I am increasingly irritated and frustrated by the Tensorflow documentation. I searched on google for documentation regarding
tf.reshape
I'm getting directed to a generic page like here. I want to see the details of tf.reshape and not the entirety of the documentation.
Am I doing something wrong here?
Do not Google about Tensorflow documentation, use the TensorFlow Python reference documentation and ctrl + f
The probably fastest way is to use the Tf documentation is:
http://devdocs.io/tensorflow~python/
Just type tf.reshape and you are done.
which can be also used offline and automatically updates the docs.
edit: even typing only res shows you the documentation.
Update for posterity:
With the new TensorFlow, the website is now indexed with Google, and it should also soon be indexed by other search engines.
I would suggest you use the GitHub repo as your documentation instead. https://github.com/tensorflow/tensorflow/tree/master/tensorflow/g3doc/api_docs/python/functions_and_classes
For example tf.reshape is in a single Markdown file https://github.com/tensorflow/tensorflow/blob/master/tensorflow/g3doc/api_docs/python/functions_and_classes/shard0/tf.reshape.md
To search for the document you want, you could use the GitHub search under that functions_and_classes folder.
An example is
tf.reshape() path:tensorflow/g3doc/api_docs/python/functions_and_classes language:Markdown
https://github.com/tensorflow/tensorflow/search?utf8=✓&q=tf.reshape%28%29+path%3Atensorflow%2Fg3doc%2Fapi_docs%2Fpython%2Ffunctions_and_classes+language%3AMarkdown&type=Code
which search for tf.reshape() under the documentation folder.
I use the non-official Dash/Zeal docset for TensorFlow:
https://github.com/ppwwyyxx/dash-docset-tensorflow
It is a very convenient way of browsing the TensorFlow documentation offline and it solves the problem you are describing.
Is this what you are looking for? Using the search functionality of the browser helped me find it.
I suppose that you have installed tensorflow in your computer and that you know the name of function that you may want to use.
So if you use some Python IDE, I think you can directly jump to the declaration or definition of this function and see the usage and explanation. That is the same documentation as online (although for some functions it is not very clear).
You can use the url for tensorflow documentation and add what you want to search..
The base url is:
https://www.tensorflow.org/api_docs/python/tf/
You can add what_ever_you_want_to_search after the /
Since Tensorflow r1.1 a search on google for items like 'tf.shape' now lists the appropriate page at the top of the search results.
This didn't work back in r0.10 and r0.11, maybe because there were many markdown formatting issues in the Tensorflow docs themselves.
Since you tf is developing best way is to go through the tf API. And it's good if you can follow these slides in http://web.stanford.edu/class/cs20si/
Related
I try to migrate my code from tf1.* to tf2, while in tf2 doc it says that tf.compat.v1.metrics.auc is deprecated because "The value of AUC returned by this may race with the update". This statement is vague to me. Does it mean that it can't be used in multithreading context? If not, in what situation can I use this function?
tf.compat.v1.metrics.auc has been moved under tf.keras.
As mentioned in the error message itself you can start using tf.keras.metrics.AUC in Tf2.
There are some changes in hyper parameters in the updated version, details with the example can be found in the above mentioned document.
I am new to Pandas, trying to learn the basics from lecture videos. In one of these the presenter demonstrates that one can call help on methods using ??.
For example if I have loaded a dataframe df then typing df.getitem?? should print the docstring as well as the source code to the console. This would be really great to have but it doesn't work for me! I tried different variants of the command and also tried to find a comment online on this, without success.
What do I need to type in order to retrieve the docstring as well as the source code of a Pandas method? Thanks a lot for your help !
(I am using Python 3.5 and PyCharm in case that makes a difference)
I believe that your lecturer was using ipython as this does support dynamic object information. For instance this is the output in ipython when you do df.__getitem__?? you see the following:
I strongly recommend ipython for interactive python development, you'll find a lot of devs using this for data exploration and analysis, the workbook is really useful for saving your commands and the output
Is there any documentation about ScriptedPatchRequest on ravendb?
I could only find something here: http://ravendb.net/docs/2.0/faq/denormalized-updates
I want to use this nice feature but don't know about the other methods like "LoadDocument" that are available through javascript patch.
See the docs here: http://ravendb.net/docs/2.5/client-api/partial-document-updates
And here is a bunch more text that SO requires me to put in.
Currently I am trying to use Magma to do matrix operation on GPU, however, I found few documents about it. The only thing I can refer to is its testing program and the online generated document(here), which is not convenient to use. And the user guide seems outdated.
If you look here, getri and potri are supported.
I have been an IDL programmer for sometime now and looking to transition to Python. I find that MPFIT's IDL version exists in Python. However, I am looking for MPFITFUN version in Python (http://www.physics.wisc.edu/~craigm/idl/down/mpfitfun.pro) or something similar.
Basically, I am looking for a Python function that takes a user-defined function and uses like Levenberg-Marquardt least-squared fit (like MPFIT).
Thanks,
There are fitting functions built into SciPy but I do not know of any which account for uncertainties in data as MPFITFUN does.
I have found Sherpa to be an excellent modeling and fitting package for Python which accounts for uncertainties and replaces MPFITFUN: http://cxc.harvard.edu/contrib/sherpa/
Since Sherpa is produced by astronomers it has a lot of built in astrophysical models, but you can build your own function to fit with Sherpa's Levenberg-Marquardt, Nelder-Mead or Monte Carlo algorithms. I used the template from the pysherpa blog:
http://pysherpa.blogspot.com/2010/06/user-defined-sherpa-model-types-using.html
mpfit.py is available from https://code.google.com/p/astrolibpy/ and an older version hosted at http://cars.uchicago.edu/software/python/mpfit.html.
A good alternative is lmfit: https://pypi.python.org/pypi/lmfit/, https://github.com/lmfit/lmfit-py, http://lmfit.github.io//lmfit-py/
I accidentally found that there also exists the MPFITEXPR in Python. Here's the link to the code. You can also download it via Astrolibpy project.
Link:
https://code.google.com/p/astrolibpy/source/browse/mpfit/mpfitexpr.py?r=3545675a0662392e3e09c88beaf275c9e7881cf6