launching tensorboard from google cloud datalab - tensorflow

Question

I need help in luanching tensorboard from tensorflow running on the datalab,
My code is the followings (everything is on the datalab):
import tensorflow as tf
with tf.name_scope('input'):
print ("X_np")
X_np = tf.placeholder(tf.float32, shape=[None, num_of_features],name="input")
with tf.name_scope('weights'):
print ("W is for weights & - 15 number of diseases")
W = tf.Variable(tf.zeros([num_of_features,15]),name="W")
with tf.name_scope('biases'):
print ("b")
#todo:authemate for more diseases
b = tf.Variable(tf.zeros([15]),name="biases")
with tf.name_scope('layer'):
print ("y_train_np")
y_train_np = tf.nn.softmax(tf.matmul(X_np,W) + b)
with tf.name_scope('correct'):
print ("y_ - placeholder for correct answer")
y_ = tf.placeholder(tf.float32, shape=[None, 15],name="correct_answer")
with tf.name_scope('loss'):
print ("cross entrpy")
cross_entropy = -tf.reduce_sum(y_*tf.log(y_train_np))
# % of correct answers found in batch
print("is correct")
is_correct = tf.equal(tf.argmax(y_train_np,1),tf.argmax(y_,1))
print("accuracy")
accuracy = tf.reduce_mean(tf.cast(is_correct,tf.float32))
print("train step")
train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
# train data and get results for batches
print("initialize all varaible")
init = tf.global_variables_initializer()
print("session")
sess = tf.Session()
writer = tf.summary.FileWriter("logs/", sess.graph)
init = tf.global_variables_initializer()
sess.run(init)
!tensorboard --logdir=/logs
the output is:
Starting TensorBoard 41 on port 6006
(You can navigate to http://172.17.0.2:6006)
However, when I click on the link, the webpage is empty
Please let me know what I am missing. I am expecting to see the graph. later i would like to generate more data. Any suggestion is appreciated.
Many thanks!

Answer 1

If you are using datalab, you can use tensorboard as below:
from google.datalab.ml import TensorBoard as tb
tb.start('./logs')
http://googledatalab.github.io/pydatalab/google.datalab.ml.html

Answer 2

You can also create a Cloud AI Platform Notebook instance with TensorBoard support by entering the following command into the Cloud Shell. Afterwards you can simply launch tensorboard when you want from launcher (File->New Launcher-> Tensorboard)
export IMAGE_FAMILY="tf-1-14-cpu"
export ZONE="us-west1-b"
export INSTANCE_NAME="tf-tensorboard-1"
export INSTANCE_TYPE="n1-standard-4"
gcloud compute instances create "${INSTANCE_NAME}" \
--zone="${ZONE}" \
--image-family="${IMAGE_FAMILY}" \
--image-project=deeplearning-platform-release \
--machine-type="${INSTANCE_TYPE}" \
--boot-disk-size=200GB \
--scopes=https://www.googleapis.com/auth/cloud-platform \
--metadata="proxy-mode=project_editors