tensorboard

问题 How do I install TensorFlow's tensorboard? 回答1: The steps to install Tensorflow are here: https://www.tensorflow.org/install/ For example, on Linux for CPU-only (no GPU), you would type this command: pip install -U pip pip install tensorflow Since TensorFlow depends on TensorBoard, running the following command should not be necessary: pip install tensorboard 回答2: Try typing which tensorboard in your terminal. It should exist if you installed with pip as mentioned in the tensorboard README

问题 How do I install TensorFlow's tensorboard? 回答1: The steps to install Tensorflow are here: https://www.tensorflow.org/install/ For example, on Linux for CPU-only (no GPU), you would type this command: pip install -U pip pip install tensorflow Since TensorFlow depends on TensorBoard, running the following command should not be necessary: pip install tensorboard 回答2: Try typing which tensorboard in your terminal. It should exist if you installed with pip as mentioned in the tensorboard README

问题 I'm working on a segmentation problem in Keras and I want to display segmentation results at the end of every training epoch. I want something similar to Tensorflow: How to Display Custom Images in Tensorboard (e.g. Matplotlib Plots), but using Keras. I know that Keras has the TensorBoard callback but it seems limited for this purpose. I know this would break the Keras backend abstraction, but I'm interested in using TensorFlow backend anyway. Is it possible to achieve that with Keras +

问题 I'm trying to get tensorboard run for a bigger model, I've post the following question . And after doing some research I found the following example my problem is : ............................ # Initializing the variables init = tf.global_variables_initializer() # Create a summary to monitor cost tensor tf.summary.scalar("loss", cost) # Create a summary to monitor accuracy tensor tf.summary.scalar("accuracy", acc) # Merge all summaries into a single op merged_summary_op = tf.summary.merge

问题 I've wrote a Tensorflow program, now I want see what I've done using Tensorboard, here is the interesting part of the code : def train_neural_network(x): prediction = neuronal_network_model(x) tf.summary.scalar('Prediction',prediction) cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=prediction, labels=y)) tf.summary.scalar('cost',cost) # default step size of optimizer is 0.001 optimizer = tf.train.AdamOptimizer(learning_rate=1e-3).minimize(cost) # epoch is feeding forward

问题 I am learning to use Tensorboard -- Tensorflow 2.0. In particular, I would like to monitor the learning curves realtime and also to visually inspect and communicate the architecture of my model. Below I will provide code for a reproducible example. I have three problems: Although I get the learning curves once the training is over I don't know what I should do to monitor them in real time The learning curve I get from Tensorboard does not agree with the plot of history.history. In fact is

问题 When I try to make tensorboard, Syntax error comes out. I can not understand in spite of open source code. I tried to search about code for tensorboard but It's unclear. Even I'm not good at python. I write the path in this way, C:\\Users\\jh902\\Documents\\.logs because I'm using Windows 10 but I'm not sure. (I used double back slash but in this monitor it seems like one slash). If I code like this, tensorboard --logdir="C:\Users\\jh902\\Documents\\.logs" this error message comes out File "

问题 I am trying to visualize the performance of tf.data.Datasets using TF2.0 (Beta). I found examples on how to use profiler in older versions of tensorflow. How is profiling done in TF2.0? I could use tf.compat.v1, but the procedure does not seem to be straight forward. I want to measure memory consumption (device placement wise) and timeline. Below examples explain profiling with TF1.x Can I measure the execution time of individual operations with TensorFlow? Understanding tensorflow profiling

问题 I have tried some tensorboard demo. The code runs fine, and after I ran tensorboard --logdir log/ , I got the following console output which indicates everything is good so far: (dlnd-tf-lab) ->tensorboard --logdir log/ Starting TensorBoard b'47' at http://0.0.0.0:6006 (Press CTRL+C to quit) However, when I copy and paste 'http://0.0.0.0:6006' onto google chrome, I got the following message on the webpage: Access Denied You are not allowed to access this page. Where did I get wrong? Could

问题 My TensorBoard log files grow huge because – it seems – every image summary ever generated is stored. This even though in TensorBoard, it seems like I can only look at the most recent image. And I only need the most recent image anyway. Is there a way to let TensorBoard know that I only need the latest iamge? I looked at the SummaryWriter API docs but there is no obvious flag. 回答1: Hi I work on TensorBoard. To the best of my knowledge, the logs are append only. However when TensorBoard loads