experiments/STT-tensorflow
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[Executor] Fix segfault when using verbose logging in the executor module.

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Selective vlog-enabling for the executor module would trigger a crash in `SimplePropagatorState::DumpState()` (called when the executor executes a kernel that produces an error status). Because `SimplePropagatorState` is in a separate module, and selective vlogging might not be enabled for that module as well, the necessary state was not created, leading to a null pointer dereference.

The fix is to share the executor's vlog setting with the propagators, so that if vlogging is enabled for the executor, `SimplePropagatorState` will create the necessary debugging structures (i.e. the `SimplePropgagatorState::active_` vector).

PiperOrigin-RevId: 310646985
Change-Id: Ic4220bfdb7e0800e1ad8a5eb6d468db5886367ad
This commit is contained in:
Derek Murray 2020-05-08 16:08:20 -07:00 committed by TensorFlower Gardener
parent 110026283f
commit 4083528111
5 changed files with 12 additions and 10 deletions
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2
tensorflow/core/common_runtime/executor.cc
View File

@ -403,7 +403,7 @@ ExecutorState<PropagatorStateType>::ExecutorState(
runner_(args.runner),
sync_on_finish_(args.sync_on_finish),
run_all_kernels_inline_(args.run_all_kernels_inline),
propagator_(immutable_state, step_id_),
propagator_(immutable_state, step_id_, vlog_),
num_outstanding_ops_(0) {
if (args.user_intra_op_threadpool != nullptr) {
Device* device = immutable_state_.params().device;

4
tensorflow/core/common_runtime/propagator_state.cc
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@ -26,10 +26,10 @@ limitations under the License.
namespace tensorflow {
PropagatorState::PropagatorState(const ImmutableExecutorState& immutable_state,
int64 step_id)
int64 step_id, bool vlog)
: immutable_state_(immutable_state),
step_id_(step_id),
vlog_(VLOG_IS_ON(1)) {
vlog_(vlog || VLOG_IS_ON(1)) {
// We start the entire execution in iteration 0 of the root frame
// so let us create the root frame and the state for iteration 0.
// We assume root_frame_->frame_name.empty().

3
tensorflow/core/common_runtime/propagator_state.h
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@ -45,7 +45,8 @@ typedef gtl::InlinedVector<AllocatorAttributes, 4> AllocatorAttributeVec;
// adding them to a `TaggedNodeSeq`.
class PropagatorState {
public:
PropagatorState(const ImmutableExecutorState& immutable_state, int64 step_id);
PropagatorState(const ImmutableExecutorState& immutable_state, int64 step_id,
bool vlog);
~PropagatorState();
private:

8
tensorflow/core/common_runtime/simple_propagator_state.cc
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@ -23,16 +23,16 @@ limitations under the License.
namespace tensorflow {
SimplePropagatorState::SimplePropagatorState(
const ImmutableExecutorState& immutable_state, int64 step_id)
const ImmutableExecutorState& immutable_state, int64 step_id, bool vlog)
: SimplePropagatorState(immutable_state, step_id,
immutable_state.get_root_frame_info()) {}
immutable_state.get_root_frame_info(), vlog) {}
SimplePropagatorState::SimplePropagatorState(
const ImmutableExecutorState& immutable_state, int64 step_id,
const ImmutableExecutorState::FrameInfo& finfo)
const ImmutableExecutorState::FrameInfo& finfo, bool vlog)
: immutable_state_(immutable_state),
step_id_(step_id),
vlog_(VLOG_IS_ON(1)),
vlog_(vlog || VLOG_IS_ON(1)),
input_tensors_(finfo.total_inputs),
pending_(
new std::atomic<int32>[immutable_state.graph_view().num_nodes()]),

5
tensorflow/core/common_runtime/simple_propagator_state.h
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@ -47,7 +47,7 @@ namespace tensorflow {
class SimplePropagatorState {
public:
SimplePropagatorState(const ImmutableExecutorState& immutable_state,
int64 step_id);
int64 step_id, bool vlog);
~SimplePropagatorState();
// A `TaggedNode` corresponds to a single invocation of a node's kernel,
@ -157,7 +157,8 @@ class SimplePropagatorState {
private:
SimplePropagatorState(const ImmutableExecutorState& immutable_state_,
int64 step_id,
const ImmutableExecutorState::FrameInfo& finfo);
const ImmutableExecutorState::FrameInfo& finfo,
bool vlog);
const ImmutableExecutorState& immutable_state_;
const int64 step_id_;