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Support old-style TensorFlow events (tensorboard) #2467

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Support old-style TensorFlow events (tensorboard) #2467

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46 changes: 32 additions & 14 deletions pkg/metricscollector/v1beta1/tfevent-metricscollector/tfevent_loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,11 +30,23 @@
import rfc3339
import tensorflow as tf
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
from tensorboard.backend.event_processing.tag_types import TENSORS
from tensorboard.backend.event_processing.tag_types import SCALARS, TENSORS

from pkg.metricscollector.v1beta1.common import const


def _should_consider(tag: str, metric_name: str, tfefile: str) -> bool:
tfefile_parent_dir = (
os.path.dirname(metric_name)
if len(metric_name.split("/")) >= 2
else os.path.dirname(tfefile)
)
basedir_name = os.path.dirname(tfefile)
return tag.startswith(metric_name.split("/")[-1]) and basedir_name.endswith(
tfefile_parent_dir
)


class TFEventFileParser:
def __init__(self, metric_names):
self.metric_names = metric_names
Expand All @@ -47,21 +59,15 @@ def find_all_files(directory):

def parse_summary(self, tfefile):
metric_logs = []
event_accumulator = EventAccumulator(tfefile, size_guidance={TENSORS: 0})
event_accumulator = EventAccumulator(
tfefile, size_guidance={SCALARS: 0, TENSORS: 0}
)
event_accumulator.Reload()
for tag in event_accumulator.Tags()[TENSORS]:
tags = event_accumulator.Tags()
for tag in tags[TENSORS]:
for m in self.metric_names:
tfefile_parent_dir = (
os.path.dirname(m)
if len(m.split("/")) >= 2
else os.path.dirname(tfefile)
)
basedir_name = os.path.dirname(tfefile)
if not tag.startswith(m.split("/")[-1]) or not basedir_name.endswith(
tfefile_parent_dir
):
if not _should_consider(tag, m, tfefile):
continue

for tensor in event_accumulator.Tensors(tag):
ml = api_pb2.MetricLog(
time_stamp=rfc3339.rfc3339(
Expand All @@ -72,7 +78,19 @@ def parse_summary(self, tfefile):
),
)
metric_logs.append(ml)

# support old-style tensorboard metrics too
for tag in tags[SCALARS]:
for m in self.metric_names:
if not _should_consider(tag, m, tfefile):
continue
for scalar in event_accumulator.Scalars(tag):
ml = api_pb2.MetricLog(
time_stamp=rfc3339.rfc3339(
datetime.fromtimestamp(scalar.wall_time)
),
metric=api_pb2.Metric(name=m, value=str(scalar.value)),
)
metric_logs.append(ml)
return metric_logs


Expand Down