diff options
| -rw-r--r-- | tensorflow/compiler/xla/service/hlo_module_config.h | 3 | ||||
| -rw-r--r-- | tensorflow/compiler/xla/service/layout_assignment.cc | 3 |
2 files changed, 1 insertions, 5 deletions
diff --git a/tensorflow/compiler/xla/service/hlo_module_config.h b/tensorflow/compiler/xla/service/hlo_module_config.h index 3f1e1cc73e..68c18836eb 100644 --- a/tensorflow/compiler/xla/service/hlo_module_config.h +++ b/tensorflow/compiler/xla/service/hlo_module_config.h @@ -106,9 +106,6 @@ class HloModuleConfig { absl::optional<ComputationLayout> entry_computation_layout_; - // Whether this is a 'host module'. - bool is_host_module_ = false; - // Module/graph-level seed handle. uint64 seed_ = 0; diff --git a/tensorflow/compiler/xla/service/layout_assignment.cc b/tensorflow/compiler/xla/service/layout_assignment.cc index 6e17711f57..082bf8bffe 100644 --- a/tensorflow/compiler/xla/service/layout_assignment.cc +++ b/tensorflow/compiler/xla/service/layout_assignment.cc @@ -855,8 +855,7 @@ void LayoutAssignment::SetupCopiedInstruction(const HloInstruction& instruction, ? instruction.sharding().GetSubSharding(instruction.shape(), index) : instruction.sharding(); // We propagate the sharding to the copied instruction only if it is a - // special sharding, like tiled ones, or special devices like the - // HostCompute module. + // special sharding, like tiled ones. // Otherwise it is preferable to leave the new instruction without device, // and let the automatic device placer to choose the best location. auto device = sharding.UniqueDevice(); |