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!
Use the Google Cloud console To open the Vertex AI TensorBoard UI, click Open TensorBoard next to your experiment.
Datalab was deprecated on September 2, 2022. Vertex AI Workbench provides a notebook-based environment that offers capabilities beyond Datalab. We recommend that you use Vertex AI Workbench for new projects and migrate your Datalab notebooks to Vertex AI Workbench.
Use Cloud Datalab to easily explore, visualize, analyze, and transform data using familiar languages, such as Python and SQL, interactively. Pre-installed Jupyter introductory, sample, and tutorial notebooks, show you how to: Access, analyze, monitor, and visualize data.
There is no charge for using Google Cloud Datalab. However, you do pay for any Google Cloud Platform resources you use with Cloud Datalab, for example: Compute resources: You incur costs from the time of creation to the time of deletion of the Cloud Datalab VM instance.
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
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