提交 f2ff5a87 authored 作者: Christof Angermueller's avatar Christof Angermueller

Update sphinx doc

上级 08c42a19
......@@ -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 = {};
......
......@@ -23,7 +23,7 @@
<script type="text/javascript">
// Backend graph in DOT format
var dotGraph = graphlibDot.read("digraph G { graph [bb=\"0,0,877.01,316\"]; node [label=\"\N\"]; subgraph cluster_n1 { graph [bb=\"413.01,80,637.01,308\"]; n11 [apply_op=\"Elemwise{Composite{scalar_sigmoid(sqr((i0 + i1 + i2)))}}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"510.01,194\", shape=ellipse, style=filled, type=colored, width=1.2888]; n15 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"510.01,106\", shape=box, style=filled, width=0.75]; n11 -> n15 [label=fscalar, lp=\"529.01,150\", pos=\"e,510.01,124.08 510.01,175.6 510.01,163.75 510.01,147.82 510.01,134.29\"]; n12 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"592.01,282\", shape=box, style=filled, width=0.75]; n12 -> n11 [label=\"0 fscalar\", lp=\"596.01,238\", pos=\"e,534.12,209.56 583.05,263.78 577.09,253.31 568.62,240.07 559.01,230 554.11,224.87 548.36,220 542.56,215.61\"]; n13 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"520.01,282\", shape=box, style=filled, width=0.75]; n13 -> n11 [label=\"1 fscalar\", lp=\"535.01,238\", pos=\"e,509.36,212.08 514.71,263.71 513.23,258.11 511.8,251.84 511.01,246 509.95,238.28 509.51,229.84 509.37,222.09\"]; n14 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"448.01,282\", shape=box, style=filled, width=0.75]; n14 -> n11 [label=\"2 fscalar\", lp=\"482.01,238\", pos=\"e,481.77,208.39 448.14,263.68 448.97,253.17 451.42,239.92 458.01,230 462.06,223.89 467.58,218.57 473.52,214.05\"]; } subgraph cluster_n7 { graph [bb=\"645.01,80,869.01,308\"]; n71 [apply_op=\"Elemwise{Composite{scalar_sigmoid(sqr((i0 + i1 + i2)))}}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"742.01,194\", shape=ellipse, style=filled, type=colored, width=1.2888]; n75 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"742.01,106\", shape=box, style=filled, width=0.75]; n71 -> n75 [label=fscalar, lp=\"761.01,150\", pos=\"e,742.01,124.08 742.01,175.6 742.01,163.75 742.01,147.82 742.01,134.29\"]; n72 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"824.01,282\", shape=box, style=filled, width=0.75]; n72 -> n71 [label=\"0 fscalar\", lp=\"828.01,238\", pos=\"e,766.12,209.56 815.05,263.78 809.09,253.31 800.62,240.07 791.01,230 786.11,224.87 780.36,220 774.56,215.61\"]; n73 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"752.01,282\", shape=box, style=filled, width=0.75]; n73 -> n71 [label=\"1 fscalar\", lp=\"767.01,238\", pos=\"e,741.36,212.08 746.71,263.71 745.23,258.11 743.8,251.84 743.01,246 741.95,238.28 741.51,229.84 741.37,222.09\"]; n74 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"680.01,282\", shape=box, style=filled, width=0.75]; n74 -> n71 [label=\"2 fscalar\", lp=\"714.01,238\", pos=\"e,713.77,208.39 680.14,263.68 680.97,253.17 683.42,239.92 690.01,230 694.06,223.89 699.58,218.57 705.52,214.05\"]; } n1 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10ff43fd0\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"217.01,194\", shape=ellipse, subg=cluster_n1, subg_map_inputs=\"[[\'n2\', \'n13\'], [\'n3\', \'n14\'], [\'n4\', \'n12\']]\", subg_map_outputs=\"[[\'n15\', \'n6\']]\", width=1.7826]; n6 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"153.01,106\", shape=ellipse, style=filled, type=colored, width=1.2888]; n1 -> n6 [label=\"1 fscalar\", lp=\"215.01,150\", pos=\"e,165.19,123.37 204.36,176.01 194.95,163.36 181.96,145.9 171.4,131.71\"]; n2 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"55.007,282\", shape=box, style=filled, width=0.75]; n2 -> n1 [label=\"0 fscalar\", lp=\"175.01,238\", pos=\"e,188.78,210.26 82.101,266.93 94.312,260.57 108.9,252.94 122.01,246 141.17,235.85 162.43,224.45 179.98,215\"]; n7 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10ff43fd0\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"70.007,194\", shape=ellipse, subg=cluster_n7, subg_map_inputs=\"[[\'n4\', \'n73\'], [\'n3\', \'n74\'], [\'n2\', \'n72\']]\", subg_map_outputs=\"[[\'n75\', \'n6\']]\", width=1.7826]; n2 -> n7 [label=\"2 fscalar\", lp=\"27.007,238\", pos=\"e,28.697,207.85 27.721,268.8 10.72,259.37 -6.2971,245.36 3.007,230 7.1667,223.13 13.164,217.55 19.883,213.03\"]; n3 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"304.01,282\", shape=box, style=filled, width=0.75]; n3 -> n1 [label=\"1 fscalar\", lp=\"363.01,238\", pos=\"e,279.27,198.73 325,263.94 334.94,253.78 343.06,240.79 335.01,230 323.95,215.19 306.9,206.39 289.16,201.24\"]; n3 -> n7 [label=\"1 fscalar\", lp=\"304.01,238\", pos=\"e,116.87,206.31 294.23,263.96 286.68,252.44 275.15,237.94 261.01,230 215.13,204.25 195.68,221.9 144.01,212 138.37,210.92 132.5,209.72 \126.66,208.46\"]; n4 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"197.01,282\", shape=box, style=filled, width=0.75]; n4 -> n1 [label=\"2 fscalar\", lp=\"233.01,238\", pos=\"e,213.03,212.08 201.05,263.6 203.84,251.63 207.59,235.5 210.75,221.89\"]; n4 -> n7 [label=\"0 fscalar\", lp=\"98.007,238\", pos=\"e,66.731,212.43 169.97,281.61 141.33,280.65 97.14,274.26 74.007,246 68.707,239.52 66.766,230.91 66.43,222.6\"]; n7 -> n6 [color=red, label=\"0 fscalar\", lp=\"143.01,150\", pos=\"e,137.33,123.24 86.01,176.42 98.606,163.37 116.32,145.01 130.37,130.46\"]; n9 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"153.01,18\", shape=box, style=filled, width=0.75]; n6 -> n9 [label=fscalar, lp=\"172.01,62\", pos=\"e,153.01,36.084 153.01,87.597 153.01,75.746 153.01,59.817 153.01,46.292\"];}");
var dotGraph = graphlibDot.read("digraph G { graph [bb=\"0,0,877.01,316\"]; node [label=\"\N\"]; subgraph cluster_n1 { graph [bb=\"413.01,80,637.01,308\"]; n11 [apply_op=\"Elemwise{Composite{scalar_sigmoid(sqr((i0 + i1 + i2)))}}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"510.01,194\", shape=ellipse, style=filled, type=colored, width=1.2888]; n15 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"510.01,106\", shape=box, style=filled, width=0.75]; n11 -> n15 [label=fscalar, lp=\"529.01,150\", pos=\"e,510.01,124.08 510.01,175.6 510.01,163.75 510.01,147.82 510.01,134.29\"]; n12 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"592.01,282\", shape=box, style=filled, width=0.75]; n12 -> n11 [label=\"0 fscalar\", lp=\"596.01,238\", pos=\"e,534.12,209.56 583.05,263.78 577.09,253.31 568.62,240.07 559.01,230 554.11,224.87 548.36,220 542.56,215.61\"]; n13 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"520.01,282\", shape=box, style=filled, width=0.75]; n13 -> n11 [label=\"1 fscalar\", lp=\"535.01,238\", pos=\"e,509.36,212.08 514.71,263.71 513.23,258.11 511.8,251.84 511.01,246 509.95,238.28 509.51,229.84 509.37,222.09\"]; n14 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"448.01,282\", shape=box, style=filled, width=0.75]; n14 -> n11 [label=\"2 fscalar\", lp=\"482.01,238\", pos=\"e,481.77,208.39 448.14,263.68 448.97,253.17 451.42,239.92 458.01,230 462.06,223.89 467.58,218.57 473.52,214.05\"]; } subgraph cluster_n7 { graph [bb=\"645.01,80,869.01,308\"]; n71 [apply_op=\"Elemwise{Composite{scalar_sigmoid(sqr((i0 + i1 + i2)))}}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"742.01,194\", shape=ellipse, style=filled, type=colored, width=1.2888]; n75 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"742.01,106\", shape=box, style=filled, width=0.75]; n71 -> n75 [label=fscalar, lp=\"761.01,150\", pos=\"e,742.01,124.08 742.01,175.6 742.01,163.75 742.01,147.82 742.01,134.29\"]; n72 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"824.01,282\", shape=box, style=filled, width=0.75]; n72 -> n71 [label=\"0 fscalar\", lp=\"828.01,238\", pos=\"e,766.12,209.56 815.05,263.78 809.09,253.31 800.62,240.07 791.01,230 786.11,224.87 780.36,220 774.56,215.61\"]; n73 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"752.01,282\", shape=box, style=filled, width=0.75]; n73 -> n71 [label=\"1 fscalar\", lp=\"767.01,238\", pos=\"e,741.36,212.08 746.71,263.71 745.23,258.11 743.8,251.84 743.01,246 741.95,238.28 741.51,229.84 741.37,222.09\"]; n74 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"680.01,282\", shape=box, style=filled, width=0.75]; n74 -> n71 [label=\"2 fscalar\", lp=\"714.01,238\", pos=\"e,713.77,208.39 680.14,263.68 680.97,253.17 683.42,239.92 690.01,230 694.06,223.89 699.58,218.57 705.52,214.05\"]; } n1 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10f204b10\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"217.01,194\", shape=ellipse, subg=cluster_n1, subg_map_inputs=\"[[\'n2\', \'n13\'], [\'n3\', \'n14\'], [\'n4\', \'n12\']]\", subg_map_outputs=\"[[\'n15\', \'n6\']]\", width=1.7826]; n6 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"153.01,106\", shape=ellipse, style=filled, type=colored, width=1.2888]; n1 -> n6 [label=\"1 fscalar\", lp=\"215.01,150\", pos=\"e,165.19,123.37 204.36,176.01 194.95,163.36 181.96,145.9 171.4,131.71\"]; n2 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"55.007,282\", shape=box, style=filled, width=0.75]; n2 -> n1 [label=\"0 fscalar\", lp=\"175.01,238\", pos=\"e,188.78,210.26 82.101,266.93 94.312,260.57 108.9,252.94 122.01,246 141.17,235.85 162.43,224.45 179.98,215\"]; n7 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10f204b10\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"70.007,194\", shape=ellipse, subg=cluster_n7, subg_map_inputs=\"[[\'n4\', \'n73\'], [\'n3\', \'n74\'], [\'n2\', \'n72\']]\", subg_map_outputs=\"[[\'n75\', \'n6\']]\", width=1.7826]; n2 -> n7 [label=\"2 fscalar\", lp=\"27.007,238\", pos=\"e,28.697,207.85 27.721,268.8 10.72,259.37 -6.2971,245.36 3.007,230 7.1667,223.13 13.164,217.55 19.883,213.03\"]; n3 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"304.01,282\", shape=box, style=filled, width=0.75]; n3 -> n1 [label=\"1 fscalar\", lp=\"363.01,238\", pos=\"e,279.27,198.73 325,263.94 334.94,253.78 343.06,240.79 335.01,230 323.95,215.19 306.9,206.39 289.16,201.24\"]; n3 -> n7 [label=\"1 fscalar\", lp=\"304.01,238\", pos=\"e,116.87,206.31 294.23,263.96 286.68,252.44 275.15,237.94 261.01,230 215.13,204.25 195.68,221.9 144.01,212 138.37,210.92 132.5,209.72 \126.66,208.46\"]; n4 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"197.01,282\", shape=box, style=filled, width=0.75]; n4 -> n1 [label=\"2 fscalar\", lp=\"233.01,238\", pos=\"e,213.03,212.08 201.05,263.6 203.84,251.63 207.59,235.5 210.75,221.89\"]; n4 -> n7 [label=\"0 fscalar\", lp=\"98.007,238\", pos=\"e,66.731,212.43 169.97,281.61 141.33,280.65 97.14,274.26 74.007,246 68.707,239.52 66.766,230.91 66.43,222.6\"]; n7 -> n6 [color=red, label=\"0 fscalar\", lp=\"143.01,150\", pos=\"e,137.33,123.24 86.01,176.42 98.606,163.37 116.32,145.01 130.37,130.46\"]; n9 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"153.01,18\", shape=box, style=filled, width=0.75]; n6 -> n9 [label=fscalar, lp=\"172.01,62\", pos=\"e,153.01,36.084 153.01,87.597 153.01,75.746 153.01,59.817 153.01,46.292\"];}");
// Frontend graph for visualization
var graph = {};
......
......@@ -23,7 +23,7 @@
<script type="text/javascript">
// Backend graph in DOT format
var dotGraph = graphlibDot.read("digraph G { graph [bb=\"0,0,636,340\"]; node [label=\"\N\"]; subgraph cluster_n1 { graph [bb=\"251,8,628,332\"]; subgraph cluster_n11 { graph [bb=\"467,96,620,324\"]; n111 [apply_op=\"Elemwise{mul,no_inplace}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"544,210\", shape=ellipse, style=filled, type=colored, width=1.2888]; n114 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"544,122\", shape=box, style=filled, width=0.75]; n111 -> n114 [label=fscalar, lp=\"563,166\", pos=\"e,544,140.08 544,191.6 544,179.75 544,163.82 544,150.29\"]; n112 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"574,298\", shape=box, style=filled, width=0.75]; n112 -> n111 [label=\"0 fscalar\", lp=\"586,254\", pos=\"e,549.96,228.08 567.93,279.6 563.75,267.63 558.13,251.5 553.38,237.89\"]; n113 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"502,298\", shape=box, style=filled, width=0.75]; n113 -> n111 [label=\"1 fscalar\", lp=\"529,254\", pos=\"e,521.37,226.05 499.83,279.65 499.3,269.38 499.99,256.39 505,246 507.26,241.31 510.46,236.96 514.07,233.04\"]; } n11 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x110110490\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"395,210\", shape=ellipse, subg=cluster_n11, subg_map_inputs=\"[[\'n12\', \'n112\'], [\'n13\', \'n113\']]\", subg_map_outputs=\"[[\'n114\', \'n15\']]\", width=1.7826]; n15 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"345,122\", shape=ellipse, style=filled, type=colored, width=1.2888]; n11 -> n15 [color=red, label=\"0 fscalar\", lp=\"399,166\", pos=\"e,354.69,139.66 385.12,192.01 377.88,179.56 367.94,162.45 359.76,148.39\"]; n12 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"404,298\", shape=box, style=filled, width=0.75]; n12 -> n11 [label=\"0 fscalar\", lp=\"425,254\", pos=\"e,396.79,228.08 402.18,279.6 400.94,267.75 399.27,251.82 397.86,238.29\"]; n13 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"332,298\", shape=box, style=filled, width=0.75]; n13 -> n11 [label=\"1 fscalar\", lp=\"371,254\", pos=\"e,367.62,226.31 334.21,279.71 336.22,269.21 339.99,255.96 347,246 350.46,241.08 354.83,236.59 359.53,232.59\"]; n17 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"345,34\", shape=box, style=filled, width=0.75]; n15 -> n17 [label=fscalar, lp=\"364,78\", pos=\"e,345,52.084 345,103.6 345,91.746 345,75.817 345,62.292\"]; n16 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"286,210\", shape=box, style=filled, width=0.75]; n16 -> n15 [label=\"1 fscalar\", lp=\"338,166\", pos=\"e,329.38,139.11 294.18,191.9 299.34,181.72 306.44,168.74 314,158 316.65,154.24 319.64,150.43 322.7,146.78\"]; } n1 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x1101109d0\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"136,210\", shape=ellipse, subg=cluster_n1, subg_map_inputs=\"[[\'n2\', \'n12\'], [\'n3\', \'n13\'], [\'n4\', \'n16\']]\", subg_map_outputs=\"[[\'n17\', \'n6\']]\", width=1.7826]; n6 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"46,122\", shape=ellipse, style=filled, type=colored, width=1.2888]; n1 -> n6 [color=red, label=\"0 fscalar\", lp=\"124,166\", pos=\"e,62.691,138.95 118.65,192.42 104.9,179.28 85.538,160.78 70.258,146.18\"]; n2 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"123,298\", shape=box, style=filled, width=0.75]; n2 -> n1 [label=\"0 fscalar\", lp=\"149,254\", pos=\"e,129.59,228.22 122.55,279.88 122.56,269.92 123.06,257.17 125,246 125.46,243.33 126.08,240.57 126.78,237.84\"]; n3 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"195,298\", shape=box, style=filled, width=0.75]; n3 -> n1 [label=\"1 fscalar\", lp=\"207,254\", pos=\"e,155.98,227.13 189.48,279.56 185.74,269.26 180.18,256.27 173,246 170.17,241.96 166.82,238.01 163.3,234.32\"]; n4 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"29,298\", shape=box, style=filled, width=0.75]; n4 -> n1 [label=\"2 fscalar\", lp=\"96,254\", pos=\"e,103.61,225.73 40.803,279.98 48.767,269.34 59.985,255.82 72,246 78.91,240.35 86.866,235.16 94.768,230.6\"]; n4 -> n6 [label=\"1 fscalar\", lp=\"39,210\", pos=\"e,36.126,139.61 23.104,279.76 16.772,258.84 8.4483,222.57 15,192 18.224,176.96 24.988,161.23 31.378,148.6\"]; n7 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"46,34\", shape=box, style=filled, width=0.75]; n6 -> n7 [label=fscalar, lp=\"65,78\", pos=\"e,46,52.084 46,103.6 46,91.746 46,75.817 46,62.292\"];}");
var dotGraph = graphlibDot.read("digraph G { graph [bb=\"0,0,636,340\"]; node [label=\"\N\"]; subgraph cluster_n1 { graph [bb=\"251,8,628,332\"]; subgraph cluster_n11 { graph [bb=\"467,96,620,324\"]; n111 [apply_op=\"Elemwise{mul,no_inplace}\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"544,210\", shape=ellipse, style=filled, type=colored, width=1.2888]; n114 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"544,122\", shape=box, style=filled, width=0.75]; n111 -> n114 [label=fscalar, lp=\"563,166\", pos=\"e,544,140.08 544,191.6 544,179.75 544,163.82 544,150.29\"]; n112 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"574,298\", shape=box, style=filled, width=0.75]; n112 -> n111 [label=\"0 fscalar\", lp=\"586,254\", pos=\"e,549.96,228.08 567.93,279.6 563.75,267.63 558.13,251.5 553.38,237.89\"]; n113 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"502,298\", shape=box, style=filled, width=0.75]; n113 -> n111 [label=\"1 fscalar\", lp=\"529,254\", pos=\"e,521.37,226.05 499.83,279.65 499.3,269.38 499.99,256.39 505,246 507.26,241.31 510.46,236.96 514.07,233.04\"]; } n11 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10f2c65d0\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"395,210\", shape=ellipse, subg=cluster_n11, subg_map_inputs=\"[[\'n12\', \'n112\'], [\'n13\', \'n113\']]\", subg_map_outputs=\"[[\'n114\', \'n15\']]\", width=1.7826]; n15 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"345,122\", shape=ellipse, style=filled, type=colored, width=1.2888]; n11 -> n15 [color=red, label=\"0 fscalar\", lp=\"399,166\", pos=\"e,354.69,139.66 385.12,192.01 377.88,179.56 367.94,162.45 359.76,148.39\"]; n12 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"404,298\", shape=box, style=filled, width=0.75]; n12 -> n11 [label=\"0 fscalar\", lp=\"425,254\", pos=\"e,396.79,228.08 402.18,279.6 400.94,267.75 399.27,251.82 397.86,238.29\"]; n13 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"332,298\", shape=box, style=filled, width=0.75]; n13 -> n11 [label=\"1 fscalar\", lp=\"371,254\", pos=\"e,367.62,226.31 334.21,279.71 336.22,269.21 339.99,255.96 347,246 350.46,241.08 354.83,236.59 359.53,232.59\"]; n17 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"345,34\", shape=box, style=filled, width=0.75]; n15 -> n17 [label=fscalar, lp=\"364,78\", pos=\"e,345,52.084 345,103.6 345,91.746 345,75.817 345,62.292\"]; n16 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"286,210\", shape=box, style=filled, width=0.75]; n16 -> n15 [label=\"1 fscalar\", lp=\"338,166\", pos=\"e,329.38,139.11 294.18,191.9 299.34,181.72 306.44,168.74 314,158 316.65,154.24 319.64,150.43 322.7,146.78\"]; } n1 [apply_op=\"theano.compile.builders.OpFromGraph object at 0x10f2c6b10\", height=0.5, label=OpFromGraph, node_type=apply, pos=\"136,210\", shape=ellipse, subg=cluster_n1, subg_map_inputs=\"[[\'n2\', \'n12\'], [\'n3\', \'n13\'], [\'n4\', \'n16\']]\", subg_map_outputs=\"[[\'n17\', \'n6\']]\", width=1.7826]; n6 [apply_op=\"Elemwise{Add}[(0, 0)]\", fillcolor=\"#FFAABB\", height=0.5, label=Elemwise, node_type=apply, pos=\"46,122\", shape=ellipse, style=filled, type=colored, width=1.2888]; n1 -> n6 [color=red, label=\"0 fscalar\", lp=\"124,166\", pos=\"e,62.691,138.95 118.65,192.42 104.9,179.28 85.538,160.78 70.258,146.18\"]; n2 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=x, node_type=input, pos=\"123,298\", shape=box, style=filled, width=0.75]; n2 -> n1 [label=\"0 fscalar\", lp=\"149,254\", pos=\"e,129.59,228.22 122.55,279.88 122.56,269.92 123.06,257.17 125,246 125.46,243.33 126.08,240.57 126.78,237.84\"]; n3 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=y, node_type=input, pos=\"195,298\", shape=box, style=filled, width=0.75]; n3 -> n1 [label=\"1 fscalar\", lp=\"207,254\", pos=\"e,155.98,227.13 189.48,279.56 185.74,269.26 180.18,256.27 173,246 170.17,241.96 166.82,238.01 163.3,234.32\"]; n4 [dtype=fscalar, fillcolor=limegreen, height=0.5, label=z, node_type=input, pos=\"29,298\", shape=box, style=filled, width=0.75]; n4 -> n1 [label=\"2 fscalar\", lp=\"96,254\", pos=\"e,103.61,225.73 40.803,279.98 48.767,269.34 59.985,255.82 72,246 78.91,240.35 86.866,235.16 94.768,230.6\"]; n4 -> n6 [label=\"1 fscalar\", lp=\"39,210\", pos=\"e,36.126,139.61 23.104,279.76 16.772,258.84 8.4483,222.57 15,192 18.224,176.96 24.988,161.23 31.378,148.6\"]; n7 [dtype=fscalar, fillcolor=dodgerblue, height=0.5, label=fscalar, node_type=output, pos=\"46,34\", shape=box, style=filled, width=0.75]; n6 -> n7 [label=fscalar, lp=\"65,78\", pos=\"e,46,52.084 46,103.6 46,91.746 46,75.817 46,62.292\"];}");
// Frontend graph for visualization
var graph = {};
......
......@@ -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"
]
}
],
......
......@@ -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>`__.
......
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