTensorShape src_shape( + input.attr().at(kOutputShapesAttr).list().shape(output_pos)); + PartialTensorShape dst_shape( + reshape.attr().at(kOutputShapesAttr).list().shape(0)); if (src_shape.unknown_rank() || dst_shape.unknown_rank()) { return false; } @@ -1273,8 +1272,7 @@ string ArithmeticOptimizer::TrySimplifyAndReplaceUses( // outputs tensors of shape [M, N] while feeding it with tensors of shape // [M*N] (or worse). The reshape nodes are then necessary to update the // tensor metadata to the required shape. - if (can_use_shapes_ && - ReshapeIsIdentity(*reshape, *input, output_pos, *graph_properties_)) { + if (ReshapeIsIdentity(*reshape, *input, output_pos)) { return reshape->input(0); } } @@ -1588,11 +1586,11 @@ Status ArithmeticOptimizer::SimplifyArithmeticOps() { std::vector> stages; - if (options_.combine_add_to_addn && can_use_shapes_) { + if (options_.combine_add_to_addn) { stages.push_back(std::unique_ptr( new AddOpsRewriteStage(ctx, ctx_ext))); } - if (options_.hoist_common_factor_out_of_aggregation && can_use_shapes_) { + if (options_.hoist_common_factor_out_of_aggregation) { stages.push_back(std::unique_ptr( new HoistCommonFactorOutOfAggregation(ctx, ctx_ext))); } @@ -1629,15 +1627,7 @@ Status ArithmeticOptimizer::SimplifyArithmeticOps() { if (simplified_tensor.empty()) { for (auto& stage : stages) { if (stage->IsSupported(node)) { - const Status stage_status = - stage->TrySimplify(node, &simplified_tensor); - // Each stage must be "error safe" (just like exception safe). In - // case of any error it must leave optimized graph unmodified. - if (!stage_status.ok()) { - LOG(WARNING) << "Failed to run arithmetic optimizer stage " - << stage->stage_name() - << ". Error: " << stage_status.error_message(); - } + TF_RETURN_IF_ERROR(stage->TrySimplify(node, &simplified_tensor)); if (!simplified_tensor.empty()) { break; } @@ -1704,16 +1694,19 @@ Status ArithmeticOptimizer::Optimize(Cluster* /*cluster*/, &frame_map_, &num_frames)); // Shapes are only needed in aggressive mode. graph_properties_.reset(new GraphProperties(item)); - const Status status = graph_properties_->InferStatically(false); - can_use_shapes_ = status.ok(); - if (!can_use_shapes_) { - LOG(WARNING) << "Shape inference failed."; - } + TF_RETURN_IF_ERROR(graph_properties_->InferStatically(false)); + // TODO(ezhulenev): Use GraphProperties to lookup tensor shapes directly + TF_RETURN_IF_ERROR(graph_properties_->AnnotateOutputShapes(optimized_graph_)); // Perform the optimizations. DedupComputations(); TF_RETURN_IF_ERROR(SimplifyArithmeticOps()); + // Clear output shapes. + for (int i = 0; i < optimized_graph->node_size(); ++i) { + optimized_graph_->mutable_node(i)->mutable_attr()->erase(kOutputShapesAttr); + } + return Status::OK(); } diff --git a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.h b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.h index cdeed05..965f0e9 100644 --- a/tensorflow/core/grappler/optimizers/arithmetic_optimizer.h +++ b/tensorflow/core/grappler/optimizers/arithmetic_optimizer.h @@ -126,7 +126,6 @@ class ArithmeticOptimizer : public GraphOptimizer { RewriterConfig::Toggle opt_level_; ArithmeticOptimizerOptions options_; - bool can_use_shapes_ = false; bool fetch_nodes_known_ = false; std::unordered_set nodes_to_preserve_; std::unique_ptr node_map_; diff --git a/tensorflow/core/grappler/optimizers/graph_optimizer_stage.cc b/tensorflow/core/grappler/optimizers/graph_optimizer_stage.cc index 1ea57f7..7044705 100644 --- a/tensorflow/core/grappler/optimizers/graph_optimizer_stage.cc +++ b/tensorflow/core/grappler/optimizers/graph_optimizer_stage.cc @@ -42,10 +42,6 @@ Status GetInputNode(const GraphOptimizerContext& ctx, const string& input, Status GetTensorProperties(const GraphOptimizerContext& ctx, const string& tensor, OpInfo::TensorProperties* properties) { - if (ctx.graph_properties == nullptr) { - return errors::InvalidArgument("Graph properties are unknown."); - } - int port; string tensor_node_name = ParseNodeName(tensor, &port); if (port < 0) { diff --git a/tensorflow/core/grappler/optimizers/graph_optimizer_stage.h b/tensorflow/core/grappler/optimizers/graph_optimizer_stage.h index c7af82a..be95c00 100644 --- a/tensorflow/core/grappler/optimizers/graph_optimizer_stage.h +++ b/tensorflow/core/grappler/optimizers/graph_optimizer_stage.h @@ -117,9 +117,6 @@ class GraphOptimizerStage { : optimizer_name_(optimizer_name), stage_name_(stage_name), ctx_(ctx) {} virtual ~GraphOptimizerStage() = default; - const string& stage_name() const { return stage_name_; } - const string& optimizer_name() const { return optimizer_name_; } - // Check if we should try to simplify node. Returning true doesn't // guarantee that node will be simplified. // -- 2.7.4