Description: Make within-documentation links local Links were found by find doc -iname "*.ipynb" -print0 | xargs -0 sed -i -E -e "s=https?://deeplearning.net/software/theano/==g" find doc -iname "*.txt" -print0 | xargs -0 sed -i -E -e "s= Forwarded: no Last-Update: 2018-03-18 --- theano-1.0.1+dfsg.orig/README.rst +++ theano-1.0.1+dfsg/README.rst @@ -8,6 +8,8 @@ To install the package, see this page: For the documentation, see the project website: http://deeplearning.net/software/theano/ +or if the theano-doc package is installed, the local copy: + file:///usr/share/doc/theano-doc/html/ Related Projects: https://github.com/Theano/Theano/wiki/Related-projects --- theano-1.0.1+dfsg.orig/doc/index.txt +++ theano-1.0.1+dfsg/doc/index.txt @@ -156,7 +156,7 @@ Roughly in order of what you'll want to * :ref:`acknowledgement` -- What we took from other projects. * `Related Projects`_ -- link to other projects that implement new functionalities on top of Theano -You can download the latest `PDF documentation `_, rather than reading it online. +This documentation is `also available in PDF format `_. Check out how Theano can be used for Machine Learning: `Deep Learning Tutorials `_. @@ -224,7 +224,7 @@ It's often helpful to include the follow * If you have an error, the *full* error message, even if it's long * Which versions of Python and Theano you're using * Whether you're using a CPU or GPU device -* Details of your Theano configuration settings (you can print this in Python via `print theano.config `__) +* Details of your Theano configuration settings (you can print this in Python via `print theano.config `__) Spending the time to create a minimal specific example of a problem is likely to get you to an answer quicker than posting something quickly that has too much irrelevant detail or is too vague. A minimal example may take you a bit more --- theano-1.0.1+dfsg.orig/doc/introduction.txt +++ theano-1.0.1+dfsg/doc/introduction.txt @@ -134,7 +134,7 @@ Getting started A PDF version of the online documentation may be found `here -`_. +`_. Theano Vision --- theano-1.0.1+dfsg.orig/doc/library/d3viz/index.ipynb +++ theano-1.0.1+dfsg/doc/library/d3viz/index.ipynb @@ -38,7 +38,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Like Theano’s [printing module](http://deeplearning.net/software/theano/library/printing.html), ``d3viz``\n", + "Like Theano’s [printing module](file:///usr/share/doc/theano-doc/html/library/printing.html), ``d3viz``\n", "requires [graphviz](http://www.graphviz.org) binary to be available." ] }, @@ -53,7 +53,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "`d3viz` extends Theano’s [printing module](http://deeplearning.net/software/theano/library/printing.html) to interactively visualize compute graphs. Instead of creating a static picture, it creates an HTML file, which can be opened with current web-browsers. `d3viz` allows\n", + "`d3viz` extends Theano’s [printing module](file:///usr/share/doc/theano-doc/html/library/printing.html) to interactively visualize compute graphs. Instead of creating a static picture, it creates an HTML file, which can be opened with current web-browsers. `d3viz` allows\n", "\n", "* to zoom to different regions and to move graphs via drag and drop,\n", "* to position nodes both manually and automatically,\n", @@ -264,7 +264,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Theano allows [function profiling](http://deeplearning.net/software/theano/tutorial/profiling.html) via the `profile=True` flag. After at least one function call, the compute time of each node can be printed in text form with `debugprint`. However, analyzing complex graphs in this way can be cumbersome.\n", + "Theano allows [function profiling](file:///usr/share/doc/theano-doc/html/tutorial/profiling.html) via the `profile=True` flag. After at least one function call, the compute time of each node can be printed in text form with `debugprint`. However, analyzing complex graphs in this way can be cumbersome.\n", "\n", "`d3viz` can visualize the same timing information graphically, and hence help to spot bottlenecks in the compute graph more easily! To begin with, we will redefine the `predict` function, this time by using `profile=True` flag. Afterwards, we capture the runtime on random data:" ] @@ -378,7 +378,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "An [OpFromGraph](http://deeplearning.net/software/theano/library/compile/opfromgraph.html) node defines a new operation, which can be called with different inputs at different places in the compute graph. Each `OpFromGraph` node defines a nested graph, which will be visualized accordingly by `d3viz`." + "An [OpFromGraph](file:///usr/share/doc/theano-doc/html/library/compile/opfromgraph.html) node defines a new operation, which can be called with different inputs at different places in the compute graph. Each `OpFromGraph` node defines a nested graph, which will be visualized accordingly by `d3viz`." ] }, { --- theano-1.0.1+dfsg.orig/doc/library/d3viz/index.txt +++ theano-1.0.1+dfsg/doc/library/d3viz/index.txt @@ -23,14 +23,14 @@ maintained, and it works both in Python pip install pydot-ng Like Theano’s `printing module -`__, ``d3viz`` +<../printing.html>`__, ``d3viz`` requires `graphviz `__ binary to be available. Overview -------- ``d3viz`` extends Theano’s `printing -module `__ +module <../printing.html>`__ to interactively visualize compute graphs. Instead of creating a static picture, it creates an HTML file, which can be opened with current web-browsers. ``d3viz`` allows @@ -143,7 +143,7 @@ Profiling --------- Theano allows `function -profiling `__ +profiling <../../tutorial/profiling.html>`__ via the ``profile=True`` flag. After at least one function call, the compute time of each node can be printed in text form with ``debugprint``. However, analyzing complex graphs in this way can be @@ -210,7 +210,7 @@ OpFromGraph nodes ----------------- An -`OpFromGraph `__ +`OpFromGraph <../compile/opfromgraph.html>`__ node defines a new operation, which can be called with different inputs at different places in the compute graph. Each ``OpFromGraph`` node defines a nested graph, which will be visualized accordingly by --- theano-1.0.1+dfsg.orig/doc/library/sparse/index.txt +++ theano-1.0.1+dfsg/doc/library/sparse/index.txt @@ -27,7 +27,7 @@ This section tries to explain how inform sparse formats of SciPy supported by Theano. There are more formats that can be used with SciPy and some documentation about them may be found `here -`_. +<../../sandbox/sparse.html>`_. .. Changes to this section should also result in changes to tutorial/sparse.txt. --- theano-1.0.1+dfsg.orig/doc/tutorial/shape_info.txt +++ theano-1.0.1+dfsg/doc/tutorial/shape_info.txt @@ -15,7 +15,7 @@ Currently, information regarding shape i - To remove computations in the graph when we only want to know the shape, but not the actual value of a variable. This is done with the - `Op.infer_shape `_ + `Op.infer_shape <../extending/cop.html#Op.infer_shape>`_ method. Example: