Question

我需要帮助从数据库上运行的tensorflow中获取张量板，我的代码如下（一切都在datalab上）：

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

输出是：在端口6006上启动TensorBoard 41 （您可以导航到http://172.17.0.2:6006）

但是，当我点击链接时，网页为空

请让我知道我错过了什么。我期待看到图表。后来我想生成更多数据。任何建议都表示赞赏。

非常感谢！

Answer 1

如果您使用的是datalab，可以使用如下的tensorboard：

UITextView

http://googledatalab.github.io/pydatalab/google.datalab.ml.html

Answer 2

您还可以通过在Cloud Shell中输入以下命令来创建具有TensorBoard支持的Cloud AI Platform Notebook实例。然后，您可以根据需要从启动器中启动tensorboard（文件->新启动器-> 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

从谷歌云数据库中启动张量板

2 个答案: