tensorboard | 易学教程

TensorBoard Embedding Example?

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问题 I'm looking for a tensorboard embedding example, with iris data for example like the embedding projector http://projector.tensorflow.org/ But unfortunately i couldn't find one. Just a little bit information about how to do it in https://www.tensorflow.org/how_tos/embedding_viz/ Does someone knows a basic tutorial for this functionality? Basics: 1) Setup a 2D tensor variable(s) that holds your embedding(s). embedding_var = tf.Variable(....) 2) Periodically save your embeddings in a LOG_DIR. 3)

Keras: Add variables to progress bar

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问题 I'd like to monitor eg. the learning rate during training in Keras both in the progress bar and in Tensorboard. I figure there must be a way to specify which variables are logged, but there's no immediate clarification on this issue on the Keras website. I guess it's got something to do with creating a custom Callback function, however, it should be possible to modify the already existing progress bar callback, no? 回答1: It can be achieved via a custom metric. Take the learning rate as an

Logging training and validation loss in tensorboard

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I'm trying to learn how to use tensorflow and tensorboard. I have a test project based on the MNIST neural net tutorial . In my code, I construct a node that calculates the fraction of digits in a data set that are correctly classified, like this: correct = tf.nn.in_top_k(self._logits, labels, 1) correct = tf.to_float(correct) accuracy = tf.reduce_mean(correct) Here, self._logits is the inference part of the graph, and labels is a placeholder that contains the correct labels. Now, what I would like to do is evaluate the accuracy for both the training set and the validation set as training

TensorFlow - Importing data from a TensorBoard TFEvent file?

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I've run several training sessions with different graphs in TensorFlow. The summaries I set up show interesting results in the training and validation. Now, I'd like to take the data I've saved in the summary logs and perform some statistical analysis and in general plot and look at the summary data in different ways. Is there any existing way to easily access this data? More specifically, is there any built in way to read a TFEvent record back into Python? If there is no simple way to do this, TensorFlow states that all its file formats are protobuf files . From my understanding of protobufs

How can I run Tensorboard on a remote server?

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问题 I'm new to Tensorflow and would greatly benefit from some visualizations of what I'm doing. I understand that Tensorboard is a useful visualization tool, but how do I run it on my remote Ubuntu machine? 回答1: Here is what I do to avoid the issues of making the remote server accept your local external IP: when I ssh into the machine, I use the option -L to transfer the port 6006 of the remote server into the port 16006 of my machine (for instance): ssh -L 16006:127.0.0.1:6006 olivier@my_server

How do I add an arbitrary value to a TensorFlow summary?

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In order to log a simple value val to a TensorBoard summary I need to val = 5 test_writer.add_summary(sess.run(tf.scalar_summary('test', val)), global_step) Is sess.run(tf.scalar_summary('test', val)) really necessary to get val added as a summary? You can construct the summary by yourself, like from tensorflow.core.framework import summary_pb2 value = summary_pb2.Summary.Value(tag="Accuracy", simple_value=0.95) summary = summary_pb2.Summary(value=[value]) you can then add summary using add_summary like in your code. Here's another (perhaps slightly more up-to-date) solution with the tf

Error when computing summaries in TensorFlow

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问题 I am trying to use TensorFlow to produce summaries and visualize them using TensorBoard. However, I am getting an error ( InvalidArgumentError: You must feed a value for placeholder tensor 'Placeholder_1' with dtype float ) that I do not understand. This is the full source of my program: from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) import tensorflow as tf x = tf.placeholder(tf.float32, [None, 784]) W = tf.Variable(tf

How to display the average of multiple runs on tensorboard

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问题 Is there a way to display the average of multiple different runs on tensorflow? I can only see them on the same graph (by sending the path of the different runs), but I want to see their average on the graph 回答1: Please follow issue 376 to see progress on this. It's an active feature request with some progress in the last month, but as of now, there's not a way to do what you want. Yet. 回答2: As @dga mentioned this is not implemented yet. Here is some code that uses EventAccumulator to combine

Install Tensorflow with Quantization Support

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问题 This is a follow-up of another question by me : Error with 8-bit Quantization in Tensorflow Basically, I would like to install the Tensorflow with 8-bit quantization support. Currently, I installed Tensorflow 0.9 with pip installation method on CentOS 7 machine (without GPU support). I could compile and run the codes as given in Pete Warden's blog post. But, I can't import the functions given in Pete Warden's reply. I would like to add the quantization support. I couldn't find any details

View Tensorboard on Docker on Google Cloud

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I am trying to display TensorBoard from TensorFlow on Docker on Google Cloud. http://tensorflow.org/how_tos/summaries_and_tensorboard/index.md tensorboard --logdir ./ I have Apache running on Google Cloud (it may be in my first container "ai-unicorn" Docker made its own container "docker-playground"). I can see the default page from Google Cloud at http://104.197.119.57/ . I start TensorBoard on Google Cloud like this: root@6cf64fd299f0:/# tensorboard --logdir ./ Starting TensorBoard on port 6006 (You can navigate to http://localhost:6006) I tried the Google Cloud SSH option called "Open in