Issue 1:
System information

See attached tf_env.txt generated by tf_env_collect.sh.

tf.version.VERSION 1.14.0

tf.version.GIT_VERSION unknown

Describe the problem

We have been successfully training Tensorflow models and loading them into Java project for inference. We have been training models using Tensorflow [1.8.0 - 1.10.0] and loading them into a gradle project compiled with 1.8.0. It worked.

dependencies {

compile(
"org.tensorflow:tensorflow:" + "1.8.0",
"com.google.guava:guava:" + guavaVersion,
"com.opencsv:opencsv:" + openCSVVersion,
)

Recently we have retrained the models using Tensorflow 1.14.0. After replacing the older models and raising the gradle version number to 1.14.0

dependencies {

compile(
"org.tensorflow:tensorflow:" + "1.14.0",
"com.google.guava:guava:" + guavaVersion,
"com.opencsv:opencsv:" + openCSVVersion,
)

one of the tests that attempts to load the model started throwing the following exception below:

java.lang.UnsatisfiedLinkError: /tmp/tensorflow_native_libraries-1567776737834-0/libtensorflow_jni.so: /tmp/tensorflow_native_libraries-1567776737834-0/libtensorflow_jni.so: undefined symbol: _ZN11tensorflow10FileSystem20RecursivelyCreateDirERKSs

at java.lang.ClassLoader$NativeLibrary.load(Native Method)
at java.lang.ClassLoader.loadLibrary0(ClassLoader.java:1941)
at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1824)
at java.lang.Runtime.load0(Runtime.java:809)
at java.lang.System.load(System.java:1086)
at org.tensorflow.NativeLibrary.load(NativeLibrary.java:101)
at org.tensorflow.TensorFlow.init(TensorFlow.java:66)
at org.tensorflow.TensorFlow.<clinit>(TensorFlow.java:70)
at org.tensorflow.SavedModelBundle.<clinit>(SavedModelBundle.java:170)

This does not look like a bug issue but it would be nice if you could provide some tips on how to fix this on our end. Thank you.

Issue 2:
I trying to add summary and checkpoint to my distributed tensorflow training with custom data

summary_hook = tf.train.SummarySaverHook(save_secs=600,output_dir=FLAGS.log_dir,summary_op=summary_op)
checkpoint_hook = tf.train.CheckpointSaverHook(save_steps=test_timing,checkpoint_dir=FLAGS.log_dir,saver=saver)
with tf.train.MonitoredTrainingSession(server.target,is_chief=is_chief,hooks=[sync_replicas_hook,summary_hook,checkpoint_hook],config=sess_config) as sess:

with above I can't run the sess with error of below

2017-08-24 19:38:31.250556: W tensorflow/core/framework/op_kernel.cc:1148] Invalid argument: Shape [-1,13] has negative dimensions
2017-08-24 19:38:31.250633: E tensorflow/core/common_runtime/executor.cc:644] Executor failed to create kernel. Invalid argument: Shape [-1,13] has negative dimensions
[[Node: mfcc_input = Placeholder[dtype=DT_FLOAT, shape=[?,13], _device="/job:worker/replica:0/task:0/gpu:0"]()]]
2017-08-24 19:38:31.251688: W tensorflow/core/framework/op_kernel.cc:1148] Invalid argument: Shape [-1,13] has negative dimensions
2017-08-24 19:38:31.251734: E tensorflow/core/common_runtime/executor.cc:644] Executor failed to create kernel. Invalid argument: Shape [-1,13] has negative dimensions
[[Node: mfcc_input = Placeholder[dtype=DT_FLOAT, shape=[?,13], _device="/job:worker/replica:0/task:0/gpu:0"]()]]
2017-08-24 19:38:31.253478: W tensorflow/core/framework/op_kernel.cc:1148] Invalid argument: Shape [-1,3] has negative dimensions
2017-08-24 19:38:31.253522: E tensorflow/core/common_runtime/executor.cc:644] Executor failed to create kernel. Invalid argument: Shape [-1,3] has negative dimensions
[[Node: labels = Placeholder[dtype=DT_INT32, shape=[?,3], _device="/job:worker/replica:0/task:0/gpu:0"]()]]

how ever if I run without the summary and checkpoint hook it just work fine....

I want to specify which timing and which directory to view my summary and save the checkpoint.

Does anyone have an idea how to solve this problem?