diff options
Diffstat (limited to 'tensorflow/compiler/tf2xla/xla_compiler.cc')
| -rw-r--r-- | tensorflow/compiler/tf2xla/xla_compiler.cc | 16 |
1 files changed, 6 insertions, 10 deletions
diff --git a/tensorflow/compiler/tf2xla/xla_compiler.cc b/tensorflow/compiler/tf2xla/xla_compiler.cc index dcb455779d..739e47778a 100644 --- a/tensorflow/compiler/tf2xla/xla_compiler.cc +++ b/tensorflow/compiler/tf2xla/xla_compiler.cc @@ -20,7 +20,6 @@ limitations under the License. #include "absl/memory/memory.h" #include "tensorflow/compiler/tf2xla/dump_graph.h" -#include "tensorflow/compiler/tf2xla/functionalize_control_flow.h" #include "tensorflow/compiler/tf2xla/graph_compiler.h" #include "tensorflow/compiler/tf2xla/shape_util.h" #include "tensorflow/compiler/tf2xla/sharding_util.h" @@ -150,6 +149,9 @@ Status XlaCompiler::FindFunctionBody(const NameAttrList& function, TF_RETURN_WITH_CONTEXT_IF_ERROR( GetFunctionBody(function, flib_runtime_, fbody), "Local lookup failed with: ", status.error_message()); + VLOG(4) << "Function " << function.name() << " in flib_runtime_"; + } else { + VLOG(4) << "Function " << function.name() << " in local_flib_runtime_"; } return Status::OK(); } @@ -323,8 +325,7 @@ Status ExecuteGraph(XlaContext* xla_context, std::unique_ptr<Graph> graph, step_container->name(), XlaContext::kXlaContextResourceName, xla_context)); - GraphCompiler graph_compiler(xla_context, device, graph.get(), flib, - step_container.get()); + GraphCompiler graph_compiler(device, graph.get(), flib, step_container.get()); TF_RETURN_IF_ERROR(graph_compiler.Compile()); // Explicitly clean up the step container, to capture the cleanup status. step_container.reset(); @@ -743,18 +744,13 @@ Status XlaCompiler::CompileGraph(const XlaCompiler::CompileOptions& options, if (VLOG_IS_ON(2)) { VLOG(2) << "XlaCompiler::CompileGraph: " << dump_graph::DumpGraphToFile( - absl::StrCat("xla_compile_graph_", name), *graph); + absl::StrCat("xla_compile_graph_", name), *graph, + flib_runtime_->GetFunctionLibraryDefinition()); } // Report the error here if initialization failed. TF_RETURN_IF_ERROR(initialization_status_); - // Converts Tensorflow's graph control-flow constructs into functional - // control-flow that can be compiled into XLA code. - TF_RETURN_IF_ERROR( - FunctionalizeControlFlow(flib_runtime_->GetFunctionLibraryDefinition(), - graph.get(), local_flib_def_.get())); - // Detect invalid nodes. // FunctionalizeControlFlow may remove some nodes from the graph. TF_RETURN_IF_ERROR(ValidateGraph(graph.get(), *options_.flib_def, |