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#include "tensorflow/core/kernels/reader_base.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/lib/core/coding.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/notification.h"
#include "tensorflow/core/lib/core/stringpiece.h"
#include "tensorflow/core/lib/strings/strcat.h"
#include "tensorflow/core/lib/strings/str_util.h"
namespace tensorflow {
// ReaderBase ------------------------------------------------------
ReaderBase::ReaderBase(const string& name) : name_(name) {}
int64 ReaderBase::NumRecordsProduced() {
mutex_lock lock(mu_);
return num_records_produced_;
}
int64 ReaderBase::NumWorkUnitsCompleted() {
mutex_lock lock(mu_);
return work_finished_;
}
Status ReaderBase::Reset() {
mutex_lock lock(mu_);
return ResetLocked();
}
Status ReaderBase::ResetLocked() {
work_started_ = 0;
work_finished_ = 0;
num_records_produced_ = 0;
work_.clear();
return Status::OK();
}
Status ReaderBase::SerializeState(string* state) {
mutex_lock lock(mu_);
return SerializeStateLocked(state);
}
Status ReaderBase::SerializeStateLocked(string* state) {
return errors::Unimplemented("Reader SerializeState");
}
Status ReaderBase::RestoreState(const string& state) {
mutex_lock lock(mu_);
Status status = RestoreStateLocked(state);
if (!status.ok()) {
ResetLocked();
}
return status;
}
Status ReaderBase::RestoreStateLocked(const string& state) {
return errors::Unimplemented("Reader RestoreState");
}
void ReaderBase::Read(QueueInterface* queue, string* key, string* value,
OpKernelContext* context) {
mutex_lock lock(mu_);
while (true) {
if (!work_in_progress()) {
GetNextWorkLocked(queue, context);
if (!context->status().ok()) return;
}
bool produced = false;
bool at_end = false;
Status status = ReadLocked(key, value, &produced, &at_end);
if (!at_end && status.ok() && !produced) {
status = errors::Internal(
"ReadLocked() for ", name(),
" must set *at_end=true, *produced=true, or return an error.");
}
if (!status.ok() && produced) {
status = errors::Internal("ReadLocked() for ", name(),
" set *produced=true *and* returned an error: ",
status.ToString());
}
if (status.ok() && at_end) {
status = OnWorkFinishedLocked();
work_finished_ = work_started_;
}
if (!status.ok()) {
context->SetStatus(status);
return;
}
if (produced) {
++num_records_produced_;
return;
}
}
}
void ReaderBase::GetNextWorkLocked(QueueInterface* queue,
OpKernelContext* context) {
Notification n;
queue->TryDequeue(
context, [this, context, &n](const QueueInterface::Tuple& tuple) {
if (context->status().ok()) {
if (tuple.size() != 1) {
context->SetStatus(
errors::InvalidArgument("Expected single component queue"));
} else if (tuple[0].dtype() != DT_STRING) {
context->SetStatus(errors::InvalidArgument(
"Expected queue with single string component"));
} else if (tuple[0].NumElements() != 1) {
context->SetStatus(errors::InvalidArgument(
"Expected to dequeue a one-element string tensor"));
} else {
work_ = tuple[0].flat<string>()(0);
++work_started_;
Status status = OnWorkStartedLocked();
if (!status.ok()) {
context->SetStatus(status);
--work_started_;
}
}
}
n.Notify();
});
n.WaitForNotification();
}
void ReaderBase::SaveBaseState(ReaderBaseState* state) const {
state->Clear();
state->set_work_started(work_started_);
state->set_work_finished(work_finished_);
state->set_num_records_produced(num_records_produced_);
state->set_current_work(work_);
}
Status ReaderBase::RestoreBaseState(const ReaderBaseState& state) {
work_started_ = state.work_started();
work_finished_ = state.work_finished();
num_records_produced_ = state.num_records_produced();
work_ = state.current_work();
if (work_started_ < 0 || work_finished_ < 0 || num_records_produced_ < 0) {
return errors::InvalidArgument(
"Unexpected negative value when restoring in ", name(), ": ",
state.ShortDebugString());
}
if (work_started_ > work_finished_) {
return errors::InvalidArgument(
"Inconsistent work started vs. finished when restoring in ", name(),
": ", state.ShortDebugString());
}
return Status::OK();
}
} // namespace tensorflow
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