恢复预训练模型的Tensorflow检查点文件

Question

I have downloaded a pre-trained TF-Slim model from MobileNet checkpoint file and I am trying to see what weights were associated with the layers.

As an example, I have three files:

67903136 Jun 14 00:15 mobilenet_v1_1.0_224.ckpt.data-00000-of-00001
19954 Jun 14 00:15 mobilenet_v1_1.0_224.ckpt.index
4319476 Jun 14 00:15 mobilenet_v1_1.0_224.ckpt.meta

First Method:

I use tensorboard directly:

tensorboard --logdir=${CHKPNT_DIR}

it runs locally ( http://127.0.0.1:6006/ ), but does not show anything:

No dashboards are active for the current data set.
Probable causes:

You haven’t written any data to your event files.
TensorBoard can’t find your event files.

Second Method:

I use the backend method Event_Accumulator :

import tensorflow as tf
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
event_acc = EventAccumulator('${CHKPNT_DIR}')
event_acc.Reload()

# Show all tags in the log file
print(event_acc.Tags())

Interestingly, all the Tags are empty:

{'scalars': [], 'histograms': [], 'meta_graph': False, 'images': [], 'graph': False, 'audio': [], 'distributions': [], 'tensors': [], 'run_metadata': []}

So this is the dir :

>>>dir(event_acc)
['Audio', 'CompressedHistograms', 'FirstEventTimestamp', 'Graph', 'Histograms', 'Images', 'MetaGraph', 'PluginAssets', 'PluginTagToContent', 'Reload', 'RetrievePluginAsset', 'RunMetadata', 'Scalars', 'SummaryMetadata', 'Tags', 'Tensors', '_CheckForOutOfOrderStepAndMaybePurge', '_CheckForRestartAndMaybePurge', '_CompressHistogram', '_ConvertHistogramProtoToTuple', '_MaybePurgeOrphanedData', '_ProcessAudio', '_ProcessEvent', '_ProcessHistogram', '_ProcessImage', '_ProcessScalar', '_ProcessTensor', '_Purge', '__class__', '__delattr__', '__dict__', '__doc__', '__format__', '__getattribute__', '__hash__', '__init__', '__module__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__weakref__', '_compression_bps', '_first_event_timestamp', '_generator', '_generator_mutex', '_graph', '_graph_from_metagraph', '_meta_graph', '_plugin_to_tag_to_content', '_tagged_metadata', '_tensor_summaries', 'accumulated_attrs', 'audios', 'compressed_histograms', 'file_version', 'histograms', 'images', 'most_recent_step', 'most_recent_wall_time', 'path', 'purge_orphaned_data', 'scalars', 'summary_metadata', 'tensors']

Then, how are we supposed to view an already pre-trained network? These checkpoint files must contain some sort of Google Protobuf data.

Running TF 1.3.0 on Mac OS 10.12.4.

Answer 1

saver = tf.train.import_meta_graph("path/your/meta/file")
saver.restore("path/to/data/file")

graph = tf.get_default_graph()
writer = tf.summary.FileWriter("path/to/write/graph")
writer.add_graph(graph)

then

tensorboard --logdir="path/to/write/graph"