Update sphinx doc

doc/library/d3viz/examples/mlp2.html

@@ -23,7 +23,7 @@
 
 	<script type="text/javascript">
 		// Backend graph in DOT format
-		var dotGraph = graphlibDot.read("digraph G {	graph [bb=\"0,0,272,476\"];	node [label=\"\N\"];	n1	 [apply_op=\"InplaceDimShuffle{x,0}\",		height=0.5,		label=DimShuffle,		node_type=apply,		pos=\"219,370\",		profile=\"4.05311584473e-06	0.0024139881134\",		shape=ellipse,		width=1.4763];	n8	 [apply_op=\"Elemwise{Composite{scalar_sigmoid((i0 + i1))}}[(0, 0)]\",		fillcolor=\"#FFAABB\",		height=0.5,		label=Elemwise,		node_type=apply,		pos=\"170,282\",		profile=\"0.000680923461914	0.0024139881134\",		shape=ellipse,		style=filled,		type=colored,		width=1.2888];	n1 -> n8	 [label=\"1 dmatrix\",		lp=\"225.5,326\",		pos=\"e,179.49,299.66 209.32,352.01 202.23,339.56 192.48,322.45 184.47,308.39\"];	n2	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"219,458\",		shape=box,		style=filled,		width=0.80556];	n2 -> n1	 [color=dodgerblue,		label=dvector,		lp=\"240,414\",		pos=\"e,219,388.08 219,439.6 219,427.75 219,411.82 219,398.29\"];	n4	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"114,370\",		profile=\"0.00137615203857	0.0024139881134\",		shape=ellipse,		width=0.92774];	n4 -> n8	 [color=red,		label=\"0 dmatrix\",		lp=\"158.5,326\",		pos=\"e,148.95,298.37 117.35,351.95 119.93,341.54 124.24,328.3 131,318 133.92,313.55 137.54,309.31 141.39,305.41\"];	n5	 [dtype=dmatrix,		fillcolor=limegreen,		height=0.5,		label=x,		node_type=input,		pos=\"50,458\",		shape=box,		style=filled,		width=0.75];	n5 -> n4	 [label=\"0 dmatrix\",		lp=\"88.5,414\",		pos=\"e,89.174,382.09 50.492,439.64 51.537,429.12 54.251,415.87 61,406 66.011,398.67 73.111,392.49 80.491,387.46\"];	n6	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"128,458\",		shape=box,		style=filled,		width=0.83333];	n6 -> n4	 [label=\"1 dmatrix\",		lp=\"149.5,414\",		pos=\"e,116.78,388.08 125.17,439.6 123.24,427.75 120.64,411.82 118.44,398.29\"];	n10	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"118,194\",		profile=\"0.00012993812561	0.0024139881134\",		shape=ellipse,		width=0.92774];	n8 -> n10	 [label=\"0 dmatrix\",		lp=\"175.5,238\",		pos=\"e,127.82,211.24 159.97,264.42 152.37,251.85 141.8,234.35 133.16,220.07\"];	n13	 [apply_op=SoftmaxWithBias,		height=0.5,		label=SoftmaxWithBias,		node_type=apply,		pos=\"76,106\",		profile=\"0.00015115737915	0.0024139881134\",		shape=ellipse,		width=2.1117];	n10 -> n13	 [label=\"0 dmatrix\",		lp=\"128.5,150\",		pos=\"e,84.361,124.12 109.9,176.42 103.94,164.2 95.704,147.35 88.845,133.3\"];	n11	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"75,282\",		shape=box,		style=filled,		width=0.83333];	n11 -> n10	 [label=\"1 dmatrix\",		lp=\"111.5,238\",		pos=\"e,100.16,209.41 75.526,263.66 76.44,253.4 78.677,240.41 84,230 86.398,225.31 89.636,220.84 93.164,216.75\"];	n15	 [dtype=dmatrix,		fillcolor=dodgerblue,		height=0.5,		label=dmatrix,		node_type=output,		pos=\"76,18\",		shape=box,		style=filled,		width=0.83333];	n13 -> n15	 [label=dmatrix,		lp=\"98,62\",		pos=\"e,76,36.084 76,87.597 76,75.746 76,59.817 76,46.292\"];	n14	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"37,194\",		shape=box,		style=filled,		width=0.80556];	n14 -> n13	 [label=\"1 dvector\",		lp=\"66.5,150\",		pos=\"e,53.961,123.42 34.978,175.72 34.504,165.47 35.203,152.48 40,142 41.795,138.08 44.242,134.36 47.022,130.92\"];}");
+		var dotGraph = graphlibDot.read("digraph G {	graph [bb=\"0,0,272,476\"];	node [label=\"\N\"];	n1	 [apply_op=\"InplaceDimShuffle{x,0}\",		height=0.5,		label=DimShuffle,		node_type=apply,		pos=\"219,370\",		profile=\"2.86102294922e-06	0.00189995765686\",		shape=ellipse,		width=1.4763];	n8	 [apply_op=\"Elemwise{Composite{scalar_sigmoid((i0 + i1))}}[(0, 0)]\",		fillcolor=\"#FFAABB\",		height=0.5,		label=Elemwise,		node_type=apply,		pos=\"170,282\",		profile=\"0.000599145889282	0.00189995765686\",		shape=ellipse,		style=filled,		type=colored,		width=1.2888];	n1 -> n8	 [label=\"1 dmatrix\",		lp=\"225.5,326\",		pos=\"e,179.49,299.66 209.32,352.01 202.23,339.56 192.48,322.45 184.47,308.39\"];	n2	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"219,458\",		shape=box,		style=filled,		width=0.80556];	n2 -> n1	 [color=dodgerblue,		label=dvector,		lp=\"240,414\",		pos=\"e,219,388.08 219,439.6 219,427.75 219,411.82 219,398.29\"];	n4	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"114,370\",		profile=\"0.000936031341553	0.00189995765686\",		shape=ellipse,		width=0.92774];	n4 -> n8	 [color=red,		label=\"0 dmatrix\",		lp=\"158.5,326\",		pos=\"e,148.95,298.37 117.35,351.95 119.93,341.54 124.24,328.3 131,318 133.92,313.55 137.54,309.31 141.39,305.41\"];	n5	 [dtype=dmatrix,		fillcolor=limegreen,		height=0.5,		label=x,		node_type=input,		pos=\"50,458\",		shape=box,		style=filled,		width=0.75];	n5 -> n4	 [label=\"0 dmatrix\",		lp=\"88.5,414\",		pos=\"e,89.174,382.09 50.492,439.64 51.537,429.12 54.251,415.87 61,406 66.011,398.67 73.111,392.49 80.491,387.46\"];	n6	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"128,458\",		shape=box,		style=filled,		width=0.83333];	n6 -> n4	 [label=\"1 dmatrix\",		lp=\"149.5,414\",		pos=\"e,116.78,388.08 125.17,439.6 123.24,427.75 120.64,411.82 118.44,398.29\"];	n10	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"118,194\",		profile=\"0.000121116638184	0.00189995765686\",		shape=ellipse,		width=0.92774];	n8 -> n10	 [label=\"0 dmatrix\",		lp=\"175.5,238\",		pos=\"e,127.82,211.24 159.97,264.42 152.37,251.85 141.8,234.35 133.16,220.07\"];	n13	 [apply_op=SoftmaxWithBias,		height=0.5,		label=SoftmaxWithBias,		node_type=apply,		pos=\"76,106\",		profile=\"0.000172853469849	0.00189995765686\",		shape=ellipse,		width=2.1117];	n10 -> n13	 [label=\"0 dmatrix\",		lp=\"128.5,150\",		pos=\"e,84.361,124.12 109.9,176.42 103.94,164.2 95.704,147.35 88.845,133.3\"];	n11	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"75,282\",		shape=box,		style=filled,		width=0.83333];	n11 -> n10	 [label=\"1 dmatrix\",		lp=\"111.5,238\",		pos=\"e,100.16,209.41 75.526,263.66 76.44,253.4 78.677,240.41 84,230 86.398,225.31 89.636,220.84 93.164,216.75\"];	n15	 [dtype=dmatrix,		fillcolor=dodgerblue,		height=0.5,		label=dmatrix,		node_type=output,		pos=\"76,18\",		shape=box,		style=filled,		width=0.83333];	n13 -> n15	 [label=dmatrix,		lp=\"98,62\",		pos=\"e,76,36.084 76,87.597 76,75.746 76,59.817 76,46.292\"];	n14	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"37,194\",		shape=box,		style=filled,		width=0.80556];	n14 -> n13	 [label=\"1 dvector\",		lp=\"66.5,150\",		pos=\"e,53.961,123.42 34.978,175.72 34.504,165.47 35.203,152.48 40,142 41.795,138.08 44.242,134.36 47.022,130.92\"];}");
 		// Frontend graph for visualization
 		var graph = {};
 		

doc/library/d3viz/index.ipynb

@@ -173,7 +173,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[open](examples/mlp.html)"
+    "[Open visualization!](examples/mlp.html)"
    ]
   },
   {
@@ -228,7 +228,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[open](./examples/mlp2.html)"
+    "[Open visualization!](./examples/mlp2.html)"
    ]
   },
   {
@@ -264,7 +264,7 @@
     "pydot_graph = formatter(predict_profiled)\n",
     "\n",
     "pydot_graph.write_png('examples/mlp2.png');\n",
-    "pydot_graph.write_png('examples/mlp2.pdf');"
+    "pydot_graph.write_pdf('examples/mlp2.pdf');"
    ]
   },
   {
@@ -294,7 +294,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here, we used the `PyDotFormatter` class to convert the compute graph into a `pydot` graph, and created a PNG and PDF file. You can find all output formats supported by Graphviz [here](http://www.graphviz.org/doc/info/output.html)."
+    "Here, we used the `PyDotFormatter` class to convert the compute graph into a `pydot` graph, and created a [PNG](./examples/mlp2.png) and [PDF](./examples/mlp2.pdf) file. You can find all output formats supported by Graphviz [here](http://www.graphviz.org/doc/info/output.html)."
    ]
   },
   {
@@ -342,7 +342,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[open](./examples/ofg.html)"
+    "[Open visualization!](./examples/ofg.html)"
    ]
   },
   {
@@ -388,7 +388,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "[open](./examples/ofg2.html)"
+    "[Open visualization!](./examples/ofg2.html)"
    ]
   },
   {
@@ -406,7 +406,7 @@
     "\n",
     "* Christof Angermueller\n",
     "* <cangermueller@gmail.com>\n",
-    "* http://cangermueller.com"
+    "* https://cangermueller.com"
    ]
   }
  ],

doc/library/d3viz/index.txt

@@ -174,6 +174,7 @@ export graps to different formats.
     pydot_graph = formatter(predict_profiled)
     
     pydot_graph.write_png('examples/mlp2.png');
+    pydot_graph.write_png('examples/mlp2.pdf');
 
 .. code:: python
 
@@ -183,9 +184,9 @@ export graps to different formats.
 .. image:: index_files/index_24_0.png
 
 
-
 Here, we used the :py:class:`theano.d3viz.formatting.PyDotFormatter` class to
-convert the compute graph into a ``pydot`` graph, and created a PNG and PDF
+convert the compute graph into a ``pydot`` graph, and created a
+:download:`PNG <examples/mlp2.png>` and :download:`PDF <examples/mlp2.pdf>`
 file. You can find all output formats supported by Graphviz `here
 <http://www.graphviz.org/doc/info/output.html>`__.