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<?xml version='1.0' encoding='UTF-8'?>
<glyph name="flashlight" format="2">
<advance width="1200"/>
<unicode hex="F0244"/>
<note>
flashlight
</note>
<outline>
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<point x="600" y="640" type="qcurve" smooth="yes"/>
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</outline>
</glyph>
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/flashlight.glif/0
|
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| 643 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="floor-lamp-outline" format="2">
<advance width="1200"/>
<unicode hex="F17C8"/>
<note>
floor-lamp-outline
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<outline>
<contour>
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</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/floor-lamp-outline.glif/0
|
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| 644 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="format-align-left" format="2">
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<unicode hex="F0262"/>
<note>
format-align-left
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/format-align-left.glif/0
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{
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| 645 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="format-float-right" format="2">
<advance width="1200"/>
<unicode hex="F026A"/>
<note>
format-float-right
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<outline>
<contour>
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</glyph>
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/format-float-right.glif/0
|
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| 646 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="format-horizontal-align-right" format="2">
<advance width="1200"/>
<unicode hex="F0620"/>
<note>
format-horizontal-align-right
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<outline>
<contour>
<point x="923" y="710" type="line"/>
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<point x="663" y="773" type="line"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/format-horizontal-align-right.glif/0
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| 647 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="format-wrap-square" format="2">
<advance width="1200"/>
<unicode hex="F0289"/>
<note>
format-wrap-square
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<outline>
<contour>
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|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/format-wrap-square.glif/0
|
{
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| 648 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="home-floor-a" format="2">
<advance width="1200"/>
<unicode hex="F0D83"/>
<note>
home-floor-a
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<outline>
<contour>
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<contour>
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<point x="657" y="624" type="line"/>
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</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/home-floor-a.glif/0
|
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| 649 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="home-switch" format="2">
<advance width="1200"/>
<unicode hex="F1794"/>
<note>
home-switch
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<outline>
<contour>
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</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/home-switch.glif/0
|
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| 650 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="image-broken" format="2">
<advance width="1200"/>
<unicode hex="F02ED"/>
<note>
image-broken
</note>
<outline>
<contour>
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/image-broken.glif/0
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| 651 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="language-html5" format="2">
<advance width="1200"/>
<unicode hex="F031D"/>
<note>
language-html5
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/language-html5.glif/0
|
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| 652 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="laptop-account" format="2">
<advance width="1200"/>
<unicode hex="F1A4A"/>
<note>
laptop-account
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<outline>
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|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/laptop-account.glif/0
|
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| 653 |
<?xml version='1.0' encoding='UTF-8'?>
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layers-remove
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<contour>
<point x="115" y="650" type="line"/>
<point x="20" y="575" type="line"/>
<point x="554" y="161" type="line"/>
<point x="632" y="222" type="line"/>
<point x="613" y="277"/>
<point x="613" y="341" type="qcurve" smooth="yes"/>
<point x="613" y="355" type="line"/>
<point x="554" y="308" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/layers-remove.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/layers-remove.glif",
"repo_id": "cascadia-code",
"token_count": 626
}
| 654 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="lighthouse" format="2">
<advance width="1200"/>
<unicode hex="F09FF"/>
<note>
lighthouse
</note>
<outline>
<contour>
<point x="417" y="840" type="line"/>
<point x="381" y="604" type="line"/>
<point x="786" y="840" type="line"/>
<point x="867" y="840" type="line"/>
<point x="867" y="967" type="line"/>
<point x="804" y="967" type="line"/>
<point x="804" y="1227" type="line"/>
<point x="867" y="1227" type="line"/>
<point x="867" y="1290" type="line"/>
<point x="611" y="1420" type="line"/>
<point x="354" y="1290" type="line"/>
<point x="354" y="1227" type="line"/>
<point x="417" y="1227" type="line"/>
<point x="417" y="967" type="line"/>
<point x="354" y="967" type="line"/>
<point x="354" y="840" type="line"/>
</contour>
<contour>
<point x="547" y="967" type="line"/>
<point x="547" y="1227" type="line"/>
<point x="674" y="1227" type="line"/>
<point x="674" y="967" type="line"/>
</contour>
<contour>
<point x="674" y="0" type="line"/>
<point x="913" y="139" type="line"/>
<point x="879" y="357" type="line"/>
<point x="290" y="15" type="line"/>
<point x="287" y="0" type="line"/>
</contour>
<contour>
<point x="318" y="181" type="line"/>
<point x="858" y="492" type="line"/>
<point x="825" y="710" type="line"/>
<point x="357" y="441" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/lighthouse.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/lighthouse.glif",
"repo_id": "cascadia-code",
"token_count": 747
}
| 655 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="locker" format="2">
<advance width="1200"/>
<unicode hex="F07D7"/>
<note>
locker
</note>
<outline>
<contour>
<point x="257" y="1420"/>
<point x="173" y="1337"/>
<point x="173" y="1280" type="qcurve" smooth="yes"/>
<point x="173" y="140" type="line" smooth="yes"/>
<point x="173" y="83"/>
<point x="257" y="0"/>
<point x="317" y="0" type="qcurve" smooth="yes"/>
<point x="883" y="0" type="line" smooth="yes"/>
<point x="943" y="0"/>
<point x="1027" y="83"/>
<point x="1027" y="140" type="qcurve" smooth="yes"/>
<point x="1027" y="1280" type="line" smooth="yes"/>
<point x="1027" y="1337"/>
<point x="943" y="1420"/>
<point x="883" y="1420" type="qcurve" smooth="yes"/>
<point x="317" y="1420" type="line" smooth="yes"/>
</contour>
<contour>
<point x="883" y="1280" type="line"/>
<point x="883" y="140" type="line"/>
<point x="317" y="140" type="line"/>
<point x="317" y="1280" type="line"/>
</contour>
<contour>
<point x="457" y="353" type="line"/>
<point x="600" y="353" type="line"/>
<point x="600" y="640" type="line"/>
<point x="457" y="640" type="line"/>
</contour>
<contour>
<point x="457" y="1030" type="line"/>
<point x="743" y="1030" type="line"/>
<point x="743" y="1137" type="line"/>
<point x="457" y="1137" type="line"/>
</contour>
<contour>
<point x="457" y="817" type="line"/>
<point x="743" y="817" type="line"/>
<point x="743" y="923" type="line"/>
<point x="457" y="923" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/locker.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/locker.glif",
"repo_id": "cascadia-code",
"token_count": 831
}
| 656 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="magic-staff" format="2">
<advance width="1200"/>
<unicode hex="F1844"/>
<note>
magic-staff
</note>
<outline>
<contour>
<point x="931" y="847"/>
<point x="1014" y="928"/>
<point x="1014" y="1041"/>
<point x="931" y="1124"/>
<point x="818" y="1124"/>
<point x="737" y="1041"/>
<point x="737" y="928"/>
<point x="818" y="847"/>
<point x="874" y="847" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="735" y="845"/>
<point x="706" y="894" type="qcurve"/>
<point x="20" y="208" type="line"/>
<point x="98" y="130" type="line"/>
<point x="784" y="816" type="line"/>
</contour>
<contour>
<point x="592" y="1145" type="line"/>
<point x="626" y="1067" type="line"/>
<point x="662" y="1145" type="line"/>
<point x="737" y="1179" type="line"/>
<point x="662" y="1212" type="line"/>
<point x="626" y="1290" type="line"/>
<point x="592" y="1212" type="line"/>
<point x="517" y="1179" type="line"/>
</contour>
<contour>
<point x="1035" y="1145" type="line"/>
<point x="1069" y="1067" type="line"/>
<point x="1102" y="1145" type="line"/>
<point x="1180" y="1179" type="line"/>
<point x="1102" y="1212" type="line"/>
<point x="1069" y="1290" type="line"/>
<point x="1035" y="1212" type="line"/>
<point x="957" y="1179" type="line"/>
</contour>
<contour>
<point x="1102" y="772" type="line"/>
<point x="1069" y="847" type="line"/>
<point x="1035" y="772" type="line"/>
<point x="957" y="736" type="line"/>
<point x="1035" y="702" type="line"/>
<point x="1069" y="627" type="line"/>
<point x="1102" y="702" type="line"/>
<point x="1180" y="736" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/magic-staff.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/magic-staff.glif",
"repo_id": "cascadia-code",
"token_count": 948
}
| 657 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="network-strength-1-alert" format="2">
<advance width="1200"/>
<unicode hex="F08F5"/>
<note>
network-strength-1-alert
</note>
<outline>
<contour>
<point x="1180" y="825" type="line"/>
<point x="1180" y="1290" type="line"/>
<point x="20" y="130" type="line"/>
<point x="949" y="130" type="line"/>
<point x="949" y="247" type="line"/>
<point x="601" y="247" type="line"/>
<point x="601" y="548" type="line"/>
<point x="1063" y="1010" type="line"/>
<point x="1063" y="825" type="line"/>
</contour>
<contour>
<point x="1180" y="709" type="line"/>
<point x="1063" y="709" type="line"/>
<point x="1063" y="361" type="line"/>
<point x="1180" y="361" type="line"/>
</contour>
<contour>
<point x="1180" y="247" type="line"/>
<point x="1063" y="247" type="line"/>
<point x="1063" y="130" type="line"/>
<point x="1180" y="130" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/network-strength-1-alert.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/network-strength-1-alert.glif",
"repo_id": "cascadia-code",
"token_count": 491
}
| 658 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="note-off-outline" format="2">
<advance width="1200"/>
<unicode hex="F1784"/>
<note>
note-off-outline
</note>
<outline>
<contour>
<point x="411" y="1109" type="line"/>
<point x="621" y="1109" type="line"/>
<point x="621" y="899" type="line"/>
<point x="797" y="723" type="line"/>
<point x="1007" y="723" type="line"/>
<point x="1007" y="513" type="line"/>
<point x="1118" y="402" type="line"/>
<point x="1118" y="889" type="line"/>
<point x="786" y="1220" type="line"/>
<point x="300" y="1220" type="line"/>
</contour>
<contour>
<point x="732" y="834" type="line"/>
<point x="732" y="1137" type="line"/>
<point x="1035" y="834" type="line"/>
</contour>
<contour>
<point x="1180" y="200" type="line"/>
<point x="1102" y="278" type="line"/>
<point x="1102" y="278" type="line"/>
<point x="1007" y="373" type="line"/>
<point x="1007" y="373" type="line"/>
<point x="621" y="759" type="line"/>
<point x="621" y="759" type="line"/>
<point x="90" y="1290" type="line"/>
<point x="20" y="1220" type="line"/>
<point x="124" y="1114" type="line"/>
<point x="124" y="337" type="line" smooth="yes"/>
<point x="124" y="291"/>
<point x="188" y="226"/>
<point x="235" y="226" type="qcurve" smooth="yes"/>
<point x="1012" y="226" type="line"/>
<point x="1110" y="130" type="line"/>
</contour>
<contour>
<point x="903" y="337" type="line"/>
<point x="235" y="337" type="line"/>
<point x="235" y="1005" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/note-off-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/note-off-outline.glif",
"repo_id": "cascadia-code",
"token_count": 820
}
| 659 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="numeric-negative-1" format="2">
<advance width="1200"/>
<unicode hex="F1052"/>
<note>
numeric-negative-1
</note>
<outline>
<contour>
<point x="1180" y="1195" type="line"/>
<point x="790" y="1195" type="line"/>
<point x="790" y="1000" type="line"/>
<point x="985" y="1000" type="line"/>
<point x="985" y="225" type="line"/>
<point x="1180" y="225" type="line"/>
</contour>
<contour>
<point x="600" y="805" type="line"/>
<point x="20" y="805" type="line"/>
<point x="20" y="615" type="line"/>
<point x="600" y="615" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/numeric-negative-1.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/numeric-negative-1.glif",
"repo_id": "cascadia-code",
"token_count": 322
}
| 660 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="pan-bottom-left" format="2">
<advance width="1200"/>
<unicode hex="F0BB5"/>
<note>
pan-bottom-left
</note>
<outline>
<contour>
<point x="811" y="1290"/>
<point x="660" y="1139"/>
<point x="660" y="921"/>
<point x="811" y="770"/>
<point x="1029" y="770"/>
<point x="1180" y="921"/>
<point x="1180" y="1139"/>
<point x="1029" y="1290"/>
<point x="920" y="1290" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="20" y="130" type="line"/>
<point x="793" y="172" type="line"/>
<point x="62" y="903" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pan-bottom-left.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pan-bottom-left.glif",
"repo_id": "cascadia-code",
"token_count": 345
}
| 661 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="pause-octagon-outline" format="2">
<advance width="1200"/>
<unicode hex="F03E8"/>
<note>
pause-octagon-outline
</note>
<outline>
<contour>
<point x="793" y="967" type="line"/>
<point x="663" y="967" type="line"/>
<point x="663" y="453" type="line"/>
<point x="793" y="453" type="line"/>
</contour>
<contour>
<point x="537" y="967" type="line"/>
<point x="407" y="967" type="line"/>
<point x="407" y="453" type="line"/>
<point x="537" y="453" type="line"/>
</contour>
<contour>
<point x="358" y="1290" type="line"/>
<point x="20" y="952" type="line"/>
<point x="20" y="468" type="line"/>
<point x="358" y="130" type="line"/>
<point x="842" y="130" type="line"/>
<point x="1180" y="468" type="line"/>
<point x="1180" y="952" type="line"/>
<point x="842" y="1290" type="line"/>
</contour>
<contour>
<point x="1050" y="897" type="line"/>
<point x="1050" y="523" type="line"/>
<point x="787" y="260" type="line"/>
<point x="413" y="260" type="line"/>
<point x="150" y="523" type="line"/>
<point x="150" y="897" type="line"/>
<point x="413" y="1160" type="line"/>
<point x="787" y="1160" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pause-octagon-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pause-octagon-outline.glif",
"repo_id": "cascadia-code",
"token_count": 649
}
| 662 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="perspective-less" format="2">
<advance width="1200"/>
<unicode hex="F0D23"/>
<note>
perspective-less
</note>
<outline>
<contour>
<point x="336" y="680" type="line"/>
<point x="864" y="680" type="line"/>
<point x="1019" y="214" type="line"/>
<point x="181" y="214" type="line"/>
</contour>
<contour>
<point x="309" y="1146" type="line"/>
<point x="309" y="1320" type="line"/>
<point x="77" y="1086" type="line"/>
<point x="309" y="854" type="line"/>
<point x="309" y="1029" type="line"/>
<point x="543" y="1029" type="line"/>
<point x="543" y="1146" type="line"/>
</contour>
<contour>
<point x="1123" y="1086" type="line"/>
<point x="891" y="1320" type="line"/>
<point x="891" y="1146" type="line"/>
<point x="657" y="1146" type="line"/>
<point x="657" y="1029" type="line"/>
<point x="891" y="1029" type="line"/>
<point x="891" y="854" type="line"/>
</contour>
<contour>
<point x="1180" y="100" type="line"/>
<point x="949" y="797" type="line"/>
<point x="251" y="797" type="line"/>
<point x="20" y="100" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/perspective-less.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/perspective-less.glif",
"repo_id": "cascadia-code",
"token_count": 612
}
| 663 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="pickaxe" format="2">
<advance width="1200"/>
<unicode hex="F08B7"/>
<note>
pickaxe
</note>
<outline>
<contour>
<point x="656" y="848" type="line"/>
<point x="20" y="209" type="line"/>
<point x="99" y="130" type="line"/>
<point x="738" y="766" type="line"/>
</contour>
<contour>
<point x="1111" y="782"/>
<point x="989" y="930" type="qcurve"/>
<point x="1024" y="964" type="line"/>
<point x="979" y="1009" type="line"/>
<point x="1013" y="1044" type="line"/>
<point x="934" y="1123" type="line"/>
<point x="899" y="1089" type="line"/>
<point x="854" y="1134" type="line"/>
<point x="820" y="1099" type="line"/>
<point x="672" y="1221"/>
<point x="491" y="1290" type="qcurve"/>
<point x="446" y="1189" type="line"/>
<point x="592" y="1110"/>
<point x="719" y="999" type="qcurve"/>
<point x="693" y="972" type="line"/>
<point x="862" y="803" type="line"/>
<point x="889" y="829" type="line"/>
<point x="1000" y="702"/>
<point x="1079" y="556" type="qcurve"/>
<point x="1180" y="601" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pickaxe.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pickaxe.glif",
"repo_id": "cascadia-code",
"token_count": 607
}
| 664 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="pin-off" format="2">
<advance width="1200"/>
<unicode hex="F0404"/>
<note>
pin-off
</note>
<outline>
<contour>
<point x="407" y="758" type="line"/>
<point x="407" y="710" type="line"/>
<point x="277" y="580" type="line"/>
<point x="277" y="453" type="line"/>
<point x="612" y="453" type="line"/>
<point x="612" y="67" type="line"/>
<point x="715" y="67" type="line"/>
<point x="715" y="447" type="line"/>
<point x="1098" y="67" type="line"/>
<point x="1180" y="148" type="line"/>
<point x="102" y="1227" type="line"/>
<point x="20" y="1145" type="line"/>
</contour>
<contour>
<point x="920" y="1227" type="line"/>
<point x="987" y="1227" type="line"/>
<point x="987" y="1353" type="line"/>
<point x="340" y="1353" type="line"/>
<point x="340" y="1227" type="line"/>
<point x="407" y="1227" type="line"/>
<point x="407" y="1085" type="line"/>
<point x="1038" y="453" type="line"/>
<point x="1050" y="453" type="line"/>
<point x="1050" y="580" type="line"/>
<point x="920" y="710" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pin-off.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/pin-off.glif",
"repo_id": "cascadia-code",
"token_count": 588
}
| 665 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="play-pause" format="2">
<advance width="1200"/>
<unicode hex="F040E"/>
<note>
play-pause
</note>
<outline>
<contour>
<point x="537" y="710" type="line"/>
<point x="20" y="1160" type="line"/>
<point x="20" y="260" type="line"/>
</contour>
<contour>
<point x="663" y="1160" type="line"/>
<point x="663" y="260" type="line"/>
<point x="857" y="260" type="line"/>
<point x="857" y="1160" type="line"/>
</contour>
<contour>
<point x="1180" y="1160" type="line"/>
<point x="987" y="1160" type="line"/>
<point x="987" y="260" type="line"/>
<point x="1180" y="260" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/play-pause.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/play-pause.glif",
"repo_id": "cascadia-code",
"token_count": 357
}
| 666 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="plus" format="2">
<advance width="1200"/>
<unicode hex="F0415"/>
<note>
plus
</note>
<outline>
<contour>
<point x="1180" y="792" type="line"/>
<point x="682" y="792" type="line"/>
<point x="682" y="1290" type="line"/>
<point x="518" y="1290" type="line"/>
<point x="518" y="792" type="line"/>
<point x="20" y="792" type="line"/>
<point x="20" y="628" type="line"/>
<point x="518" y="628" type="line"/>
<point x="518" y="130" type="line"/>
<point x="682" y="130" type="line"/>
<point x="682" y="628" type="line"/>
<point x="1180" y="628" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/plus.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/plus.glif",
"repo_id": "cascadia-code",
"token_count": 336
}
| 667 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="polymer" format="2">
<advance width="1200"/>
<unicode hex="F0421"/>
<note>
polymer
</note>
<outline>
<contour>
<point x="1180" y="710" type="line"/>
<point x="953" y="1115" type="line"/>
<point x="752" y="1115" type="line"/>
<point x="351" y="476" type="line"/>
<point x="221" y="710" type="line"/>
<point x="448" y="1115" type="line"/>
<point x="247" y="1115" type="line"/>
<point x="20" y="710" type="line"/>
<point x="247" y="305" type="line"/>
<point x="448" y="305" type="line"/>
<point x="846" y="944" type="line"/>
<point x="979" y="710" type="line"/>
<point x="752" y="305" type="line"/>
<point x="953" y="305" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/polymer.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/polymer.glif",
"repo_id": "cascadia-code",
"token_count": 382
}
| 668 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="radiobox-marked" format="2">
<advance width="1200"/>
<unicode hex="F043E"/>
<note>
radiobox-marked
</note>
<outline>
<contour>
<point x="725" y="244"/>
<point x="600" y="244" type="qcurve" smooth="yes"/>
<point x="475" y="244"/>
<point x="260" y="370"/>
<point x="134" y="585"/>
<point x="134" y="835"/>
<point x="260" y="1050"/>
<point x="475" y="1176"/>
<point x="725" y="1176"/>
<point x="940" y="1050"/>
<point x="1066" y="835"/>
<point x="1066" y="585"/>
<point x="940" y="370"/>
</contour>
<contour>
<point x="714" y="1290"/>
<point x="600" y="1290" type="qcurve" smooth="yes"/>
<point x="486" y="1290"/>
<point x="271" y="1203"/>
<point x="107" y="1039"/>
<point x="20" y="824"/>
<point x="20" y="596"/>
<point x="107" y="381"/>
<point x="271" y="217"/>
<point x="486" y="130"/>
<point x="714" y="130"/>
<point x="929" y="217"/>
<point x="1093" y="381"/>
<point x="1180" y="596"/>
<point x="1180" y="824"/>
<point x="1093" y="1039"/>
<point x="929" y="1203"/>
</contour>
<contour>
<point x="679" y="1001"/>
<point x="600" y="1001" type="qcurve" smooth="yes"/>
<point x="521" y="1001"/>
<point x="388" y="922"/>
<point x="309" y="789"/>
<point x="309" y="631"/>
<point x="388" y="498"/>
<point x="521" y="419"/>
<point x="679" y="419"/>
<point x="812" y="498"/>
<point x="891" y="631"/>
<point x="891" y="789"/>
<point x="812" y="922"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/radiobox-marked.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/radiobox-marked.glif",
"repo_id": "cascadia-code",
"token_count": 885
}
| 669 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="ray-vertex" format="2">
<advance width="1200"/>
<unicode hex="F0445"/>
<note>
ray-vertex
</note>
<outline>
<contour>
<point x="20" y="653" type="line"/>
<point x="437" y="653" type="line"/>
<point x="453" y="601"/>
<point x="543" y="536"/>
<point x="657" y="536"/>
<point x="747" y="601"/>
<point x="763" y="653" type="qcurve"/>
<point x="1180" y="653" type="line"/>
<point x="1180" y="767" type="line"/>
<point x="763" y="767" type="line"/>
<point x="747" y="819"/>
<point x="657" y="884"/>
<point x="543" y="884"/>
<point x="453" y="819"/>
<point x="437" y="767" type="qcurve"/>
<point x="20" y="767" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/ray-vertex.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/ray-vertex.glif",
"repo_id": "cascadia-code",
"token_count": 396
}
| 670 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="relation-one-to-many" format="2">
<advance width="1200"/>
<unicode hex="F14A2"/>
<note>
relation-one-to-many
</note>
<outline>
<contour>
<point x="1123" y="653" type="line"/>
<point x="1006" y="536" type="line"/>
<point x="657" y="536" type="line"/>
<point x="657" y="1001" type="line"/>
<point x="309" y="1001" type="line"/>
<point x="309" y="1116" type="line"/>
<point x="194" y="1116" type="line"/>
<point x="194" y="1001" type="line"/>
<point x="20" y="1001" type="line"/>
<point x="20" y="884" type="line"/>
<point x="194" y="884" type="line"/>
<point x="194" y="767" type="line"/>
<point x="309" y="767" type="line"/>
<point x="309" y="884" type="line"/>
<point x="543" y="884" type="line"/>
<point x="543" y="419" type="line"/>
<point x="1006" y="419" type="line"/>
<point x="1123" y="304" type="line"/>
<point x="1180" y="304" type="line"/>
<point x="1180" y="653" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/relation-one-to-many.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/relation-one-to-many.glif",
"repo_id": "cascadia-code",
"token_count": 515
}
| 671 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="resistor" format="2">
<advance width="1200"/>
<unicode hex="F0B44"/>
<note>
resistor
</note>
<outline>
<contour>
<point x="20" y="653" type="line"/>
<point x="251" y="653" type="line"/>
<point x="535" y="244" type="line"/>
<point x="712" y="903" type="line"/>
<point x="891" y="653" type="line"/>
<point x="1180" y="653" type="line"/>
<point x="1180" y="767" type="line"/>
<point x="949" y="767" type="line"/>
<point x="665" y="1176" type="line"/>
<point x="488" y="517" type="line"/>
<point x="309" y="767" type="line"/>
<point x="20" y="767" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/resistor.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/resistor.glif",
"repo_id": "cascadia-code",
"token_count": 340
}
| 672 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="rug" format="2">
<advance width="1200"/>
<unicode hex="F1475"/>
<note>
rug
</note>
<outline>
<contour>
<point x="644" y="604"/>
<point x="706" y="666"/>
<point x="706" y="754"/>
<point x="644" y="816"/>
<point x="556" y="816"/>
<point x="494" y="754"/>
<point x="494" y="666"/>
<point x="556" y="604"/>
<point x="600" y="604" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="1180" y="446" type="line"/>
<point x="1022" y="446" type="line"/>
<point x="1022" y="552" type="line"/>
<point x="1180" y="552" type="line"/>
<point x="1180" y="658" type="line"/>
<point x="1022" y="658" type="line"/>
<point x="1022" y="762" type="line"/>
<point x="1180" y="762" type="line"/>
<point x="1180" y="868" type="line"/>
<point x="1022" y="868" type="line"/>
<point x="1022" y="974" type="line"/>
<point x="1180" y="974" type="line"/>
<point x="1180" y="1078" type="line"/>
<point x="20" y="1078" type="line"/>
<point x="20" y="974" type="line"/>
<point x="178" y="974" type="line"/>
<point x="178" y="868" type="line"/>
<point x="20" y="868" type="line"/>
<point x="20" y="762" type="line"/>
<point x="178" y="762" type="line"/>
<point x="178" y="658" type="line"/>
<point x="20" y="658" type="line"/>
<point x="20" y="552" type="line"/>
<point x="178" y="552" type="line"/>
<point x="178" y="446" type="line"/>
<point x="20" y="446" type="line"/>
<point x="20" y="342" type="line"/>
<point x="1180" y="342" type="line"/>
</contour>
<contour>
<point x="575" y="476"/>
<point x="501" y="463"/>
<point x="435" y="500"/>
<point x="410" y="572"/>
<point x="422" y="606" type="qcurve"/>
<point x="385" y="614"/>
<point x="336" y="673"/>
<point x="336" y="747"/>
<point x="385" y="806"/>
<point x="422" y="814" type="qcurve"/>
<point x="410" y="848"/>
<point x="435" y="920"/>
<point x="501" y="957"/>
<point x="575" y="944"/>
<point x="600" y="917" type="qcurve"/>
<point x="625" y="944"/>
<point x="699" y="957"/>
<point x="765" y="920"/>
<point x="790" y="848"/>
<point x="780" y="814" type="qcurve"/>
<point x="815" y="806"/>
<point x="864" y="747"/>
<point x="864" y="673"/>
<point x="815" y="614"/>
<point x="780" y="606" type="qcurve"/>
<point x="790" y="572"/>
<point x="765" y="500"/>
<point x="699" y="463"/>
<point x="625" y="476"/>
<point x="600" y="503" type="qcurve"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/rug.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/rug.glif",
"repo_id": "cascadia-code",
"token_count": 1389
}
| 673 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="sale-outline" format="2">
<advance width="1200"/>
<unicode hex="F1A06"/>
<note>
sale-outline
</note>
<outline>
<contour>
<point x="431" y="980"/>
<point x="386" y="932"/>
<point x="386" y="864"/>
<point x="431" y="818"/>
<point x="499" y="818"/>
<point x="547" y="864"/>
<point x="547" y="932"/>
<point x="499" y="980"/>
<point x="466" y="980" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="701" y="602"/>
<point x="653" y="556"/>
<point x="653" y="488"/>
<point x="701" y="440"/>
<point x="769" y="440"/>
<point x="814" y="488"/>
<point x="814" y="556"/>
<point x="769" y="602"/>
<point x="734" y="602" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="870" y="904" type="line"/>
<point x="794" y="980" type="line"/>
<point x="330" y="516" type="line"/>
<point x="406" y="440" type="line"/>
</contour>
<contour>
<point x="749" y="1169" type="line"/>
<point x="600" y="1318" type="line"/>
<point x="451" y="1166" type="line"/>
<point x="242" y="1202" type="line"/>
<point x="209" y="995" type="line"/>
<point x="20" y="899" type="line"/>
<point x="116" y="713" type="line"/>
<point x="20" y="523" type="line"/>
<point x="207" y="428" type="line"/>
<point x="242" y="218" type="line"/>
<point x="449" y="254" type="line"/>
<point x="597" y="102" type="line"/>
<point x="746" y="251" type="line"/>
<point x="956" y="218" type="line"/>
<point x="988" y="425" type="line"/>
<point x="1180" y="521" type="line"/>
<point x="1084" y="710" type="line"/>
<point x="1180" y="899" type="line"/>
<point x="991" y="995" type="line"/>
<point x="958" y="1202" type="line"/>
</contour>
<contour>
<point x="966" y="710" type="line"/>
<point x="1036" y="569" type="line"/>
<point x="895" y="496" type="line"/>
<point x="870" y="339" type="line"/>
<point x="713" y="362" type="line"/>
<point x="600" y="254" type="line"/>
<point x="487" y="362" type="line"/>
<point x="330" y="339" type="line"/>
<point x="305" y="496" type="line"/>
<point x="164" y="569" type="line"/>
<point x="234" y="710" type="line"/>
<point x="164" y="851" type="line"/>
<point x="305" y="924" type="line"/>
<point x="330" y="1081" type="line"/>
<point x="487" y="1058" type="line"/>
<point x="600" y="1166" type="line"/>
<point x="713" y="1058" type="line"/>
<point x="870" y="1081" type="line"/>
<point x="895" y="924" type="line"/>
<point x="1036" y="851" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/sale-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/sale-outline.glif",
"repo_id": "cascadia-code",
"token_count": 1393
}
| 674 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="set-square" format="2">
<advance width="1200"/>
<unicode hex="F145D"/>
<note>
set-square
</note>
<outline>
<contour>
<point x="1180" y="130" type="line"/>
<point x="1014" y="296" type="line"/>
<point x="932" y="218" type="line"/>
<point x="882" y="276" type="line"/>
<point x="963" y="347" type="line"/>
<point x="817" y="493" type="line"/>
<point x="746" y="415" type="line"/>
<point x="695" y="462" type="line"/>
<point x="773" y="544" type="line"/>
<point x="637" y="679" type="line"/>
<point x="556" y="601" type="line"/>
<point x="505" y="652" type="line"/>
<point x="586" y="730" type="line"/>
<point x="441" y="869" type="line"/>
<point x="363" y="788" type="line"/>
<point x="312" y="839" type="line"/>
<point x="383" y="927" type="line"/>
<point x="244" y="1066" type="line"/>
<point x="166" y="992" type="line"/>
<point x="115" y="1042" type="line"/>
<point x="196" y="1124" type="line"/>
<point x="20" y="1290" type="line"/>
<point x="20" y="130" type="line"/>
</contour>
<contour>
<point x="658" y="347" type="line"/>
<point x="237" y="347" type="line"/>
<point x="237" y="768" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/set-square.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/set-square.glif",
"repo_id": "cascadia-code",
"token_count": 647
}
| 675 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="shield-half" format="2">
<advance width="1200"/>
<unicode hex="F1360"/>
<note>
shield-half
</note>
<outline>
<contour>
<point x="890" y="0" type="qcurve"/>
<point x="890" y="1420" type="line"/>
<point x="310" y="1160" type="line"/>
<point x="310" y="773" type="line" smooth="yes"/>
<point x="310" y="598"/>
<point x="461" y="275"/>
<point x="724" y="42"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/shield-half.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/shield-half.glif",
"repo_id": "cascadia-code",
"token_count": 235
}
| 676 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="sleep" format="2">
<advance width="1200"/>
<unicode hex="F04B2"/>
<note>
sleep
</note>
<outline>
<contour>
<point x="1180" y="816" type="line"/>
<point x="1002" y="816" type="line"/>
<point x="1180" y="1026" type="line"/>
<point x="1180" y="1132" type="line"/>
<point x="864" y="1132" type="line"/>
<point x="864" y="1026" type="line"/>
<point x="1042" y="1026" type="line"/>
<point x="864" y="816" type="line"/>
<point x="864" y="710" type="line"/>
<point x="1180" y="710" type="line"/>
</contour>
<contour>
<point x="758" y="604" type="line"/>
<point x="580" y="604" type="line"/>
<point x="758" y="816" type="line"/>
<point x="758" y="920" type="line"/>
<point x="442" y="920" type="line"/>
<point x="442" y="816" type="line"/>
<point x="620" y="816" type="line"/>
<point x="442" y="604" type="line"/>
<point x="442" y="500" type="line"/>
<point x="758" y="500" type="line"/>
</contour>
<contour>
<point x="336" y="394" type="line"/>
<point x="158" y="394" type="line"/>
<point x="336" y="604" type="line"/>
<point x="336" y="710" type="line"/>
<point x="20" y="710" type="line"/>
<point x="20" y="604" type="line"/>
<point x="200" y="604" type="line"/>
<point x="20" y="394" type="line"/>
<point x="20" y="288" type="line"/>
<point x="336" y="288" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/sleep.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/sleep.glif",
"repo_id": "cascadia-code",
"token_count": 742
}
| 677 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="spider" format="2">
<advance width="1200"/>
<unicode hex="F11EA"/>
<note>
spider
</note>
<outline>
<contour>
<point x="954" y="602" type="line"/>
<point x="1104" y="449" type="line"/>
<point x="1180" y="526" type="line"/>
<point x="1007" y="699" type="line"/>
<point x="844" y="744" type="line"/>
<point x="949" y="757" type="line"/>
<point x="1175" y="933" type="line"/>
<point x="1111" y="1019" type="line"/>
<point x="903" y="864" type="line"/>
<point x="758" y="838" type="line"/>
<point x="931" y="1011" type="line"/>
<point x="872" y="1258" type="line"/>
<point x="763" y="1233" type="line"/>
<point x="809" y="1047" type="line"/>
<point x="750" y="983" type="line"/>
<point x="730" y="1029"/>
<point x="648" y="1083"/>
<point x="552" y="1083"/>
<point x="470" y="1029"/>
<point x="450" y="983" type="qcurve"/>
<point x="389" y="1047" type="line"/>
<point x="437" y="1233" type="line"/>
<point x="328" y="1258" type="line"/>
<point x="269" y="1011" type="line"/>
<point x="442" y="838" type="line"/>
<point x="297" y="864" type="line"/>
<point x="89" y="1019" type="line"/>
<point x="25" y="933" type="line"/>
<point x="251" y="757" type="line"/>
<point x="353" y="742" type="line"/>
<point x="190" y="696" type="line"/>
<point x="20" y="526" type="line"/>
<point x="96" y="449" type="line"/>
<point x="246" y="602" type="line"/>
<point x="376" y="638" type="line"/>
<point x="165" y="457" type="line"/>
<point x="165" y="162" type="line"/>
<point x="274" y="162" type="line"/>
<point x="274" y="409" type="line"/>
<point x="358" y="480" type="line"/>
<point x="374" y="391"/>
<point x="511" y="276"/>
<point x="689" y="276"/>
<point x="826" y="391"/>
<point x="842" y="480" type="qcurve"/>
<point x="926" y="409" type="line"/>
<point x="926" y="162" type="line"/>
<point x="1035" y="162" type="line"/>
<point x="1035" y="457" type="line"/>
<point x="824" y="638" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/spider.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/spider.glif",
"repo_id": "cascadia-code",
"token_count": 1104
}
| 678 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="square-medium" format="2">
<advance width="1200"/>
<unicode hex="F0A13"/>
<note>
square-medium
</note>
<outline>
<contour>
<point x="1180" y="130" type="line"/>
<point x="1180" y="1290" type="line"/>
<point x="20" y="1290" type="line"/>
<point x="20" y="130" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/square-medium.glif/0
|
{
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"repo_id": "cascadia-code",
"token_count": 181
}
| 679 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="star-outline" format="2">
<advance width="1200"/>
<unicode hex="F04D2"/>
<note>
star-outline
</note>
<outline>
<contour>
<point x="818" y="352" type="line"/>
<point x="600" y="485" type="line"/>
<point x="382" y="352" type="line"/>
<point x="439" y="602" type="line"/>
<point x="246" y="769" type="line"/>
<point x="502" y="790" type="line"/>
<point x="600" y="1025" type="line"/>
<point x="698" y="790" type="line"/>
<point x="954" y="769" type="line"/>
<point x="761" y="602" type="line"/>
</contour>
<contour>
<point x="864" y="567" type="line"/>
<point x="1180" y="842" type="line"/>
<point x="763" y="877" type="line"/>
<point x="600" y="1261" type="line"/>
<point x="437" y="877" type="line"/>
<point x="20" y="842" type="line"/>
<point x="336" y="567" type="line"/>
<point x="241" y="159" type="line"/>
<point x="600" y="376" type="line"/>
<point x="959" y="159" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/star-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/star-outline.glif",
"repo_id": "cascadia-code",
"token_count": 527
}
| 680 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="step-backward-2" format="2">
<advance width="1200"/>
<unicode hex="F04D6"/>
<note>
step-backward-2
</note>
<outline>
<contour>
<point x="906" y="324" type="line"/>
<point x="906" y="1096" type="line"/>
<point x="740" y="1096" type="line"/>
<point x="740" y="324" type="line"/>
</contour>
<contour>
<point x="628" y="324" type="line"/>
<point x="628" y="1096" type="line"/>
<point x="20" y="710" type="line"/>
</contour>
<contour>
<point x="1180" y="324" type="line"/>
<point x="1180" y="1096" type="line"/>
<point x="1014" y="1096" type="line"/>
<point x="1014" y="324" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/step-backward-2.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/step-backward-2.glif",
"repo_id": "cascadia-code",
"token_count": 366
}
| 681 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="swap-horizontal-variant" format="2">
<advance width="1200"/>
<unicode hex="F08C1"/>
<note>
swap-horizontal-variant
</note>
<outline>
<contour>
<point x="317" y="1420" type="line"/>
<point x="30" y="1137" type="line"/>
<point x="317" y="853" type="line"/>
<point x="317" y="1067" type="line"/>
<point x="883" y="1067" type="line" smooth="yes"/>
<point x="943" y="1067"/>
<point x="1027" y="983"/>
<point x="1027" y="863"/>
<point x="943" y="780"/>
<point x="883" y="780" type="qcurve" smooth="yes"/>
<point x="317" y="780" type="line" smooth="yes"/>
<point x="197" y="780"/>
<point x="30" y="613"/>
<point x="30" y="380"/>
<point x="197" y="213"/>
<point x="317" y="213" type="qcurve" smooth="yes"/>
<point x="883" y="213" type="line"/>
<point x="883" y="0" type="line"/>
<point x="1170" y="283" type="line"/>
<point x="883" y="567" type="line"/>
<point x="883" y="353" type="line"/>
<point x="317" y="353" type="line" smooth="yes"/>
<point x="257" y="353"/>
<point x="173" y="437"/>
<point x="173" y="557"/>
<point x="257" y="640"/>
<point x="317" y="640" type="qcurve" smooth="yes"/>
<point x="883" y="640" type="line" smooth="yes"/>
<point x="1003" y="640"/>
<point x="1170" y="807"/>
<point x="1170" y="1040"/>
<point x="1003" y="1207"/>
<point x="883" y="1207" type="qcurve" smooth="yes"/>
<point x="317" y="1207" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/swap-horizontal-variant.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/swap-horizontal-variant.glif",
"repo_id": "cascadia-code",
"token_count": 783
}
| 682 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="tablet-cellphone" format="2">
<advance width="1200"/>
<unicode hex="F09A7"/>
<note>
tablet-cellphone
</note>
<outline>
<contour>
<point x="79" y="1164"/>
<point x="20" y="1105"/>
<point x="20" y="1062" type="qcurve" smooth="yes"/>
<point x="20" y="457" type="line" smooth="yes"/>
<point x="20" y="415"/>
<point x="79" y="356"/>
<point x="122" y="356" type="qcurve" smooth="yes"/>
<point x="677" y="356" type="line"/>
<point x="677" y="457" type="line"/>
<point x="223" y="457" type="line"/>
<point x="223" y="1062" type="line"/>
<point x="878" y="1062" type="line"/>
<point x="878" y="960" type="line"/>
<point x="1078" y="960" type="line"/>
<point x="1078" y="1062" type="line" smooth="yes"/>
<point x="1078" y="1105"/>
<point x="1019" y="1164"/>
<point x="979" y="1164" type="qcurve" smooth="yes"/>
<point x="122" y="1164" type="line" smooth="yes"/>
</contour>
<contour>
<point x="807" y="861"/>
<point x="776" y="830"/>
<point x="776" y="809" type="qcurve" smooth="yes"/>
<point x="776" y="306" type="line" smooth="yes"/>
<point x="776" y="285"/>
<point x="807" y="256"/>
<point x="828" y="256" type="qcurve" smooth="yes"/>
<point x="1130" y="256" type="line" smooth="yes"/>
<point x="1152" y="256"/>
<point x="1180" y="285"/>
<point x="1180" y="306" type="qcurve" smooth="yes"/>
<point x="1180" y="809" type="line" smooth="yes"/>
<point x="1180" y="830"/>
<point x="1152" y="861"/>
<point x="1130" y="861" type="qcurve" smooth="yes"/>
<point x="828" y="861" type="line" smooth="yes"/>
</contour>
<contour>
<point x="1078" y="760" type="line"/>
<point x="1078" y="408" type="line"/>
<point x="878" y="408" type="line"/>
<point x="878" y="760" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tablet-cellphone.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tablet-cellphone.glif",
"repo_id": "cascadia-code",
"token_count": 962
}
| 683 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="tag-heart" format="2">
<advance width="1200"/>
<unicode hex="F068B"/>
<note>
tag-heart
</note>
<outline>
<contour>
<point x="1180" y="699"/>
<point x="1147" y="735" type="qcurve" smooth="yes"/>
<point x="625" y="1257" type="line" smooth="yes"/>
<point x="589" y="1290"/>
<point x="543" y="1290" type="qcurve" smooth="yes"/>
<point x="134" y="1290" type="line" smooth="yes"/>
<point x="88" y="1290"/>
<point x="20" y="1222"/>
<point x="20" y="1176" type="qcurve" smooth="yes"/>
<point x="20" y="767" type="line" smooth="yes"/>
<point x="20" y="721"/>
<point x="53" y="685" type="qcurve" smooth="yes"/>
<point x="575" y="163" type="line" smooth="yes"/>
<point x="611" y="130"/>
<point x="706" y="130"/>
<point x="739" y="163" type="qcurve" smooth="yes"/>
<point x="1147" y="571" type="line" smooth="yes"/>
<point x="1180" y="604"/>
</contour>
<contour>
<point x="260" y="1001"/>
<point x="222" y="1001" type="qcurve" smooth="yes"/>
<point x="186" y="1001"/>
<point x="134" y="1050"/>
<point x="134" y="1124"/>
<point x="186" y="1176"/>
<point x="260" y="1176"/>
<point x="309" y="1124"/>
<point x="309" y="1050"/>
</contour>
<contour>
<point x="949" y="563"/>
<point x="905" y="519" type="qcurve" smooth="yes"/>
<point x="657" y="272" type="line"/>
<point x="409" y="519" type="line" smooth="yes"/>
<point x="369" y="563"/>
<point x="369" y="683"/>
<point x="453" y="767"/>
<point x="573" y="767"/>
<point x="616" y="726" type="qcurve" smooth="yes"/>
<point x="657" y="683" type="line"/>
<point x="701" y="726" type="line" smooth="yes"/>
<point x="742" y="767"/>
<point x="864" y="767"/>
<point x="949" y="683"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tag-heart.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tag-heart.glif",
"repo_id": "cascadia-code",
"token_count": 954
}
| 684 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="tag" format="2">
<advance width="1200"/>
<unicode hex="F04F9"/>
<note>
tag
</note>
<outline>
<contour>
<point x="260" y="1001"/>
<point x="222" y="1001" type="qcurve" smooth="yes"/>
<point x="186" y="1001"/>
<point x="134" y="1050"/>
<point x="134" y="1124"/>
<point x="186" y="1176"/>
<point x="260" y="1176"/>
<point x="309" y="1124"/>
<point x="309" y="1050"/>
</contour>
<contour>
<point x="1180" y="699"/>
<point x="1147" y="735" type="qcurve" smooth="yes"/>
<point x="625" y="1257" type="line" smooth="yes"/>
<point x="589" y="1290"/>
<point x="543" y="1290" type="qcurve" smooth="yes"/>
<point x="134" y="1290" type="line" smooth="yes"/>
<point x="88" y="1290"/>
<point x="20" y="1222"/>
<point x="20" y="1176" type="qcurve" smooth="yes"/>
<point x="20" y="767" type="line" smooth="yes"/>
<point x="20" y="718"/>
<point x="53" y="685" type="qcurve" smooth="yes"/>
<point x="575" y="163" type="line" smooth="yes"/>
<point x="611" y="130"/>
<point x="706" y="130"/>
<point x="739" y="163" type="qcurve" smooth="yes"/>
<point x="1147" y="571" type="line" smooth="yes"/>
<point x="1180" y="604"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tag.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/tag.glif",
"repo_id": "cascadia-code",
"token_count": 662
}
| 685 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="text-short" format="2">
<advance width="1200"/>
<unicode hex="F09A9"/>
<note>
text-short
</note>
<outline>
<contour>
<point x="20" y="781" type="line"/>
<point x="1180" y="781" type="line"/>
<point x="1180" y="927" type="line"/>
<point x="20" y="927" type="line"/>
</contour>
<contour>
<point x="20" y="493" type="line"/>
<point x="746" y="493" type="line"/>
<point x="746" y="639" type="line"/>
<point x="20" y="639" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/text-short.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/text-short.glif",
"repo_id": "cascadia-code",
"token_count": 281
}
| 686 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="timeline-help-outline" format="2">
<advance width="1200"/>
<unicode hex="F0F9A"/>
<note>
timeline-help-outline
</note>
<outline>
<contour>
<point x="223" y="753"/>
<point x="164" y="812"/>
<point x="79" y="812"/>
<point x="20" y="753"/>
<point x="20" y="667"/>
<point x="79" y="608"/>
<point x="164" y="608"/>
<point x="223" y="667"/>
<point x="223" y="710" type="qcurve" smooth="yes"/>
</contour>
<contour>
<point x="72" y="1213" type="line"/>
<point x="72" y="911" type="line"/>
<point x="171" y="911" type="line"/>
<point x="171" y="1213" type="line"/>
</contour>
<contour>
<point x="171" y="207" type="line"/>
<point x="171" y="509" type="line"/>
<point x="72" y="509" type="line"/>
<point x="72" y="207" type="line"/>
</contour>
<contour>
<point x="1180" y="1055"/>
<point x="1121" y="1114"/>
<point x="1078" y="1114" type="qcurve" smooth="yes"/>
<point x="474" y="1114" type="line" smooth="yes"/>
<point x="433" y="1114"/>
<point x="374" y="1055"/>
<point x="374" y="1012" type="qcurve" smooth="yes"/>
<point x="374" y="812" type="line"/>
<point x="273" y="710" type="line"/>
<point x="374" y="608" type="line"/>
<point x="374" y="408" type="line" smooth="yes"/>
<point x="374" y="365"/>
<point x="433" y="306"/>
<point x="474" y="306" type="qcurve" smooth="yes"/>
<point x="1078" y="306" type="line" smooth="yes"/>
<point x="1121" y="306"/>
<point x="1180" y="365"/>
<point x="1180" y="408" type="qcurve" smooth="yes"/>
<point x="1180" y="1012" type="line" smooth="yes"/>
</contour>
<contour>
<point x="1078" y="408" type="line"/>
<point x="474" y="408" type="line"/>
<point x="474" y="651" type="line"/>
<point x="415" y="710" type="line"/>
<point x="474" y="769" type="line"/>
<point x="474" y="1012" type="line"/>
<point x="1078" y="1012" type="line"/>
</contour>
<contour>
<point x="726" y="533" type="line"/>
<point x="726" y="457" type="line"/>
<point x="802" y="457" type="line"/>
<point x="802" y="533" type="line"/>
</contour>
<contour>
<point x="700" y="812" type="line" smooth="yes"/>
<point x="700" y="842"/>
<point x="745" y="887"/>
<point x="809" y="887"/>
<point x="852" y="842"/>
<point x="852" y="812" type="qcurve" smooth="yes"/>
<point x="852" y="774"/>
<point x="821" y="753" type="qcurve" smooth="yes"/>
<point x="807" y="743" type="line" smooth="yes"/>
<point x="769" y="717"/>
<point x="726" y="639"/>
<point x="726" y="594" type="qcurve" smooth="yes"/>
<point x="726" y="585" type="line"/>
<point x="802" y="585" type="line"/>
<point x="802" y="594" type="line" smooth="yes"/>
<point x="802" y="649"/>
<point x="847" y="679" type="qcurve" smooth="yes"/>
<point x="863" y="689" type="line" smooth="yes"/>
<point x="894" y="710"/>
<point x="927" y="774"/>
<point x="927" y="812" type="qcurve" smooth="yes"/>
<point x="927" y="873"/>
<point x="840" y="963"/>
<point x="715" y="963"/>
<point x="625" y="873"/>
<point x="625" y="812" type="qcurve" smooth="yes"/>
<point x="625" y="786" type="line"/>
<point x="700" y="786" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/timeline-help-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/timeline-help-outline.glif",
"repo_id": "cascadia-code",
"token_count": 1736
}
| 687 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="timer-sand-empty" format="2">
<advance width="1200"/>
<unicode hex="F06AD"/>
<note>
timer-sand-empty
</note>
<outline>
<contour>
<point x="1027" y="1420" type="line"/>
<point x="173" y="1420" type="line"/>
<point x="173" y="993" type="line"/>
<point x="457" y="710" type="line"/>
<point x="173" y="427" type="line"/>
<point x="173" y="0" type="line"/>
<point x="1027" y="0" type="line"/>
<point x="1027" y="427" type="line"/>
<point x="743" y="710" type="line"/>
<point x="1027" y="993" type="line"/>
</contour>
<contour>
<point x="600" y="673" type="line"/>
<point x="883" y="390" type="line"/>
<point x="883" y="140" type="line"/>
<point x="317" y="140" type="line"/>
<point x="317" y="390" type="line"/>
</contour>
<contour>
<point x="883" y="1030" type="line"/>
<point x="600" y="747" type="line"/>
<point x="317" y="1030" type="line"/>
<point x="317" y="1280" type="line"/>
<point x="883" y="1280" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/timer-sand-empty.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/timer-sand-empty.glif",
"repo_id": "cascadia-code",
"token_count": 539
}
| 688 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="triangle-small-down" format="2">
<advance width="1200"/>
<unicode hex="F1A09"/>
<note>
triangle-small-down
</note>
<outline>
<contour>
<point x="600" y="202" type="line"/>
<point x="1180" y="1218" type="line"/>
<point x="20" y="1218" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/triangle-small-down.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/triangle-small-down.glif",
"repo_id": "cascadia-code",
"token_count": 166
}
| 689 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="turnstile-outline" format="2">
<advance width="1200"/>
<unicode hex="F0CD6"/>
<note>
turnstile-outline
</note>
<outline>
<contour>
<point x="763" y="721" type="qcurve"/>
<point x="682" y="803" type="line"/>
<point x="649" y="767"/>
<point x="551" y="767"/>
<point x="483" y="835"/>
<point x="483" y="933"/>
<point x="518" y="966" type="qcurve"/>
<point x="437" y="1048" type="line"/>
<point x="369" y="980"/>
<point x="369" y="884" type="qcurve"/>
<point x="20" y="884" type="line"/>
<point x="20" y="767" type="line"/>
<point x="398" y="767" type="line"/>
<point x="431" y="715"/>
<point x="483" y="683" type="qcurve"/>
<point x="483" y="304" type="line"/>
<point x="600" y="304" type="line"/>
<point x="600" y="653" type="line"/>
<point x="695" y="653"/>
</contour>
<contour>
<point x="1180" y="1290" type="line"/>
<point x="483" y="1290" type="line"/>
<point x="483" y="1116" type="line"/>
<point x="831" y="767" type="line"/>
<point x="831" y="130" type="line"/>
<point x="1180" y="130" type="line"/>
</contour>
<contour>
<point x="1066" y="1176" type="line"/>
<point x="1066" y="244" type="line"/>
<point x="949" y="244" type="line"/>
<point x="949" y="816" type="line"/>
<point x="600" y="1165" type="line"/>
<point x="600" y="1176" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/turnstile-outline.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/turnstile-outline.glif",
"repo_id": "cascadia-code",
"token_count": 754
}
| 690 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="vector-polyline" format="2">
<advance width="1200"/>
<unicode hex="F0561"/>
<note>
vector-polyline
</note>
<outline>
<contour>
<point x="369" y="1233" type="line"/>
<point x="20" y="1233" type="line"/>
<point x="20" y="884" type="line"/>
<point x="192" y="884" type="line"/>
<point x="306" y="536" type="line"/>
<point x="251" y="536" type="line"/>
<point x="251" y="187" type="line"/>
<point x="600" y="187" type="line"/>
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<point x="913" y="767" type="line"/>
<point x="1180" y="767" type="line"/>
<point x="1180" y="1116" type="line"/>
<point x="831" y="1116" type="line"/>
<point x="831" y="852" type="line"/>
<point x="518" y="536" type="line"/>
<point x="428" y="536" type="line"/>
<point x="314" y="884" type="line"/>
<point x="369" y="884" type="line"/>
</contour>
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</outline>
</glyph>
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cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/vector-polyline.glif/0
|
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| 691 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="video-2d" format="2">
<advance width="1200"/>
<unicode hex="F1A1C"/>
<note>
video-2d
</note>
<outline>
<contour>
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<point x="931" y="293" type="line" smooth="yes"/>
<point x="1036" y="293"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/video-2d.glif/0
|
{
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| 692 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="view-parallel-outline" format="2">
<advance width="1200"/>
<unicode hex="F148D"/>
<note>
view-parallel-outline
</note>
<outline>
<contour>
<point x="1151" y="0" type="line"/>
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<point x="49" y="1420" type="line"/>
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<point x="363" y="159" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/view-parallel-outline.glif/0
|
{
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| 693 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="virus-off" format="2">
<advance width="1200"/>
<unicode hex="F18E1"/>
<note>
virus-off
</note>
<outline>
<contour>
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<point x="345" y="1185" type="qcurve" smooth="yes"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/virus-off.glif/0
|
{
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}
| 694 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="volume-variant-off" format="2">
<advance width="1200"/>
<unicode hex="F0E08"/>
<note>
volume-variant-off
</note>
<outline>
<contour>
<point x="20" y="1193" type="line"/>
<point x="286" y="927" type="line"/>
<point x="207" y="927" type="line"/>
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<point x="816" y="781" type="line"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/volume-variant-off.glif/0
|
{
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| 695 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="wall-sconce-round-variant" format="2">
<advance width="1200"/>
<unicode hex="F091E"/>
<note>
wall-sconce-round-variant
</note>
<outline>
<contour>
<point x="667" y="1223" type="line"/>
<point x="533" y="1223" type="line"/>
<point x="533" y="1018" type="line"/>
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<contour>
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<contour>
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<point x="1001" y="345"/>
<point x="1148" y="598"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/wall-sconce-round-variant.glif/0
|
{
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"repo_id": "cascadia-code",
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}
| 696 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="webpack" format="2">
<advance width="1200"/>
<unicode hex="F072B"/>
<note>
webpack
</note>
<outline>
<contour>
<point x="947" y="477" type="line"/>
<point x="624" y="296" type="line"/>
<point x="624" y="67" type="line"/>
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</contour>
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<point x="600" y="1094" type="line"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/webpack.glif/0
|
{
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| 697 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="window-shutter-open" format="2">
<advance width="1200"/>
<unicode hex="F111E"/>
<note>
window-shutter-open
</note>
<outline>
<contour>
<point x="20" y="967" type="line"/>
<point x="150" y="967" type="line"/>
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</contour>
<contour>
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<point x="857" y="903" type="line"/>
<point x="343" y="903" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/window-shutter-open.glif/0
|
{
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}
| 698 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="xmpp" format="2">
<advance width="1200"/>
<unicode hex="F07FF"/>
<note>
xmpp
</note>
<outline>
<contour>
<point x="703" y="587"/>
<point x="600" y="481" type="qcurve"/>
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<point x="434" y="729" type="qcurve" smooth="yes"/>
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</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/MaterialDesignIconsDesktop.ufo/glyphs/xmpp.glif/0
|
{
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| 699 |
<?xml version='1.0' encoding='UTF-8'?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>ascender</key>
<integer>750</integer>
<key>capHeight</key>
<integer>700</integer>
<key>copyright</key>
<string>Copyright (c) 2014 by Davide Bignotti. All rights reserved.</string>
<key>descender</key>
<integer>-250</integer>
<key>familyName</key>
<string>Pomicons</string>
<key>guidelines</key>
<array/>
<key>italicAngle</key>
<integer>0</integer>
<key>openTypeHeadCreated</key>
<string>2014/03/16 20:33:00</string>
<key>openTypeHheaAscender</key>
<integer>750</integer>
<key>openTypeHheaDescender</key>
<integer>-250</integer>
<key>openTypeNameDescription</key>
<string>Copyright (c) 2013 by Davide Bignotti. All rights reserved.</string>
<key>openTypeNameDesigner</key>
<string>Davide Bignotti</string>
<key>openTypeNameDesignerURL</key>
<string>[email protected]</string>
<key>openTypeNameLicenseURL</key>
<string>Free</string>
<key>openTypeNameManufacturer</key>
<string>Davide Bignotti</string>
<key>openTypeNamePreferredSubfamilyName</key>
<string>Regular</string>
<key>openTypeOS2Panose</key>
<array>
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<key>openTypeOS2StrikeoutPosition</key>
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<key>openTypeOS2StrikeoutSize</key>
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<array>
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<integer>-250</integer>
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<integer>400</integer>
<key>openTypeOS2WidthClass</key>
<integer>5</integer>
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<integer>1000</integer>
<key>openTypeOS2WinDescent</key>
<integer>0</integer>
<key>postscriptBlueValues</key>
<array/>
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<array/>
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<array/>
<key>postscriptFontName</key>
<string>Pomicons</string>
<key>postscriptOtherBlues</key>
<array/>
<key>postscriptStemSnapH</key>
<array>
<integer>74</integer>
<integer>179</integer>
<integer>221</integer>
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<key>postscriptStemSnapV</key>
<array/>
<key>styleMapStyleName</key>
<string>regular</string>
<key>styleName</key>
<string>Regular</string>
<key>trademark</key>
<string>Pomicons is a trademark of Davide Bignotti.</string>
<key>unitsPerEm</key>
<integer>2048</integer>
<key>versionMajor</key>
<integer>1</integer>
<key>versionMinor</key>
<integer>0</integer>
<key>xHeight</key>
<integer>500</integer>
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</plist>
|
cascadia-code/sources/nerdfonts/full/processed/Pomicons.ufo/fontinfo.plist/0
|
{
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}
| 700 |
<?xml version='1.0' encoding='UTF-8'?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>ascender</key>
<integer>1567</integer>
<key>capHeight</key>
<integer>1462</integer>
<key>copyright</key>
<string>MIT © Ryan L McIntyre</string>
<key>descender</key>
<integer>-492</integer>
<key>familyName</key>
<string>Powerline Extra Symbols</string>
<key>guidelines</key>
<array/>
<key>italicAngle</key>
<integer>0</integer>
<key>openTypeHeadCreated</key>
<string>2007/01/08 12:28:04</string>
<key>openTypeHheaAscender</key>
<integer>1901</integer>
<key>openTypeHheaDescender</key>
<integer>-483</integer>
<key>openTypeNameDescription</key>
<string>Extra glyphs for your powerline separators</string>
<key>openTypeNameDesignerURL</key>
<string>https://github.com/ryanoasis/powerline-extra-symbols</string>
<key>openTypeNameLicense</key>
<string>MIT</string>
<key>openTypeNameLicenseURL</key>
<string>https://opensource.org/licenses/MIT</string>
<key>openTypeNameManufacturerURL</key>
<string>https://github.com/ryanoasis/powerline-extra-symbols</string>
<key>openTypeNamePreferredSubfamilyName</key>
<string>Regular</string>
<key>openTypeOS2Panose</key>
<array>
<integer>2</integer>
<integer>11</integer>
<integer>6</integer>
<integer>9</integer>
<integer>3</integer>
<integer>8</integer>
<integer>4</integer>
<integer>2</integer>
<integer>2</integer>
<integer>4</integer>
</array>
<key>openTypeOS2StrikeoutPosition</key>
<integer>498</integer>
<key>openTypeOS2StrikeoutSize</key>
<integer>102</integer>
<key>openTypeOS2TypoAscender</key>
<integer>1567</integer>
<key>openTypeOS2TypoDescender</key>
<integer>-492</integer>
<key>openTypeOS2TypoLineGap</key>
<integer>132</integer>
<key>openTypeOS2UnicodeRanges</key>
<array>
<integer>0</integer>
<integer>1</integer>
<integer>2</integer>
<integer>3</integer>
<integer>5</integer>
<integer>6</integer>
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<integer>29</integer>
<integer>30</integer>
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<integer>32</integer>
<integer>33</integer>
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<integer>38</integer>
<integer>45</integer>
<integer>62</integer>
<integer>67</integer>
<integer>69</integer>
</array>
<key>openTypeOS2VendorID</key>
<string>1ASC</string>
<key>openTypeOS2WeightClass</key>
<integer>400</integer>
<key>openTypeOS2WidthClass</key>
<integer>5</integer>
<key>openTypeOS2WinAscent</key>
<integer>1901</integer>
<key>openTypeOS2WinDescent</key>
<integer>483</integer>
<key>postscriptBlueScale</key>
<real>0.011</real>
<key>postscriptBlueShift</key>
<integer>10</integer>
<key>postscriptBlueValues</key>
<array>
<integer>-20</integer>
<integer>0</integer>
<integer>1098</integer>
<integer>1118</integer>
<integer>1462</integer>
<integer>1556</integer>
</array>
<key>postscriptFamilyBlues</key>
<array/>
<key>postscriptFamilyOtherBlues</key>
<array/>
<key>postscriptFontName</key>
<string>PowerlineExtraSymbols</string>
<key>postscriptOtherBlues</key>
<array/>
<key>postscriptStemSnapH</key>
<array>
<integer>12</integer>
<integer>20</integer>
<integer>44</integer>
<integer>48</integer>
<integer>68</integer>
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<integer>116</integer>
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<integer>202</integer>
</array>
<key>postscriptStemSnapV</key>
<array>
<integer>10</integer>
<integer>14</integer>
<integer>27</integer>
<integer>34</integer>
<integer>46</integer>
<integer>52</integer>
<integer>61</integer>
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<integer>76</integer>
<integer>87</integer>
</array>
<key>postscriptUnderlinePosition</key>
<integer>-205</integer>
<key>postscriptUnderlineThickness</key>
<integer>102</integer>
<key>styleMapStyleName</key>
<string>regular</string>
<key>styleName</key>
<string>Regular</string>
<key>unitsPerEm</key>
<integer>2048</integer>
<key>versionMajor</key>
<integer>1</integer>
<key>versionMinor</key>
<integer>0</integer>
<key>xHeight</key>
<integer>1098</integer>
</dict>
</plist>
|
cascadia-code/sources/nerdfonts/full/processed/PowerlineExtraSymbols.ufo/fontinfo.plist/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/PowerlineExtraSymbols.ufo/fontinfo.plist",
"repo_id": "cascadia-code",
"token_count": 2079
}
| 701 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="POWER ON-OFF SYMBOL" format="2">
<advance width="1200"/>
<unicode hex="23FC"/>
<note>
POWER ON-OFF SYMBOL
</note>
<outline>
<contour>
<point x="501" y="891" type="curve" smooth="yes"/>
<point x="501" y="527" type="line"/>
<point x="501" y="527" type="line"/>
<point x="501" y="473"/>
<point x="545" y="428"/>
<point x="600" y="428" type="curve"/>
<point x="600" y="428" type="line"/>
<point x="655" y="428"/>
<point x="699" y="472"/>
<point x="699" y="527" type="curve" smooth="yes"/>
<point x="699" y="891" type="line"/>
<point x="699" y="891" type="line"/>
<point x="699" y="945"/>
<point x="655" y="990"/>
<point x="600" y="990" type="curve"/>
<point x="600" y="990" type="line"/>
<point x="545" y="990"/>
<point x="501" y="945"/>
</contour>
<contour>
<point x="20" y="710" type="curve"/>
<point x="20" y="710" type="line"/>
<point x="20" y="390"/>
<point x="279" y="131"/>
<point x="600" y="130" type="curve"/>
<point x="600" y="130" type="line"/>
<point x="921" y="130"/>
<point x="1180" y="390"/>
<point x="1180" y="710" type="curve"/>
<point x="1180" y="710" type="line"/>
<point x="1180" y="1031"/>
<point x="920" y="1290"/>
<point x="600" y="1290" type="curve"/>
<point x="600" y="1191" type="line"/>
<point x="600" y="1092" type="line"/>
<point x="600" y="1092" type="line"/>
<point x="705" y="1092"/>
<point x="800" y="1049"/>
<point x="870" y="980" type="curve"/>
<point x="870" y="980" type="line"/>
<point x="939" y="910"/>
<point x="982" y="816"/>
<point x="982" y="710" type="curve"/>
<point x="982" y="710" type="line"/>
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<point x="939" y="510"/>
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<point x="870" y="440" type="line"/>
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<point x="330" y="440" type="line"/>
<point x="261" y="510"/>
<point x="218" y="604"/>
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<point x="218" y="710" type="line"/>
<point x="218" y="816"/>
<point x="261" y="910"/>
<point x="330" y="980" type="curve"/>
<point x="330" y="980" type="line"/>
<point x="400" y="1049"/>
<point x="494" y="1092"/>
<point x="600" y="1092" type="curve"/>
<point x="600" y="1191" type="line"/>
<point x="600" y="1290" type="line"/>
<point x="600" y="1290" type="line"/>
<point x="279" y="1290"/>
<point x="20" y="1031"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/Unicode_IEC_symbol_font.ufo/glyphs/P_O_W_E_R_ O_N_-O_F_F_ S_Y_M_B_O_L_.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/Unicode_IEC_symbol_font.ufo/glyphs/P_O_W_E_R_ O_N_-O_F_F_ S_Y_M_B_O_L_.glif",
"repo_id": "cascadia-code",
"token_count": 1454
}
| 702 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="arrow-right" format="2">
<advance width="1200"/>
<unicode hex="EA9C"/>
<note>
arrow-right
</note>
<outline>
<contour>
<point x="623" y="261" type="line"/>
<point x="695" y="194" type="line"/>
<point x="1180" y="674" type="line"/>
<point x="1180" y="746" type="line"/>
<point x="695" y="1226" type="line"/>
<point x="623" y="1159" type="line"/>
<point x="1025" y="756" type="line"/>
<point x="20" y="756" type="line"/>
<point x="20" y="664" type="line"/>
<point x="1025" y="664" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/arrow-right.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/arrow-right.glif",
"repo_id": "cascadia-code",
"token_count": 305
}
| 703 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="chevron-up" format="2">
<advance width="1200"/>
<unicode hex="EAB7"/>
<note>
chevron-up
</note>
<outline>
<contour>
<point x="1106" y="403" type="line"/>
<point x="1180" y="477" type="line"/>
<point x="634" y="1017" type="line"/>
<point x="566" y="1017" type="line"/>
<point x="20" y="477" type="line"/>
<point x="94" y="403" type="line"/>
<point x="597" y="912" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/chevron-up.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/chevron-up.glif",
"repo_id": "cascadia-code",
"token_count": 245
}
| 704 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="debug-stop" format="2">
<advance width="1200"/>
<unicode hex="EAD7"/>
<note>
debug-stop
</note>
<outline>
<contour>
<point x="1180" y="1290" type="line"/>
<point x="20" y="1290" type="line"/>
<point x="20" y="130" type="line"/>
<point x="1180" y="130" type="line"/>
</contour>
<contour>
<point x="1056" y="1166" type="line"/>
<point x="1056" y="249" type="line"/>
<point x="139" y="249" type="line"/>
<point x="139" y="1166" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/debug-stop.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/debug-stop.glif",
"repo_id": "cascadia-code",
"token_count": 280
}
| 705 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="empty-window" format="2">
<advance width="1200"/>
<unicode hex="EAE4"/>
<note>
empty-window
</note>
<outline>
<contour>
<point x="330" y="1251" type="line"/>
<point x="251" y="1251" type="line"/>
<point x="251" y="1020" type="line"/>
<point x="20" y="1020" type="line"/>
<point x="20" y="941" type="line"/>
<point x="251" y="941" type="line"/>
<point x="251" y="710" type="line"/>
<point x="330" y="710" type="line"/>
<point x="330" y="941" type="line"/>
<point x="561" y="941" type="line"/>
<point x="561" y="1020" type="line"/>
<point x="330" y="1020" type="line"/>
</contour>
<contour>
<point x="136" y="169" type="line"/>
<point x="1143" y="169" type="line"/>
<point x="1180" y="206" type="line"/>
<point x="1180" y="1057" type="line"/>
<point x="1143" y="1098" type="line"/>
<point x="639" y="1098" type="line"/>
<point x="639" y="1020" type="line"/>
<point x="1106" y="1020" type="line"/>
<point x="1106" y="867" type="line"/>
<point x="639" y="867" type="line"/>
<point x="639" y="788" type="line"/>
<point x="1106" y="788" type="line"/>
<point x="1106" y="248" type="line"/>
<point x="177" y="248" type="line"/>
<point x="177" y="632" type="line"/>
<point x="98" y="632" type="line"/>
<point x="98" y="206" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/empty-window.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/empty-window.glif",
"repo_id": "cascadia-code",
"token_count": 725
}
| 706 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="file-zip" format="2">
<advance width="1200"/>
<unicode hex="EAEF"/>
<note>
file-zip
</note>
<outline>
<contour>
<point x="20" y="1339" type="line"/>
<point x="20" y="81" type="line"/>
<point x="66" y="35" type="line"/>
<point x="1030" y="35" type="line"/>
<point x="1082" y="81" type="line"/>
<point x="1082" y="736" type="line"/>
<point x="1165" y="823" type="line"/>
<point x="1180" y="854" type="line"/>
<point x="1180" y="1339" type="line"/>
<point x="1128" y="1385" type="line"/>
<point x="66" y="1385" type="line"/>
</contour>
<contour>
<point x="407" y="1097" type="line"/>
<point x="309" y="1097" type="line"/>
<point x="309" y="1293" type="line"/>
<point x="407" y="1293" type="line"/>
</contour>
<contour>
<point x="407" y="225" type="line"/>
<point x="309" y="225" type="line"/>
<point x="309" y="133" type="line"/>
<point x="113" y="133" type="line"/>
<point x="113" y="1293" type="line"/>
<point x="211" y="1293" type="line"/>
<point x="211" y="1050" type="line"/>
<point x="257" y="999" type="line"/>
<point x="309" y="999" type="line"/>
<point x="309" y="906" type="line"/>
<point x="407" y="906" type="line"/>
<point x="407" y="999" type="line"/>
<point x="453" y="999" type="line"/>
<point x="499" y="1050" type="line"/>
<point x="499" y="1293" type="line"/>
<point x="695" y="1293" type="line"/>
<point x="695" y="860" type="line"/>
<point x="711" y="823" type="line"/>
<point x="793" y="741" type="line"/>
<point x="793" y="133" type="line"/>
<point x="407" y="133" type="line"/>
</contour>
<contour>
<point x="499" y="323" type="line"/>
<point x="499" y="225" type="line"/>
<point x="407" y="225" type="line"/>
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</contour>
<contour>
<point x="309" y="421" type="line"/>
<point x="309" y="323" type="line"/>
<point x="407" y="323" type="line"/>
<point x="407" y="421" type="line"/>
</contour>
<contour>
<point x="407" y="421" type="line"/>
<point x="499" y="421" type="line"/>
<point x="499" y="519" type="line"/>
<point x="407" y="519" type="line"/>
</contour>
<contour>
<point x="309" y="612" type="line"/>
<point x="309" y="519" type="line"/>
<point x="407" y="519" type="line"/>
<point x="407" y="612" type="line"/>
</contour>
<contour>
<point x="407" y="612" type="line"/>
<point x="499" y="612" type="line"/>
<point x="499" y="710" type="line"/>
<point x="407" y="710" type="line"/>
</contour>
<contour>
<point x="309" y="808" type="line"/>
<point x="309" y="710" type="line"/>
<point x="407" y="710" type="line"/>
<point x="407" y="808" type="line"/>
</contour>
<contour>
<point x="407" y="906" type="line"/>
<point x="407" y="808" type="line"/>
<point x="499" y="808" type="line"/>
<point x="499" y="906" type="line"/>
</contour>
<contour>
<point x="984" y="756" type="line"/>
<point x="984" y="133" type="line"/>
<point x="886" y="133" type="line"/>
<point x="886" y="762" type="line"/>
<point x="871" y="798" type="line"/>
<point x="793" y="875" type="line"/>
<point x="793" y="1293" type="line"/>
<point x="1082" y="1293" type="line"/>
<point x="1082" y="875" type="line"/>
<point x="1000" y="792" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/file-zip.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/file-zip.glif",
"repo_id": "cascadia-code",
"token_count": 1773
}
| 707 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="graph-scatter" format="2">
<advance width="1200"/>
<unicode hex="EBE3"/>
<note>
graph-scatter
</note>
<outline>
<contour>
<point x="104" y="210" type="line"/>
<point x="104" y="1290" type="line"/>
<point x="20" y="1290" type="line"/>
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</contour>
<contour>
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<point x="516" y="958" type="line"/>
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<point x="352" y="1126" type="line"/>
</contour>
<contour>
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<point x="1100" y="1042" type="line"/>
<point x="1100" y="1206" type="line"/>
<point x="932" y="1206" type="line"/>
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<contour>
<point x="600" y="710" type="line"/>
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<point x="768" y="874" type="line"/>
<point x="600" y="874" type="line"/>
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<contour>
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<point x="516" y="542" type="line"/>
<point x="352" y="542" type="line"/>
</contour>
<contour>
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<point x="1100" y="462" type="line"/>
<point x="1100" y="626" type="line"/>
<point x="932" y="626" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/graph-scatter.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/graph-scatter.glif",
"repo_id": "cascadia-code",
"token_count": 738
}
| 708 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="preview" format="2">
<advance width="1200"/>
<unicode hex="EB2F"/>
<note>
preview
</note>
<outline>
<contour>
<point x="20" y="1124" type="line"/>
<point x="20" y="292" type="line"/>
<point x="104" y="212" type="line"/>
<point x="1100" y="212" type="line"/>
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<point x="1100" y="1208" type="line"/>
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<contour>
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<point x="1100" y="1124" type="line"/>
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<point x="104" y="292" type="line"/>
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<point x="1016" y="1040" type="line"/>
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<contour>
<point x="932" y="956" type="line"/>
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<point x="268" y="956" type="line"/>
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<point x="684" y="376" type="line"/>
<point x="1016" y="376" type="line"/>
<point x="1016" y="708" type="line"/>
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<contour>
<point x="768" y="460" type="line"/>
<point x="768" y="624" type="line"/>
<point x="932" y="624" type="line"/>
<point x="932" y="460" type="line"/>
</contour>
<contour>
<point x="516" y="624" type="line"/>
<point x="516" y="708" type="line"/>
<point x="184" y="708" type="line"/>
<point x="184" y="624" type="line"/>
</contour>
<contour>
<point x="184" y="376" type="line"/>
<point x="516" y="376" type="line"/>
<point x="516" y="460" type="line"/>
<point x="184" y="460" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/preview.glif/0
|
{
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"repo_id": "cascadia-code",
"token_count": 946
}
| 709 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="remove" format="2">
<advance width="1200"/>
<unicode hex="EB3B"/>
<note>
remove
</note>
<outline>
<contour>
<point x="1180" y="752" type="line"/>
<point x="20" y="752" type="line"/>
<point x="20" y="668" type="line"/>
<point x="1180" y="668" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/remove.glif/0
|
{
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"repo_id": "cascadia-code",
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}
| 710 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="ruby" format="2">
<advance width="1200"/>
<unicode hex="EB48"/>
<note>
ruby
</note>
<outline>
<contour>
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<point x="857" y="1075" type="line"/>
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<point x="821" y="991" type="line"/>
<point x="600" y="991" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/ruby.glif/0
|
{
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"repo_id": "cascadia-code",
"token_count": 524
}
| 711 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="settings" format="2">
<advance width="1200"/>
<unicode hex="EB52"/>
<note>
settings
</note>
<outline>
<contour>
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<point x="228" y="1208" type="line"/>
<point x="144" y="1208" type="line"/>
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</contour>
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<point x="1056" y="212" type="line"/>
<point x="1056" y="376" type="line"/>
<point x="972" y="376" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/settings.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/settings.glif",
"repo_id": "cascadia-code",
"token_count": 1205
}
| 712 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="symbol-class" format="2">
<advance width="1200"/>
<unicode hex="EB5B"/>
<note>
symbol-class
</note>
<outline>
<contour>
<point x="783" y="672" type="line"/>
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<point x="954" y="554" type="line"/>
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</contour>
<contour>
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<point x="1036" y="861" type="line"/>
<point x="1090" y="812" type="line"/>
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<contour>
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</contour>
<contour>
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<point x="110" y="924" type="line"/>
<point x="386" y="1200" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/symbol-class.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/symbol-class.glif",
"repo_id": "cascadia-code",
"token_count": 1080
}
| 713 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="type-hierarchy-sub" format="2">
<advance width="1200"/>
<unicode hex="EBBA"/>
<note>
type-hierarchy-sub
</note>
<outline>
<contour>
<point x="1180" y="396" type="line"/>
<point x="1132" y="444" type="line"/>
<point x="980" y="444" type="line"/>
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<point x="377" y="1290" type="line"/>
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<point x="377" y="130" type="line"/>
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</contour>
<contour>
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</contour>
<contour>
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<point x="110" y="178" type="line"/>
</contour>
<contour>
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<point x="1090" y="178" type="line"/>
<point x="909" y="178" type="line"/>
<point x="909" y="353" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/type-hierarchy-sub.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/type-hierarchy-sub.glif",
"repo_id": "cascadia-code",
"token_count": 1037
}
| 714 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="vm" format="2">
<advance width="1200"/>
<unicode hex="EA7A"/>
<note>
vm
</note>
<outline>
<contour>
<point x="1180" y="1206" type="line"/>
<point x="1140" y="1250" type="line"/>
<point x="60" y="1250" type="line"/>
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<point x="684" y="334" type="line"/>
<point x="1140" y="334" type="line"/>
<point x="1180" y="378" type="line"/>
</contour>
<contour>
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<point x="1100" y="418" type="line"/>
<point x="104" y="418" type="line"/>
<point x="104" y="1166" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/vm.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/codicon.ufo/glyphs/vm.glif",
"repo_id": "cascadia-code",
"token_count": 520
}
| 715 |
<?xml version='1.0' encoding='UTF-8'?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>ascender</key>
<integer>960</integer>
<key>capHeight</key>
<integer>0</integer>
<key>descender</key>
<integer>-64</integer>
<key>familyName</key>
<string>icomoon</string>
<key>guidelines</key>
<array/>
<key>italicAngle</key>
<integer>0</integer>
<key>openTypeHeadCreated</key>
<string>2015/05/02 10:07:53</string>
<key>openTypeHheaAscender</key>
<integer>960</integer>
<key>openTypeHheaDescender</key>
<integer>-64</integer>
<key>openTypeNameDescription</key>
<string></string>
<key>openTypeNamePreferredSubfamilyName</key>
<string>Regular</string>
<key>openTypeOS2Panose</key>
<array>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
<integer>0</integer>
</array>
<key>openTypeOS2StrikeoutPosition</key>
<integer>265</integer>
<key>openTypeOS2StrikeoutSize</key>
<integer>51</integer>
<key>openTypeOS2Type</key>
<array/>
<key>openTypeOS2TypoAscender</key>
<integer>960</integer>
<key>openTypeOS2TypoDescender</key>
<integer>-64</integer>
<key>openTypeOS2TypoLineGap</key>
<integer>64</integer>
<key>openTypeOS2UnicodeRanges</key>
<array>
<integer>0</integer>
<integer>60</integer>
</array>
<key>openTypeOS2VendorID</key>
<string></string>
<key>openTypeOS2WeightClass</key>
<integer>400</integer>
<key>openTypeOS2WidthClass</key>
<integer>5</integer>
<key>openTypeOS2WinAscent</key>
<integer>960</integer>
<key>openTypeOS2WinDescent</key>
<integer>64</integer>
<key>postscriptBlueValues</key>
<array/>
<key>postscriptFamilyBlues</key>
<array/>
<key>postscriptFamilyOtherBlues</key>
<array/>
<key>postscriptFontName</key>
<string>icomoon</string>
<key>postscriptOtherBlues</key>
<array/>
<key>postscriptStemSnapH</key>
<array/>
<key>postscriptStemSnapV</key>
<array/>
<key>styleMapStyleName</key>
<string>regular</string>
<key>styleName</key>
<string>Regular</string>
<key>unitsPerEm</key>
<integer>2048</integer>
<key>versionMajor</key>
<integer>0</integer>
<key>versionMinor</key>
<integer>0</integer>
<key>xHeight</key>
<integer>0</integer>
</dict>
</plist>
|
cascadia-code/sources/nerdfonts/full/processed/devicons.ufo/fontinfo.plist/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/devicons.ufo/fontinfo.plist",
"repo_id": "cascadia-code",
"token_count": 1195
}
| 716 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="cc-nc-eu" format="2">
<advance width="1200"/>
<unicode hex="E293"/>
<note>
cc-nc-eu
</note>
<outline>
<contour>
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<point x="1011" y="1121" type="qcurve" smooth="yes"/>
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</contour>
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</contour>
<contour>
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</outline>
<lib>
<dict>
<key>com.schriftgestaltung.Glyphs.lastChange</key>
<string>2024-02-27 18:45:39 +0000</string>
</dict>
</lib>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/font-awesome-extension.ufo/glyphs/cc-nc-eu.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/font-awesome-extension.ufo/glyphs/cc-nc-eu.glif",
"repo_id": "cascadia-code",
"token_count": 1817
}
| 717 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="RepRap" format="2">
<advance width="1200"/>
<unicode hex="F352"/>
<note>
RepRap
</note>
<outline>
<contour>
<point x="183" y="1005" type="line" smooth="yes"/>
<point x="12" y="833"/>
<point x="12" y="587" type="qcurve" smooth="yes"/>
<point x="12" y="343"/>
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<point x="1017" y="1005" type="qcurve" smooth="yes"/>
<point x="599" y="1420" type="line"/>
</contour>
</outline>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/font-logos.ufo/glyphs/R_epR_ap.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/font-logos.ufo/glyphs/R_epR_ap.glif",
"repo_id": "cascadia-code",
"token_count": 292
}
| 718 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="circle" format="2">
<advance width="1200"/>
<unicode hex="F4AA"/>
<note>
circle
</note>
<outline>
<contour>
<point x="112" y="378"/>
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</contour>
</outline>
<lib>
<dict>
<key>com.schriftgestaltung.Glyphs.lastChange</key>
<string>2024-02-27 18:49:53 +0000</string>
</dict>
</lib>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/octicons.ufo/glyphs/circle.glif/0
|
{
"file_path": "cascadia-code/sources/nerdfonts/full/processed/octicons.ufo/glyphs/circle.glif",
"repo_id": "cascadia-code",
"token_count": 716
}
| 719 |
<?xml version='1.0' encoding='UTF-8'?>
<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
<key>i_custom_asm</key>
<string>i_custom_asm.glif</string>
<key>i_custom_c</key>
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|
cascadia-code/sources/nerdfonts/full/processed/original-source.ufo/glyphs/contents.plist/0
|
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| 720 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="i_indent_line" format="2">
<advance width="1200"/>
<unicode hex="E621"/>
<note>
i_indent_line
</note>
<outline>
<contour>
<point x="552" y="48" type="curve" smooth="yes"/>
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</contour>
</outline>
<lib>
<dict>
<key>com.schriftgestaltung.Glyphs.lastChange</key>
<string>2024-02-27 18:42:08 +0000</string>
</dict>
</lib>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/original-source.ufo/glyphs/i_indent_line.glif/0
|
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| 721 |
<?xml version='1.0' encoding='UTF-8'?>
<glyph name="i_seti_wat" format="2">
<advance width="1200"/>
<unicode hex="E6A2"/>
<note>
i_seti_wat
</note>
<outline>
<contour>
<point x="370" y="818" type="line"/>
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</contour>
</outline>
<lib>
<dict>
<key>com.schriftgestaltung.Glyphs.lastChange</key>
<string>2024-02-27 18:42:08 +0000</string>
</dict>
</lib>
</glyph>
|
cascadia-code/sources/nerdfonts/full/processed/original-source.ufo/glyphs/i_seti_wat.glif/0
|
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| 722 |
import argparse
import pandas as pd
import pytorch_lightning as pl
import torch
from pytorch_lightning import seed_everything
from pytorch_lightning.callbacks import ModelCheckpoint, TQDMProgressBar
from pytorch_lightning.loggers import MLFlowLogger
from scotch.latent_learning.scotch_data_module import SCOTCHDataModule
from scotch.latent_learning.scotch_module import SCOTCHModule
from tensordict import TensorDict
from causica.datasets.causica_dataset_format import Variable, VariablesMetadata
from causica.datasets.variable_types import VariableTypeEnum
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Run DREAM3 experiments.")
parser.add_argument("-d", "--dimension", type=int, help="dimension of dream3 dataset (10, 50, or 100)")
parser.add_argument("-n", "--name", type=str, help="name of the dataset (Yeast1, Yeast2, Yeast3, Ecoli1, Ecoli2)")
parser.add_argument("-e", "--epoch", type=int, help="max number of epochs", default=20000)
parser.add_argument("-l", "--lr", type=float, help="learning rate", default=3e-3)
parser.add_argument("-s", "--sparsity", type=float, help="sparsity penalty", default=500)
parser.add_argument("-t", "--dt", type=float, help="dt", default=0.05)
parser.add_argument("-nor", "--normalize", action="store_true", help="whether to normalize")
parser.add_argument("-sd", "--seed", type=int, help="random seed", required=True)
parser.add_argument("-en", "--experiment_name", type=str, help="experiment name", required=True)
parser.add_argument("-res", "--res_connection", action="store_true", help="whether to use res_connection")
parser.add_argument("-ln", "--layer_norm", action="store_true", help="whether to use layer_norm")
parser.add_argument("-warm", "--lr_warmup", type=int, default=10000, help="warmup epochs")
parser.add_argument("-deci", "--deci_diffusion", action="store_true", help="whether to use deci diffusion function")
parser.add_argument(
"-sig",
"--sigmoid_output",
action="store_true",
help="whether to use sigmoid output for deci diffusion function",
)
args = parser.parse_args()
# set seed
seed_everything(args.seed)
# HParams
experiment_name = args.experiment_name
max_epochs = args.epoch
default_lr = args.lr
lrs = {
"graph": default_lr, # changed from 1e-2
"qz0_mean_net": default_lr,
"qz0_logstd_net": default_lr,
"pz0_mean": default_lr,
"pz0_logstd": default_lr,
"prior_drift_fn": default_lr,
"diffusion_fn": default_lr,
"posterior_drift_fn": default_lr,
"trajectory_encoder": default_lr,
}
prior_sparsity_lambda = args.sparsity
t_max = 1.05
num_time_points = 21
dt = args.dt # sde solver dt = observation interval
normalize = args.normalize
lr_warmup_iters = 100
res_connection = args.res_connection
layer_norm = args.layer_norm
deci_diffusion = args.deci_diffusion
sigmoid_output = args.sigmoid_output
hparams = {
"seed": args.seed,
"epoch": args.epoch,
"normalize": args.normalize,
"prior_sparsity_lambda": prior_sparsity_lambda,
"t_max": t_max,
"num_time_points": num_time_points,
"dt": dt,
"default_lr": default_lr,
"lr_warmup_iters": lr_warmup_iters,
"res_connection": res_connection,
"layer_norm": layer_norm,
"deci_diffusion": deci_diffusion,
"sigmoid_output": sigmoid_output,
}
# DREAM3
state_size = args.dimension
variables_metadata = VariablesMetadata(
[Variable(name=f"x{i}", type=VariableTypeEnum.CONTINUOUS, group_name=f"x{i}") for i in range(state_size)]
)
ts = torch.linspace(0, t_max, num_time_points)
training_data_df = pd.read_csv(
f"data/DREAM3 in silico challenge/Size{args.dimension}/DREAM3 data/InSilicoSize{args.dimension}-{args.name}-trajectories.tsv",
sep="\t",
).drop("Time", axis=1)
training_data = torch.tensor(training_data_df.values, device="cuda").view(
-1, num_time_points, state_size
) # (batch, t, vars)
training_data = (
(training_data - training_data.mean(dim=(0, 1))) / training_data.std(dim=(0, 1)) if normalize else training_data
)
training_data = TensorDict(
{f"x{i}": training_data[:, :, i].unsqueeze(dim=2) for i in range(state_size)},
batch_size=[training_data.shape[0]],
)
edges_df = pd.read_csv(
f"data/DREAM3 in silico challenge/Size{args.dimension}/Networks/InSilicoSize{args.dimension}-{args.name}.tsv",
sep="\t",
header=None,
).drop(2, axis=1)
true_graph = torch.zeros((state_size, state_size), dtype=torch.int64, device="cuda")
edges_df = edges_df.applymap(lambda x: int(x[1:]))
edges = torch.tensor(edges_df.values, device="cuda")
for edge in edges:
true_graph[edge[0] - 1, edge[1] - 1] = 1 # 0-indexed
validation_data = training_data
#####
scotch_data = SCOTCHDataModule(
ts=ts,
training_data=training_data,
validation_data=validation_data,
true_graph=true_graph,
variables_metadata=variables_metadata,
batch_size=1024,
)
# SCOTCH Module
scotch = SCOTCHModule(
learning_rates=lrs,
prior_sparsity_lambda=prior_sparsity_lambda,
dt=dt,
record_graph_logits=args.dimension < 20,
lr_warmup_iters=lr_warmup_iters,
ignore_self_connections=True,
res_connections=res_connection,
layer_norm=layer_norm,
deci_diffusion=deci_diffusion,
add_diffusion_self_connections=True,
sigmoid_output=sigmoid_output,
)
mlf_logger = MLFlowLogger(
experiment_name=experiment_name,
tracking_uri="file:./mlflow_logs/mlruns",
)
mlf_logger.log_hyperparams(hparams)
trainer = pl.Trainer(
accelerator="gpu",
max_epochs=max_epochs,
fast_dev_run=False,
callbacks=[
TQDMProgressBar(refresh_rate=19),
ModelCheckpoint(every_n_epochs=500, dirpath="./outputs", save_last=True),
],
check_val_every_n_epoch=50,
logger=mlf_logger,
)
trainer.fit(scotch, datamodule=scotch_data)
|
causica/research_experiments/scotch/src/scotch/experiments/dream3.py/0
|
{
"file_path": "causica/research_experiments/scotch/src/scotch/experiments/dream3.py",
"repo_id": "causica",
"token_count": 2711
}
| 723 |
class_path: causica.lightning.data_modules.variable_spec_data.CSuiteDataModule
init_args:
dataset_name: csuite_nonlingauss
batch_size: 128
load_counterfactual: false
load_interventional: true
|
causica/src/causica/config/lightning/default_data.yaml/0
|
{
"file_path": "causica/src/causica/config/lightning/default_data.yaml",
"repo_id": "causica",
"token_count": 69
}
| 724 |
import fsspec
import numpy as np
import torch
from causica.distributions.adjacency import ExpertGraphContainer
class LoadedExpertGraphContainer(ExpertGraphContainer):
"""Loads an expert graph container from a file path."""
def __init__(self, graph_path: str, confidence: float, scale: float):
"""
Args:
graph_path: fsspec compatible path to a saved graph, with np.nan indicating undecided values.
This can be saved as a .npy file or a .csv file.
confidence: See ExpertGraphContainer
scale: See ExpertGraphContainer
"""
with fsspec.open(graph_path) as f:
if graph_path.endswith(".csv"):
prior_adj_matrix = np.loadtxt(f, delimiter=",")
else:
prior_adj_matrix = np.load(f)
prior_mask = ~np.isnan(prior_adj_matrix)
prior_adj_matrix = np.nan_to_num(prior_adj_matrix)
super().__init__(
dag=torch.tensor(prior_adj_matrix), mask=torch.tensor(prior_mask), confidence=confidence, scale=scale
)
|
causica/src/causica/datasets/loaded_expert_graph_container.py/0
|
{
"file_path": "causica/src/causica/datasets/loaded_expert_graph_container.py",
"repo_id": "causica",
"token_count": 471
}
| 725 |
import torch
import torch.nn.functional as F
def gumbel_softmax_binary(logits: torch.Tensor, tau: float, hard: bool = False) -> torch.Tensor:
"""
Calculate the gumbel softmax for binary logits.
Args:
logits: A tensor of binary logits of shape (...)
tau: Temperature of the gumbel softmax
hard: whether samples should be hard {0, 1} or soft (in [0, 1])
Returns:
Tensor of shape (...)
"""
stacked_logits = torch.stack([torch.zeros_like(logits, device=logits.device), logits], dim=-1) # (..., 2)
return F.gumbel_softmax(stacked_logits, tau=tau, hard=hard, dim=-1)[..., 1] # (...) binary
|
causica/src/causica/distributions/gumbel_binary.py/0
|
{
"file_path": "causica/src/causica/distributions/gumbel_binary.py",
"repo_id": "causica",
"token_count": 261
}
| 726 |
import torch
from tensordict import TensorDict, TensorDictBase
from torch.distributions.constraints import Constraint
from causica.distributions.transforms.base import TypedTransform
class TensorToTensorDictTransform(TypedTransform[torch.Tensor, TensorDictBase]):
"""
A transform for converting a torch tensor to a TensorDict.
It extracts the slices from the last dimension of the tensor and assigns them to the correct key.
"""
arg_constraints: dict[str, Constraint] = {}
bijective = True
def __init__(self, shapes: dict[str, torch.Size]):
"""
Args:
shapes: the shapes of each of the keys
"""
super().__init__()
self.shapes = shapes
self.num_keys = len(shapes)
self.output_shape, self.slices = shapes_to_slices(self.shapes)
def _call(self, x: torch.Tensor) -> TensorDictBase:
"""Create a Tensordict by retrieving the slice associated with each key."""
return TensorDict({name: x[..., slice_] for name, slice_ in self.slices.items()}, batch_size=x.shape[:-1])
def _inverse(self, y: TensorDictBase) -> torch.Tensor:
"""
Create a tensor by stacking the slice associated with each key.
Args:
y: Tensordict with batch_shape
Returns:
A tensor with shape batch_shape + [output_shape]
"""
return torch.cat([y[name] for name in self.slices], dim=-1)
def log_abs_det_jacobian(self, _: torch.Tensor, y: TensorDictBase) -> TensorDictBase:
"""This transformation doesn't affect the log det jacobian"""
return y.apply(torch.zeros_like)
def stacked_key_masks(self) -> torch.Tensor:
"""
Create a binary of matrix of where each key is in the tensor.
Returns:
A matrix of shape [num_keys, output_shape] with 1 if the index of the tensor
belongs to the key corresponding to that row
"""
stacked_key_masks = torch.zeros((self.num_keys, self.output_shape), dtype=torch.float)
for i, slice_ in enumerate(self.slices.values()):
stacked_key_masks[i, slice_] = 1.0
return stacked_key_masks
def order_td(self, td: TensorDictBase) -> TensorDictBase:
"""Order the keys of a TensorDict to match the order of the shapes."""
return td.select(*self.shapes.keys(), inplace=True)
def shapes_to_slices(shapes: dict[str, torch.Size]) -> tuple[int, dict[str, slice]]:
"""
Convert a dictionary of shapes to a dictionary of masks by stacking the shapes
Each mask corresponds to the embedded location in the tensor
Args:
shapes: A dict of key names to shapes
Returns:
The shape of the stacked tensor and a dictionary of each key to the mask
"""
assert all(len(shape) == 1 for shape in shapes.values())
slices: dict[str, slice] = {}
idx = 0
next_idx = 0
for name, shape in shapes.items():
next_idx = idx + shape[-1]
slices[name] = slice(idx, next_idx)
idx = next_idx
return next_idx, slices
|
causica/src/causica/distributions/transforms/tensor_to_tensordict.py/0
|
{
"file_path": "causica/src/causica/distributions/transforms/tensor_to_tensordict.py",
"repo_id": "causica",
"token_count": 1234
}
| 727 |
import inspect
from collections import defaultdict
from typing import Callable
import pytorch_lightning as pl
from torch.utils.data import ConcatDataset, DataLoader
from causica.data_generation.samplers.sem_sampler import SEMSampler
from causica.datasets.samplers import SubsetBatchSampler
from causica.datasets.synthetic_dataset import CausalMetaset
class SyntheticDataModule(pl.LightningDataModule):
"""A datamodule to produce datasets and their underlying causal graphs and interventions.
This datamodule samples synthetic datasets from a list of SEM samplers and returns batches of CausalDataset objects.
This means, that the underlying tensors are not yet stacked and will need to be processed by the module using the
data. Currently, the data module uses the `SubsetBatchSampler` to sample batches from the different sampled SEMs,
ensuring that each batch is sampled from SEMs with the same number of nodes. This is important, as it allows for
easy batching of the data, as the tensors are already of the same shape.
Note:
This data module does currently not support DDP, because the batch sampler does not simply consume indices
from a a regular sampler. In future, DDP support will be added by ensuring that each compute node is individually
seeded to generate different data samples and adapting the batch sampler to ensure that an epoch has the same length
regardless of the number of compute nodes.
This data module might generate duplicate data samples, when num_workers > 1. This is because the individual
workers are not individually seeded.
"""
def __init__(
self,
sem_samplers: list[SEMSampler] | Callable[[], list[SEMSampler]],
train_batch_size: int,
test_batch_size: int,
dataset_size: int,
num_interventions: int = 0,
num_intervention_samples: int = 100,
num_sems: int = 0,
batches_per_metaset: int = 1,
sample_interventions: bool = False,
sample_counterfactuals: bool = False,
num_workers: int = 0,
pin_memory: bool = True,
persistent_workers: bool = True,
prefetch_factor: int = 16,
) -> None:
"""
Args:
sem_samplers: Either a list of sem samplers or a function that returns a list of SEM samplers
train_batch_size: The training batch size to use
test_batch_size: The testing batch size to use
dataset_size: The size of dataset to generate
num_interventions: The number of interventions to generate (0 for no interventions)
num_sems: The number of SEMs to generate (0 for infinite SEMs)
batches_per_metaset: The number of batches per epoch per dataset
sample_interventions: Whether to sample interventions
sample_counterfactuals: Whether to sample counterfactuals
num_workers: The number of workers to use for the dataloader
pin_memory: Whether to pin memory for the dataloader
persistent_workers: Whether to use persistent workers for the dataloader
prefetch_factor: The prefetch factor to use for the dataloader
"""
super().__init__()
self.dataset_size = dataset_size
self.train_batch_size = train_batch_size
self.test_batch_size = test_batch_size
if callable(sem_samplers) and inspect.isclass(type(sem_samplers)):
self.sem_samplers_hparams = vars(sem_samplers)
elif callable(sem_samplers):
self.sem_samplers_hparams = {k: v.default for k, v in inspect.signature(sem_samplers).parameters.items()}
else:
self.sem_samplers_hparams = {}
self.sem_sampler_list = sem_samplers if isinstance(sem_samplers, list) else sem_samplers()
self.num_interventions = num_interventions
self.num_intervention_samples = num_intervention_samples
self.num_workers = num_workers
self.num_sems = num_sems
self.batches_per_metaset = batches_per_metaset
self.sample_interventions = sample_interventions
self.sample_counterfactuals = sample_counterfactuals
self.num_workers = num_workers
self.persistent_workers = persistent_workers
self.pin_memory = pin_memory
self.prefetch_factor = prefetch_factor
self.save_hyperparameters(logger=False)
self.train_dataset = self._get_dataset(self.train_batch_size)
self.val_dataset = self._get_dataset(self.test_batch_size)
def prepare_data(self) -> None:
# Log hyperparameters if trainer is available
if self.trainer and self.trainer.logger:
hyperparams = {k: v for k, v in self.hparams.items() if k != "sem_samplers"}
hyperparams["sem_samplers_hparams"] = self.sem_samplers_hparams
self.trainer.logger.log_hyperparams(hyperparams)
def _get_dataset(self, dataset_size: int) -> ConcatDataset:
"""Builds causal datasets given the SEM samplers.
Args:
dataset_size: Number of samples of the causal dataset (ie number of datasets generated).
Returns:
dataset object
"""
cur_dataset_size = dataset_size * self.batches_per_metaset
if self.num_sems > 0 and cur_dataset_size < self.num_sems:
raise ValueError(
f"Dataset size must be at least the number of SEMs. Got {cur_dataset_size} < {self.num_sems}"
)
datasets_by_nodes = defaultdict(list)
for sampler in self.sem_sampler_list:
datasets_by_nodes[sampler.adjacency_dist.num_nodes].append(
CausalMetaset(
sampler,
sample_dataset_size=self.dataset_size,
dataset_size=cur_dataset_size,
num_interventions=self.num_interventions,
num_intervention_samples=self.num_intervention_samples,
num_sems=self.num_sems,
sample_interventions=self.sample_interventions,
sample_counterfactuals=self.sample_counterfactuals,
)
)
return ConcatDataset(ConcatDataset(ds) for ds in datasets_by_nodes.values())
def train_dataloader(self):
batch_sampler = SubsetBatchSampler([len(d) for d in self.train_dataset.datasets], self.train_batch_size)
return DataLoader(
dataset=self.train_dataset,
batch_sampler=batch_sampler,
collate_fn=lambda x: x,
num_workers=self.num_workers,
persistent_workers=self.persistent_workers,
pin_memory=self.pin_memory,
prefetch_factor=self.prefetch_factor,
)
def val_dataloader(self):
batch_sampler = SubsetBatchSampler([len(d) for d in self.val_dataset.datasets], self.test_batch_size)
return DataLoader(
dataset=self.val_dataset, batch_sampler=batch_sampler, collate_fn=lambda x: x, pin_memory=self.pin_memory
)
def test_dataloader(self):
return self.val_dataloader()
|
causica/src/causica/lightning/data_modules/synthetic_data_module.py/0
|
{
"file_path": "causica/src/causica/lightning/data_modules/synthetic_data_module.py",
"repo_id": "causica",
"token_count": 2944
}
| 728 |
from collections import deque, namedtuple
from dataclasses import dataclass, field
from enum import Enum
from typing import Any, Optional, Tuple, Union
import torch
from dataclasses_json import dataclass_json
from torch.optim import Optimizer
class AugLagOuterConvergenceReason(Enum):
"""
Enum class to represent different reasons for outer loop convergence in AugLag learning rate scheduler.
Attributes:
MAX_OUTER_STEPS_REACHED: Number of outer steps has reached `max_outer_steps`.
PENALTY_TOLERANCE_REACHED: The constraint has been below the `penalty_tolerance` for more than `patience_penalty_reached` steps.
PATIENCE_MAX_RHO_REACHED: Rho has been over `safety_rho` for more than `patience_max_rho` steps.
NOT_CONVERGED: Not converged.
"""
MAX_OUTER_STEPS_REACHED = 1
PENALTY_TOLERANCE_REACHED = 2
PATIENCE_MAX_RHO_REACHED = 3
NOT_CONVERGED = 4
class AugLagInnerConvergenceReason(Enum):
"""
Enum class to represent different reasons for inner loop convergence in AugLag learning rate scheduler.
Attributes:
MAX_INNER_STEPS_REACHED: Number of inner steps has reached `max_inner_steps`.
NUM_LR_UPDATES_REACHED: Number of learning rate updates has reached `max_lr_down`.
EARLY_STOPPING_REACHED: The current step counter is equal to or greater than the sum of the last best step and the inner early stopping patience.
NOT_CONVERGED: Not converged.
"""
MAX_INNER_STEPS_REACHED = 1
NUM_LR_UPDATES_REACHED = 2
EARLY_STOPPING_REACHED = 3
NOT_CONVERGED = 4
AugLagConvergenceReasonTuple = namedtuple(
"AugLagConvergenceReasonTuple", ["inner_convergence_reason", "outer_convergence_reason"]
)
class AugLagLossCalculator(torch.nn.Module):
def __init__(self, init_alpha: float, init_rho: float):
super().__init__()
self.init_alpha = init_alpha
self.init_rho = init_rho
self.alpha: torch.Tensor
self.rho: torch.Tensor
self.register_buffer("alpha", torch.tensor(self.init_alpha, dtype=torch.float))
self.register_buffer("rho", torch.tensor(self.init_rho, dtype=torch.float))
def forward(self, objective: torch.Tensor, constraint: torch.Tensor) -> torch.Tensor:
return objective + self.alpha * constraint + self.rho * constraint * constraint / 2
@dataclass_json
@dataclass
class AugLagLRConfig:
"""Configuration parameters for the AuglagLR scheduler.
Attributes:
lr_update_lag: Number of iterations to wait before updating the learning rate.
lr_update_lag_best: Number of iterations to wait after the best model before updating the learning rate.
lr_init_dict: Dictionary of intitialization parameters for every new inner optimization step. This must contain
all parameter_groups for all optimizers
aggregation_period: Aggregation period to compare the mean of the loss terms across this period.
lr_factor: Learning rate update schedule factor (exponential decay).
penalty_progress_rate: Number of iterations to wait before updating rho based on the dag penalty.
safety_rho: Maximum rho that could be updated to.
safety_alpha: Maximum alpha that could be udated to.
max_lr_down: Maximum number of lr update times to decide inner loop termination.
inner_early_stopping_patience: Maximum number of iterations to run after the best inner loss to terminate inner
loop.
max_outer_steps: Maximum number of outer update steps.
patience_penalty_reached: Maximum number of outer iterations to run after the dag penalty has reached a good
value.
patience_max_rho: Maximum number of iterations to run once rho threshold is reached.
penalty_tolerance: Tolerance of the dag penalty
max_inner_steps: Maximum number of inner loop steps to run.
force_not_converged: If True, it will not be reported as converged until max_outer_steps is reached.
"""
lr_update_lag: int = 500
lr_update_lag_best: int = 250
lr_init_dict: dict[str, float] = field(
default_factory=lambda: {"vardist": 0.1, "functional_relationships": 0.0003, "noise_dist": 0.003}
)
aggregation_period: int = 20
lr_factor: float = 0.1
penalty_progress_rate: float = 0.65
safety_rho: float = 1e13
safety_alpha: float = 1e13
max_lr_down: int = 3
inner_early_stopping_patience: int = 500
max_outer_steps: int = 100
patience_penalty_reached: int = 5
patience_max_rho: int = 3
penalty_tolerance: float = 1e-5
max_inner_steps: int = 3000
force_not_converged: bool = False
class AugLagLR:
"""A Pytorch like scheduler which performs the Augmented Lagrangian optimization procedure.
It consists of an inner loop which optimizes the objective for a fixed set of lagrangian parameters. The lagrangian
parameters are annealed in the outer loop, according to a schedule as specified by the hyperparameters.
"""
def __init__(self, config: AugLagLRConfig) -> None:
"""
Args:
config: An `AugLagLRConfig` object containing the configuration parameters.
"""
self.config = config
self.outer_opt_counter = 0
self.outer_below_penalty_tol = 0
self.outer_max_rho = 0
self._prev_lagrangian_penalty = torch.tensor(torch.inf)
self._cur_lagrangian_penalty = torch.tensor(torch.inf)
self.loss_tracker: deque[torch.Tensor] = deque([], maxlen=config.aggregation_period)
self._init_new_inner_optimisation()
# Track whether auglag is disabled and the state of the loss when it was disabled
self._disabled = False
self._disabled_loss_state: Optional[dict[str, Any]] = None
def _init_new_inner_optimisation(self) -> None:
"""Init the hyperparameters for a new inner loop optimization."""
self.best_loss = torch.tensor(torch.inf)
self.last_lr_update_step = 0
self.num_lr_updates = 0
self.last_best_step = 0
self.loss_tracker.clear()
self.loss_tracker_sum: Optional[torch.Tensor] = None
self.step_counter = 0
def _is_inner_converged(self) -> Tuple[bool, AugLagInnerConvergenceReason]:
"""Check if the inner optimization loop has converged, based on maximum number of inner steps, number of lr updates.
Returns:
bool: Return True if converged, else False.
reason: Reason for convergence.
"""
# Define a dictionary mapping conditions to convergence reasons
conditions = {
AugLagInnerConvergenceReason.MAX_INNER_STEPS_REACHED: self.step_counter >= self.config.max_inner_steps,
AugLagInnerConvergenceReason.NUM_LR_UPDATES_REACHED: self.num_lr_updates >= self.config.max_lr_down,
AugLagInnerConvergenceReason.EARLY_STOPPING_REACHED: self.last_best_step
+ self.config.inner_early_stopping_patience
<= self.step_counter,
}
# Check each condition
for reason, condition in conditions.items():
if condition:
return True, reason
# If none of the conditions were met, return False and NOT_CONVERGED
return False, AugLagInnerConvergenceReason.NOT_CONVERGED
def _is_outer_converged(self) -> Tuple[bool, AugLagOuterConvergenceReason]:
"""Check if the outer loop has converged.
Determined as converged if any of the below conditions are true. If `force_not_converged` is true, only (1) is
checked.
1. Number of outer steps has reached `max_outer_steps`.
2. The constraint has been below the `penalty_tolerance` for more than `patience_penalty_reached` steps.
3. Rho has been over `safety_rho` for more than `patience_max_rho` steps.
Returns:
bool: Return True if outer loop is converged, else False.
reason: Reason for convergence.
"""
conditions = {
AugLagOuterConvergenceReason.MAX_OUTER_STEPS_REACHED: self.outer_opt_counter >= self.config.max_outer_steps,
AugLagOuterConvergenceReason.PENALTY_TOLERANCE_REACHED: self.outer_below_penalty_tol
>= self.config.patience_penalty_reached,
AugLagOuterConvergenceReason.PATIENCE_MAX_RHO_REACHED: self.outer_max_rho >= self.config.patience_max_rho,
}
if self.config.force_not_converged:
return (
conditions[AugLagOuterConvergenceReason.MAX_OUTER_STEPS_REACHED],
AugLagOuterConvergenceReason.MAX_OUTER_STEPS_REACHED,
)
# Check each condition
for reason, condition in conditions.items():
if condition:
return True, reason
# If none of the conditions were met, return False and NOT_CONVERGED
return False, AugLagOuterConvergenceReason.NOT_CONVERGED
def _enough_steps_since_last_lr_update(self) -> bool:
"""Check if enough steps have been taken since the previous learning rate update, based on the previous one.
Returns:
bool: indicating whether sufficient steps have occurred since the last update
"""
return self.last_lr_update_step + self.config.lr_update_lag <= self.step_counter
def _enough_steps_since_best_model(self) -> bool:
"""Check the number of iteration steps which have been passed after seeing the current best model.
Returns:
bool: Returns True if last iteration at which learning rate was
updated and last best loss iteration is less than total steps, else False.
"""
return self.last_best_step + self.config.lr_update_lag_best <= self.step_counter
def _update_lr(self, optimizer: Union[Optimizer, list[Optimizer]]):
"""Update the learning rate of the optimizer(s) based on the lr multiplicative factor.
Args:
optimizer: Optimizers of auglag to be updated.
"""
self.last_lr_update_step = self.step_counter
self.num_lr_updates += 1
if isinstance(optimizer, list):
for opt in optimizer:
for param_group in opt.param_groups:
param_group["lr"] *= self.config.lr_factor
else:
for param_group in optimizer.param_groups:
param_group["lr"] *= self.config.lr_factor
def reset_lr(self, optimizer: Union[Optimizer, list[Optimizer]]):
"""Reset the learning rate of individual param groups from lr init dictionary.
Args:
optimizer: Optimizer(s) corresponding to all param groups.
"""
self.last_lr_update_step = self.step_counter
if isinstance(optimizer, list):
for opt in optimizer:
for param_group in opt.param_groups:
param_group["lr"] = self.config.lr_init_dict[param_group["name"]]
else:
for param_group in optimizer.param_groups:
param_group["lr"] = self.config.lr_init_dict[param_group["name"]]
def _update_lagrangian_params(self, loss: AugLagLossCalculator):
"""Update the lagrangian parameters (of the auglag routine) based on the dag constraint values observed.
Args:
loss: loss with lagrangian attributes rho and alpha to be updated.
"""
if self._cur_lagrangian_penalty < self.config.penalty_tolerance:
self.outer_below_penalty_tol += 1
else:
self.outer_below_penalty_tol = 0
if loss.rho > self.config.safety_rho:
self.outer_max_rho += 1
if self._cur_lagrangian_penalty > self._prev_lagrangian_penalty * self.config.penalty_progress_rate:
print(f"Updating rho, dag penalty prev: {self._prev_lagrangian_penalty: .10f}")
loss.rho *= 10.0
else:
self._prev_lagrangian_penalty = self._cur_lagrangian_penalty
loss.alpha += loss.rho * self._cur_lagrangian_penalty
if self._cur_lagrangian_penalty == 0.0:
loss.alpha *= 5
print(f"Updating alpha to: {loss.alpha}")
if loss.rho >= self.config.safety_rho:
loss.alpha *= 5
# Update parameters and make sure to maintain the dtype and device
loss.alpha = torch.min(loss.alpha, torch.full_like(loss.alpha, self.config.safety_alpha))
loss.rho = torch.min(loss.rho, torch.full_like(loss.rho, self.config.safety_rho))
def _is_auglag_converged(
self, optimizer: Union[Optimizer, list[Optimizer]], loss: AugLagLossCalculator
) -> Tuple[bool, AugLagConvergenceReasonTuple]:
"""Checks if the inner and outer loops have converged. If inner loop is converged,
it initilaizes the optimisation parameters for a new inner loop. If both are converged, it returns True.
Args:
optimizer: Optimizer(s) corresponding to different parameter groups on which auglag is being performed.
loss: Auglag loss.
Returns:
bool: Returns True if both inner and outer have converged, else False
dict: Dictionary of convergence reasons for inner and outer loop
"""
is_inner_converged, inner_convergence_reason = self._is_inner_converged()
is_outer_converged, outer_convergence_reason = self._is_outer_converged()
if is_inner_converged:
if is_outer_converged:
return True, AugLagConvergenceReasonTuple(inner_convergence_reason, outer_convergence_reason)
self._update_lagrangian_params(loss)
self.outer_opt_counter += 1
self._init_new_inner_optimisation()
self.reset_lr(optimizer)
elif self._enough_steps_since_last_lr_update() and self._enough_steps_since_best_model():
self._update_lr(optimizer)
return False, AugLagConvergenceReasonTuple(inner_convergence_reason, outer_convergence_reason)
def _update_loss_tracker(self, loss_value: torch.Tensor):
"""Update the loss tracker with the current loss value.
Args:
loss_value: The current loss value.
"""
if self.loss_tracker_sum is None:
self.loss_tracker_sum = torch.zeros_like(loss_value)
if len(self.loss_tracker) == self.loss_tracker.maxlen:
self.loss_tracker_sum -= self.loss_tracker.popleft()
self.loss_tracker.append(loss_value)
self.loss_tracker_sum += loss_value
def _check_best_loss(self):
"""Update the best loss based on the average loss over an aggregation period."""
if len(self.loss_tracker) == self.loss_tracker.maxlen and self.loss_tracker_sum is not None:
avg_loss = self.loss_tracker_sum / self.loss_tracker.maxlen
if avg_loss < self.best_loss:
self.best_loss = avg_loss
self.last_best_step = self.step_counter
@property
def disabled(self) -> bool:
return self._disabled
def enable(self, loss: AugLagLossCalculator) -> None:
"""Enable auglag with the given loss calculator.
If auglag is disabled, this will restore the loss calculator state to the state when it was disabled and will
allow `step` to increment auglag iterations again.
Args:
loss: The loss calculator used with this scheduler
"""
if not self._disabled:
return
if self._disabled_loss_state is not None:
loss.load_state_dict(self._disabled_loss_state)
self._disabled_loss_state = None
self._disabled = False
def disable(self, loss: AugLagLossCalculator) -> None:
"""Disable auglag with the given loss calculator.
If auglag is enabled, this disables auglag iterations when `step` is called, stores the current state of the
loss so that it can be re-enabled and sets the constraint factors in the loss calculator to 0.
Args:
loss: The loss calculator used with this scheduler
"""
if self._disabled:
return
self._disabled_loss_state = loss.state_dict()
loss.alpha = torch.zeros_like(loss.alpha)
loss.rho = torch.zeros_like(loss.rho)
self._disabled = True
def step(
self,
optimizer: Union[Optimizer, list[Optimizer]],
loss: AugLagLossCalculator,
loss_value: torch.Tensor,
lagrangian_penalty: torch.Tensor,
) -> Tuple[bool, AugLagConvergenceReasonTuple]:
"""The main update method to take one auglag inner step.
Args:
optimizer: Optimizer(s) corresponding to different param groups.
loss: auglag loss with lagrangian parameters
loss_value: the actual value of the elbo for the current update step.
lagrangian_penalty: Dag penalty for the current update step.
Returns:
bool: if the auglag has converged (False) or not (True)
reason: named tuple (`AugLagConvergenceReasonTuple`) of convergence reasons for inner and outer loop, see
also `AugLagInnerConvergenceReason` and `AugLagOuterConvergenceReason`.
"""
if self.disabled:
return False, AugLagConvergenceReasonTuple(
AugLagInnerConvergenceReason.NOT_CONVERGED, AugLagOuterConvergenceReason.NOT_CONVERGED
)
assert torch.all(lagrangian_penalty >= 0), "auglag penalty must be non-negative"
self._update_loss_tracker(loss_value.detach())
self._cur_lagrangian_penalty = lagrangian_penalty.detach()
self.step_counter += 1
self._check_best_loss()
return self._is_auglag_converged(optimizer=optimizer, loss=loss)
|
causica/src/causica/training/auglag.py/0
|
{
"file_path": "causica/src/causica/training/auglag.py",
"repo_id": "causica",
"token_count": 7163
}
| 729 |
"""Module with ENCO specific tests."""
import numpy as np
import torch
from torch.distributions.utils import probs_to_logits
from causica.distributions.adjacency.enco import ENCOAdjacencyDistribution
def test_enco_entropy():
"""Test ENCO entropy is correct for a known distribution."""
eps = 1e-7
probs_exist = torch.tensor([[0.0, 1.0 - eps], [1.0 - eps, 0.0]])
probs_orient = torch.tensor([0.5])
logits_exist = torch.nn.Parameter(probs_to_logits(probs_exist, is_binary=True), requires_grad=True)
logits_orient = torch.nn.Parameter(probs_to_logits(probs_orient, is_binary=True), requires_grad=True)
dist = ENCOAdjacencyDistribution(logits_exist=logits_exist, logits_orient=logits_orient)
entropy = dist.entropy()
np.testing.assert_allclose(entropy.detach(), 2 * np.log(2))
entropy.backward()
np.testing.assert_allclose(logits_exist.grad, np.zeros_like(logits_exist.detach().numpy()), atol=1e-7)
np.testing.assert_allclose(logits_orient.grad, np.zeros_like(logits_orient.detach().numpy()), atol=1e-7)
optim = torch.optim.SGD((logits_orient, logits_exist), lr=1e-2, momentum=0.9)
optim.step()
def test_enco_backprop():
"""Test ENCO backpropagation works."""
logits_exist = torch.nn.Parameter(torch.zeros((2, 2)), requires_grad=True)
logits_orient = torch.nn.Parameter(torch.tensor([1.0]), requires_grad=True)
logits_exist_np = np.array(logits_exist.detach().numpy())
logits_orient_np = np.array(logits_orient.detach().numpy())
optim = torch.optim.SGD((logits_orient, logits_exist), lr=1e-2, momentum=0.9)
dist = ENCOAdjacencyDistribution(logits_exist=logits_exist, logits_orient=logits_orient)
# maximise the entropy
loss = -dist.entropy()
loss_init = loss.detach().numpy()
loss.backward()
optim.step()
loss = -dist.entropy()
# entropy should increase
assert (loss.detach().numpy() < loss_init).all()
logits_exist_after = logits_exist.detach().numpy()
# diagonal elements should remain the same
np.testing.assert_allclose(np.diagonal(logits_exist_after), np.diagonal(logits_exist_np))
# other edges should be more like to exist (their existence logits increase)
assert logits_exist_after[1, 0] > logits_exist_np[1, 0]
assert logits_exist_after[0, 1] > logits_exist_np[0, 1]
# the orientation logit should be heading towards 0 so it should decrease from 1
assert (logits_orient_np > logits_orient.detach().numpy()).all()
optim.zero_grad()
# test we can backpropagate through relaxed_sample
sample = dist.relaxed_sample(sample_shape=(100,), temperature=0.1)
loss = torch.sum((torch.eye(2)[None, ...] - sample) ** 2)
loss.backward()
# their should be gradients
assert abs(logits_exist.grad[0, 1]) > 1e-3
assert abs(logits_orient.grad[0]) > 1e-3
def test_enco():
"""Test ENCO methods are correct for a known distribution."""
probs_exist = torch.tensor([[0.0, 0.3], [0.8, 0.0]])
probs_orient = torch.tensor([0.7])
logits_exist = probs_to_logits(probs_exist, is_binary=True)
logits_orient = probs_to_logits(probs_orient, is_binary=True)
dist = ENCOAdjacencyDistribution(logits_exist=logits_exist, logits_orient=logits_orient)
np.testing.assert_allclose(torch.tensor([[0.0, 0.09], [0.56, 0.0]]), dist.mean)
np.testing.assert_allclose(torch.tensor([[0.0, 0.0], [1.0, 0.0]]), dist.mode)
samples = torch.tensor([[[0.0, 1.0], [0.0, 0.0]], [[0.0, 0.0], [1.0, 0.0]], [[0.0, 0.0], [0.0, 0.0]]])
np.testing.assert_allclose(
dist.log_prob(samples), np.array([np.log(0.09 * 0.44), np.log(0.91 * 0.56), np.log(0.91 * 0.44)]), atol=1e-7
)
|
causica/test/distributions/adjacency/test_enco.py/0
|
{
"file_path": "causica/test/distributions/adjacency/test_enco.py",
"repo_id": "causica",
"token_count": 1507
}
| 730 |
import torch
from causica.distributions import JointNoiseModule, Noise, NoiseModule, UnivariateNormalNoiseModule
from causica.functional_relationships import LinearFunctionalRelationships, RFFFunctionalRelationships
from causica.sem.distribution_parameters_sem import DistributionParametersSEM
def create_lingauss_sem(
shapes: dict[str, torch.Size],
coef_matrix: torch.Tensor,
graph: torch.Tensor,
log_scale: float = 0.0,
) -> DistributionParametersSEM:
"""Creates a dummy SEM with linear functional relationships and Gaussian noise."""
independent_noise_modules = {
name: UnivariateNormalNoiseModule(shape[-1], init_log_scale=log_scale) for name, shape in shapes.items()
}
noise_dist = JointNoiseModule(independent_noise_modules)
func = LinearFunctionalRelationships(shapes, coef_matrix)
return DistributionParametersSEM(graph=graph, noise_dist=noise_dist, func=func)
def create_rffgauss_sem(
shapes: dict[str, torch.Size],
random_features: torch.Tensor,
coeff_matrix: torch.Tensor,
graph: torch.Tensor,
log_scale: float = 0.0,
) -> DistributionParametersSEM:
"""Creates a dummy SEM with RFF functional relationships and Gaussian noise."""
independent_noise_modules = {
name: UnivariateNormalNoiseModule(shape[-1], init_log_scale=log_scale) for name, shape in shapes.items()
}
noise_dist = JointNoiseModule(independent_noise_modules)
func = RFFFunctionalRelationships(shapes, random_features, coeff_matrix)
return DistributionParametersSEM(graph=graph, noise_dist=noise_dist, func=func)
|
causica/test/sem/__init__.py/0
|
{
"file_path": "causica/test/sem/__init__.py",
"repo_id": "causica",
"token_count": 528
}
| 731 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
###########################################################################################
# CUSTOMIZED ENCODING/DECODING KERNELS AS USED In THE PAPER: #
# Clifford Neural Layers for PDE Modeling #
###########################################################################################
from typing import Tuple, Union
import torch
import torch.nn as nn
from cliffordlayers.nn.functional.utils import _w_assert
def get_2d_scalar_vector_encoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Clifford kernel for 2d Clifford algebra encoding layers.
This specific 2d embedding layer assumes scalar and vector input fields.
I.e. each part of the input multivector field is present except the bivector part.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList]): Weight input of dimension `(4, d~input, d~output, ...)`.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
Tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d~output * 4, d~input * 3, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 2
w = _w_assert(w)
assert len(w) == 4
k0 = torch.cat([w[0], g[0] * w[1], g[1] * w[2]], dim=1)
k1 = torch.cat([w[1], w[0], -g[1] * w[3]], dim=1)
k2 = torch.cat([w[2], g[0] * w[3], w[0]], dim=1)
k3 = torch.cat([w[3], w[2], -w[1]], dim=1)
k = torch.cat([k0, k1, k2, k3], dim=0)
return 4, k
def get_2d_scalar_vector_decoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Clifford kernel for 2d Clifford algebra decoding layers.
This specific 2d decoding layer assumes scalar and vector output fields.
I.e. each part of the output multivector field is present except the bivector part.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList]): Weight input of dimension `(4, d~input, d~output, ...)`.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
Tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d~output * 3, d~input * 4, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 2
w = _w_assert(w)
assert len(w) == 4
k0 = torch.cat([w[0], g[0] * w[1], g[1] * w[2], -g[0] * g[1] * w[3]], dim=1)
k1 = torch.cat([w[1], w[0], -g[1] * w[3], g[1] * w[2]], dim=1)
k2 = torch.cat([w[2], g[0] * w[3], w[0], -g[0] * w[1]], dim=1)
k = torch.cat([k0, k1, k2], dim=0)
return 3, k
def get_2d_rotation_scalar_vector_encoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Rotational Clifford kernel for 2d Clifford algebra encoding layers.
This specific 2d embedding layer assumes scalar and vector input fields.
I.e. each part of the input multivector field is present except the bivector part.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList]): Weight input of dimension `(6, d~input, d~output, ...)`.
w[0], w[1], w[2], w[3] are the weight 2d Clifford weight tensors;
w[4] is the scaling tensor;
w[5] is the zero kernel tensor.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
Tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d_output * 4, d~input * 3, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 2
assert g[0] == -1 and g[1] == -1, "Wrong signature of Clifford algebra. Signature not suitable for rotation kernel."
w = _w_assert(w)
assert len(w) == 6
# Adding scalar output kernel.
k0 = torch.cat([w[0], -w[1], -w[2]], dim=1)
# Rotational kernel from here onwards.
s0 = w[0] * w[0]
s1 = w[1] * w[1]
s2 = w[2] * w[2]
s3 = w[3] * w[3]
norm = torch.sqrt(s0 + s1 + s2 + s3 + 0.0001)
w0_n = w[0] / norm
w1_n = w[1] / norm
w2_n = w[2] / norm
w3_n = w[3] / norm
norm_factor = 2.0
s1 = norm_factor * (w1_n * w1_n)
s2 = norm_factor * (w2_n * w2_n)
s3 = norm_factor * (w3_n * w3_n)
rot01 = norm_factor * w0_n * w1_n
rot02 = norm_factor * w0_n * w2_n
rot03 = norm_factor * w0_n * w3_n
rot12 = norm_factor * w1_n * w2_n
rot13 = norm_factor * w1_n * w3_n
rot23 = norm_factor * w2_n * w3_n
scale = w[4]
zero_kernel = w[5]
k1 = torch.cat(
[
zero_kernel,
scale * (1.0 - (s2 + s3)),
scale * (rot12 - rot03),
],
dim=1,
)
k2 = torch.cat(
[
zero_kernel,
scale * (rot12 + rot03),
scale * (1.0 - (s1 + s3)),
],
dim=1,
)
k3 = torch.cat(
[
zero_kernel,
scale * (rot13 - rot02),
scale * (rot23 + rot01),
],
dim=1,
)
k = torch.cat([k0, k1, k2, k3], dim=0)
return 4, k
def get_2d_rotation_scalar_vector_decoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Rotational Clifford kernel for 2d Clifford algebra decoding layers.
This specific 2d decoding layer assumes scalar and vector output fields.
I.e. each part of the output multivector field is present except the bivector part.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList]): Weight input of dimension `(6, d~input, d~output, ...)`.
w[0], w[1], w[2], w[3] are the weight 2d Clifford weight tensors;
w[4] is the scaling tensor;
w[5] is the zero kernel tensor.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
Tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d~output * 3, d~input * 4, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 2
assert g[0] == -1 and g[1] == -1, "Wrong signature of Clifford algebra. Signature not suitable for rotation kernel."
w = _w_assert(w)
assert len(w) == 6
# Adding scalar output kernel.
k0 = torch.cat([w[0], -w[1], -w[2], -w[3]], dim=1)
# Rotational kernel from here onwards.
s0 = w[0] * w[0]
s1 = w[1] * w[1]
s2 = w[2] * w[2]
s3 = w[3] * w[3]
norm = torch.sqrt(s0 + s1 + s2 + s3 + 0.0001)
w0_n = w[0] / norm
w1_n = w[1] / norm
w2_n = w[2] / norm
w3_n = w[3] / norm
norm_factor = 2.0
s1 = norm_factor * (w1_n * w1_n)
s2 = norm_factor * (w2_n * w2_n)
s3 = norm_factor * (w3_n * w3_n)
rot01 = norm_factor * w0_n * w1_n
rot02 = norm_factor * w0_n * w2_n
rot03 = norm_factor * w0_n * w3_n
rot12 = norm_factor * w1_n * w2_n
rot13 = norm_factor * w1_n * w3_n
rot23 = norm_factor * w2_n * w3_n
scale = w[4]
zero_kernel = w[5]
k1 = torch.cat(
[
zero_kernel,
scale * (1.0 - (s2 + s3)),
scale * (rot12 - rot03),
scale * (rot13 + rot02),
],
dim=1,
)
k2 = torch.cat(
[
zero_kernel,
scale * (rot12 + rot03),
scale * (1.0 - (s1 + s3)),
scale * (rot23 - rot01),
],
dim=1,
)
k = torch.cat([k0, k1, k2], dim=0)
return 3, k
def get_3d_maxwell_encoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Clifford kernel for 3d Clifford algebra encoding layers.
This specific 3d embedding layer assumes vector and bivector input fields.
I.e. each part of the input multivector field is present except the scalar and the bivector parts.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor): Weight input of dimension `(8, d~input, d~output, ...)`.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
Tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d~output * 8, d~input * 6, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 3
w = _w_assert(w)
k0 = torch.cat(
[
w[1] * g[0],
w[2] * g[1],
w[3] * g[2],
-w[4] * g[0] * g[1],
-w[5] * g[0] * g[2],
-w[6] * g[1] * g[2],
],
dim=1,
)
k1 = torch.cat(
[w[0], -w[4] * g[1], -w[5] * g[2], w[2] * g[1], w[3] * g[2], -w[7] * g[1] * g[2]],
dim=1,
)
k2 = torch.cat(
[w[4] * g[0], w[0], -w[6] * g[2], -w[1] * g[0], w[7] * g[0] * g[2], w[3] * g[2]],
dim=1,
)
k3 = torch.cat(
[w[5] * g[0], w[6] * g[1], w[0], -w[7] * g[0] * g[1], -w[1] * g[0], -w[2] * g[1]],
dim=1,
)
k4 = torch.cat([w[2], -w[1], g[2] * w[7], w[0], -w[6] * g[2], w[5] * g[2]], dim=1)
k5 = torch.cat([w[3], -w[7] * g[1], -w[1], w[6] * g[1], w[0], -w[4] * g[1]], dim=1)
k6 = torch.cat([w[7] * g[0], w[3], -w[2], -w[5] * g[0], w[4] * g[0], w[0]], dim=1)
k7 = torch.cat([w[6], -w[5], w[4], w[3], -w[2], w[1]], dim=1)
k = torch.cat([k0, k1, k2, k3, k4, k5, k6, k7], dim=0)
return 8, k
def get_3d_maxwell_decoding_kernel(
w: Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor
) -> Tuple[int, torch.Tensor]:
"""Clifford kernel for 3d Clifford algebra decoding layers.
This specific 3d embedding layer assumes vector and bivector input fields.
I.e. each part of the output multivector field is present except the scalar and the bivector parts.
Args:
w (Union[tuple, list, torch.Tensor, nn.Parameter, nn.ParameterList], g: torch.Tensor): Weight input of dimension `(8, d~input, d~output, ...)`.
g (torch.Tensor): Signature of Clifford algebra.
Returns:
tuple[int, torch.Tensor]: Number of blades, weight output of dimension `(d~output * 6, d~input * 8, ...)`.
"""
assert isinstance(g, torch.Tensor)
assert g.numel() == 3
w = _w_assert(w)
k1 = torch.cat(
[w[1], w[0], -w[4] * g[1], -w[5] * g[2], w[2] * g[1], w[3] * g[2], -w[7] * g[1] * g[2], -w[6] * g[2] * g[1]],
dim=1,
)
k2 = torch.cat(
[w[2], w[4] * g[0], w[0], -w[6] * g[2], -w[1] * g[0], w[7] * g[0] * g[2], w[3] * g[2], w[5] * g[2] * g[0]],
dim=1,
)
k3 = torch.cat(
[w[3], w[5] * g[0], w[6] * g[1], w[0], -w[7] * g[0] * g[1], -w[1] * g[0], -w[2] * g[1], -w[4] * g[0] * g[1]],
dim=1,
)
k4 = torch.cat([w[4], w[2], -w[1], g[2] * w[7], w[0], -w[6] * g[2], w[5] * g[2], w[3] * g[2]], dim=1)
k5 = torch.cat([w[5], w[3], -w[7] * g[1], -w[1], w[6] * g[1], w[0], -w[4] * g[1], -w[2] * g[1]], dim=1)
k6 = torch.cat([w[6], w[7] * g[0], w[3], -w[2], -w[5] * g[0], w[4] * g[0], w[0], w[1] * g[0]], dim=1)
k = torch.cat([k1, k2, k3, k4, k5, k6], dim=0)
return 6, k
|
cliffordlayers/cliffordlayers/models/basic/custom_kernels.py/0
|
{
"file_path": "cliffordlayers/cliffordlayers/models/basic/custom_kernels.py",
"repo_id": "cliffordlayers",
"token_count": 5447
}
| 732 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import torch
from torch import nn
from typing import Union
from ...cliffordkernels import get_2d_clifford_kernel, get_3d_clifford_kernel
from ...signature import CliffordSignature
from ..functional.utils import batchmul2d, batchmul3d
class CliffordSpectralConv2d(nn.Module):
"""2d Clifford Fourier layer.
Performs following three steps:
1. Clifford Fourier transform over the multivector of 2d Clifford algebras, based on complex Fourier transforms using [pytorch.fft.fft2](https://pytorch.org/docs/stable/generated/torch.fft.fft2.html#torch.fft.fft2).
2. Weight multiplication in the Clifford Fourier space using the geometric product.
3. Inverse Clifford Fourier transform, based on inverse complex Fourier transforms using [pytorch.fft.ifft2](https://pytorch.org/docs/stable/generated/torch.fft.ifft2.html#torch.fft.ifft2).
Args:
g ((Union[tuple, list, torch.Tensor]): Signature of Clifford algebra.
in_channels (int): Number of input channels.
out_channels (int): Number of output channels.
modes1 (int): Number of non-zero Fourier modes in the first dimension.
modes2 (int): Number of non-zero Fourier modes in the second dimension.
multiply (bool): Multipliation in the Fourier space. If set to False this class only crops high-frequency modes.
"""
def __init__(
self,
g: Union[tuple, list, torch.Tensor],
in_channels: int,
out_channels: int,
modes1: int,
modes2: int,
multiply: bool = True,
) -> None:
super().__init__()
sig = CliffordSignature(g)
# To allow move to same device as module.
self.register_buffer("g", sig.g)
self.dim = sig.dim
if self.dim != 2:
raise ValueError("g must be a 2D Clifford algebra")
self.n_blades = sig.n_blades
self.in_channels = in_channels
self.out_channels = out_channels
self.modes1 = modes1
self.modes2 = modes2
self.multiply = multiply
# Initialize weight parameters.
if multiply:
scale = 1 / (in_channels * out_channels)
self.weights = nn.Parameter(
scale * torch.rand(4, out_channels, in_channels, self.modes1 * 2, self.modes2 * 2, dtype=torch.float32)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
# Reshape x such that FFT can be applied to dual pairs.
B, _, *D, I = x.shape
*_, I = x.shape
if not (I == self.n_blades):
raise ValueError(f"Input has {I} blades, but Clifford layer expects {self.n_blades}.")
dual_1 = torch.view_as_complex(torch.stack((x[..., 0], x[..., 3]), dim=-1))
dual_2 = torch.view_as_complex(torch.stack((x[..., 1], x[..., 2]), dim=-1))
dual_1_ft = torch.fft.fft2(dual_1)
dual_2_ft = torch.fft.fft2(dual_2)
# Add dual pairs again to multivector in the Fourier space.
multivector_ft = torch.cat(
(
dual_1_ft.real,
dual_2_ft.real,
dual_2_ft.imag,
dual_1_ft.imag,
),
dim=1,
)
# Reserve Cifford output Fourier modes.
out_ft = torch.zeros(
B,
self.out_channels * self.n_blades,
*D,
dtype=torch.float,
device=multivector_ft.device,
)
# Concatenate positive and negative modes, such that the geometric product can be applied in one go.
input_mul = torch.cat(
(
torch.cat(
(
multivector_ft[:, :, : self.modes1, : self.modes2],
multivector_ft[:, :, : self.modes1, -self.modes2 :],
),
-1,
),
torch.cat(
(
multivector_ft[:, :, -self.modes1 :, : self.modes2],
multivector_ft[:, :, -self.modes1 :, -self.modes2 :],
),
-1,
),
),
-2,
)
# Get Clifford weight tensor and apply the geometric product in the Fourier space.
if self.multiply:
_, kernel = get_2d_clifford_kernel(self.weights, self.g)
output_mul = batchmul2d(input_mul, kernel)
else:
output_mul = input_mul
# Fill the output modes, i.e. cut away high-frequency modes.
out_ft[:, :, : self.modes1, : self.modes2] = output_mul[:, :, : self.modes1, : self.modes2]
out_ft[:, :, -self.modes1 :, : self.modes2] = output_mul[:, :, -self.modes1 :, : self.modes2]
out_ft[:, :, : self.modes1, -self.modes2 :] = output_mul[:, :, : self.modes1, -self.modes2 :]
out_ft[:, :, -self.modes1 :, -self.modes2 :] = output_mul[:, :, -self.modes1 :, -self.modes2 :]
# Reshape output such that inverse FFTs can be applied to the dual pairs.
out_ft = out_ft.reshape(B, I, -1, *out_ft.shape[-2:])
B_dim, I_dim, C_dim, *D_dims = range(len(out_ft.shape))
out_ft = out_ft.permute(B_dim, C_dim, *D_dims, I_dim)
out_dual_1 = torch.view_as_complex(torch.stack((out_ft[..., 0], out_ft[..., 3]), dim=-1))
out_dual_2 = torch.view_as_complex(torch.stack((out_ft[..., 1], out_ft[..., 2]), dim=-1))
dual_1_ifft = torch.fft.ifft2(out_dual_1, s=(out_dual_1.size(-2), out_dual_1.size(-1)))
dual_2_ifft = torch.fft.ifft2(out_dual_2, s=(out_dual_2.size(-2), out_dual_2.size(-1)))
# Finally, return to the multivector in the spatial domain.
output = torch.stack(
(
dual_1_ifft.real,
dual_2_ifft.real,
dual_2_ifft.imag,
dual_1_ifft.imag,
),
dim=-1,
)
return output
class CliffordSpectralConv3d(nn.Module):
"""3d Clifford Fourier layer.
Performs following three steps:
1. Clifford Fourier transform over the multivector of 3d Clifford algebras, based on complex Fourier transforms using [pytorch.fft.fftn](https://pytorch.org/docs/stable/generated/torch.fft.fftn.html#torch.fft.fftn).
2. Weight multiplication in the Clifford Fourier space using the geometric product.
3. Inverse Clifford Fourier transform, based on inverse complex Fourier transforms using [pytorch.fft.ifftn](https://pytorch.org/docs/stable/generated/torch.fft.fftn.html#torch.fft.ifftn).
Args:
g ((Union[tuple, list, torch.Tensor]): Signature of Clifford algebra.
in_channels (int): Number of input channels.
out_channels (int): Number of output channels.
modes1 (int): Number of non-zero Fourier modes in the first dimension.
modes2 (int): Number of non-zero Fourier modes in the second dimension.
modes3 (int): Number of non-zero Fourier modes in the second dimension.
multiply (bool): Multipliation in the Fourier space. If set to False this class only crops high-frequency modes.
"""
def __init__(
self,
g: Union[tuple, list, torch.Tensor],
in_channels: int,
out_channels: int,
modes1: int,
modes2: int,
modes3: int,
multiply: bool = True,
) -> None:
super().__init__()
sig = CliffordSignature(g)
self.g = sig.g
self.dim = sig.dim
if self.dim != 3:
raise ValueError("g must be a 3D Clifford algebra")
self.n_blades = sig.n_blades
self.in_channels = in_channels
self.out_channels = out_channels
self.modes1 = modes1
self.modes2 = modes2
self.modes3 = modes3
self.multiply = multiply
# Initialize weight parameters.
if self.multiply:
scale = 1 / (in_channels * out_channels)
self.weights = nn.Parameter(
scale
* torch.rand(
8,
out_channels,
in_channels,
self.modes1 * 2,
self.modes2 * 2,
self.modes3 * 2,
dtype=torch.float32,
)
)
def forward(self, x: torch.Tensor) -> torch.Tensor:
# Reshape x such that FFT can be applied to dual pairs.
B, _, *D, I = x.shape
*_, I = x.shape
if not (I == self.n_blades):
raise ValueError(f"Input has {I} blades, but Clifford layer expects {self.n_blades}.")
dual_1 = torch.view_as_complex(torch.stack((x[..., 0], x[..., 7]), dim=-1))
dual_2 = torch.view_as_complex(torch.stack((x[..., 1], x[..., 6]), dim=-1))
dual_3 = torch.view_as_complex(torch.stack((x[..., 2], x[..., 5]), dim=-1))
dual_4 = torch.view_as_complex(torch.stack((x[..., 3], x[..., 4]), dim=-1))
dual_1_ft = torch.fft.fftn(dual_1, dim=[-3, -2, -1])
dual_2_ft = torch.fft.fftn(dual_2, dim=[-3, -2, -1])
dual_3_ft = torch.fft.fftn(dual_3, dim=[-3, -2, -1])
dual_4_ft = torch.fft.fftn(dual_4, dim=[-3, -2, -1])
# Add dual pairs again to multivector in the Fourier space.
multivector_ft = torch.cat(
(
dual_1_ft.real,
dual_2_ft.real,
dual_3_ft.real,
dual_4_ft.real,
dual_4_ft.imag,
dual_3_ft.imag,
dual_2_ft.imag,
dual_1_ft.imag,
),
dim=1,
)
# Reserve Cifford output Fourier modes.
out_ft = torch.zeros(
B,
self.out_channels * self.n_blades,
*D,
dtype=torch.float,
device=multivector_ft.device,
)
# Concatenate positive and negative modes, such that the geometric product can be applied in one go.
input_mul = torch.cat(
(
torch.cat(
(
torch.cat(
(
multivector_ft[:, :, : self.modes1, : self.modes2, : self.modes3],
multivector_ft[:, :, : self.modes1, : self.modes2, -self.modes3 :],
),
-1,
),
torch.cat(
(
multivector_ft[:, :, : self.modes1, -self.modes2 :, : self.modes3],
multivector_ft[:, :, : self.modes1, -self.modes2 :, -self.modes3 :],
),
-1,
),
),
-2,
),
torch.cat(
(
torch.cat(
(
multivector_ft[:, :, -self.modes1 :, : self.modes2, : self.modes3],
multivector_ft[:, :, -self.modes1 :, : self.modes2, -self.modes3 :],
),
-1,
),
torch.cat(
(
multivector_ft[:, :, -self.modes1 :, -self.modes2 :, : self.modes3],
multivector_ft[:, :, -self.modes1 :, -self.modes2 :, -self.modes3 :],
),
-1,
),
),
-2,
),
),
-3,
)
# Get Clifford weight tensor and apply the geometric product in the Fourier space.
if self.multiply:
_, kernel = get_3d_clifford_kernel(self.weights, self.g)
output_mul = batchmul3d(input_mul, kernel)
else:
output_mul = input_mul
# Fill the output modes, i.e. cut away high-frequency modes.
out_ft[:, :, : self.modes1, : self.modes2, : self.modes3] = output_mul[
:, :, : self.modes1, : self.modes2, : self.modes3
]
out_ft[:, :, : self.modes1, : self.modes2, -self.modes3 :] = output_mul[
:, :, : self.modes1, : self.modes2, -self.modes3 :
]
out_ft[:, :, : self.modes1, -self.modes2 :, : self.modes3] = output_mul[
:, :, : self.modes1, -self.modes2 :, : self.modes3
]
out_ft[:, :, : self.modes1, -self.modes2 :, -self.modes3 :] = output_mul[
:, :, : self.modes1, -self.modes2 :, -self.modes3 :
]
out_ft[:, :, -self.modes1 :, : self.modes2, : self.modes3] = output_mul[
:, :, -self.modes1 :, : self.modes2, : self.modes3
]
out_ft[:, :, -self.modes1 :, : self.modes2, -self.modes3 :] = output_mul[
:, :, : -self.modes1 :, : self.modes2, -self.modes3 :
]
out_ft[:, :, -self.modes1 :, -self.modes2 :, : self.modes3] = output_mul[
:, :, -self.modes1 :, -self.modes2 :, : self.modes3
]
out_ft[:, :, -self.modes1 :, -self.modes2 :, -self.modes3 :] = output_mul[
:, :, -self.modes1 :, -self.modes2 :, -self.modes3 :
]
# Reshape output such that inverse FFTs can be applied to the dual pairs.
out_ft = out_ft.reshape(B, I, -1, *out_ft.shape[-3:])
B_dim, I_dim, C_dim, *D_dims = range(len(out_ft.shape))
out_ft = out_ft.permute(B_dim, C_dim, *D_dims, I_dim)
out_dual_1 = torch.view_as_complex(torch.stack((out_ft[..., 0], out_ft[..., 7]), dim=-1))
out_dual_2 = torch.view_as_complex(torch.stack((out_ft[..., 1], out_ft[..., 6]), dim=-1))
out_dual_3 = torch.view_as_complex(torch.stack((out_ft[..., 2], out_ft[..., 5]), dim=-1))
out_dual_4 = torch.view_as_complex(torch.stack((out_ft[..., 3], out_ft[..., 4]), dim=-1))
dual_1_ifft = torch.fft.ifftn(out_dual_1, s=(out_dual_1.size(-3), out_dual_1.size(-2), out_dual_1.size(-1)))
dual_2_ifft = torch.fft.ifftn(out_dual_2, s=(out_dual_2.size(-3), out_dual_2.size(-2), out_dual_2.size(-1)))
dual_3_ifft = torch.fft.ifftn(out_dual_3, s=(out_dual_3.size(-3), out_dual_3.size(-2), out_dual_3.size(-1)))
dual_4_ifft = torch.fft.ifftn(out_dual_4, s=(out_dual_4.size(-3), out_dual_4.size(-2), out_dual_4.size(-1)))
# Finally, return to the multivector in the spatial domain.
output = torch.stack(
(
dual_1_ifft.real,
dual_2_ifft.real,
dual_3_ifft.real,
dual_4_ifft.real,
dual_4_ifft.imag,
dual_3_ifft.imag,
dual_2_ifft.imag,
dual_1_ifft.imag,
),
dim=-1,
)
return output
|
cliffordlayers/cliffordlayers/nn/modules/cliffordfourier.py/0
|
{
"file_path": "cliffordlayers/cliffordlayers/nn/modules/cliffordfourier.py",
"repo_id": "cliffordlayers",
"token_count": 8100
}
| 733 |
window.MathJax = {
tex: {
inlineMath: [["\\(", "\\)"]],
displayMath: [["\\[", "\\]"]],
processEscapes: true,
processEnvironments: true
},
options: {
ignoreHtmlClass: ".*|",
processHtmlClass: "arithmatex"
}
};
document$.subscribe(() => {
MathJax.typesetPromise()
})
|
cliffordlayers/docs/javascripts/mathjax.js/0
|
{
"file_path": "cliffordlayers/docs/javascripts/mathjax.js",
"repo_id": "cliffordlayers",
"token_count": 152
}
| 734 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import torch
import torch.nn.functional as F
from cliffordlayers.nn.modules.cliffordconv import (
CliffordConv1d,
CliffordConv2d,
CliffordConv3d,
)
def count_params(model):
return sum(p.numel() for p in model.parameters() if p.requires_grad)
def test_complex_convolution():
"""Test Clifford1d convolution module against complex convolution module using g = [-1]."""
in_channels = 8
out_channels = 16
x = torch.randn(1, in_channels, 128, 2)
clifford_conv = CliffordConv1d(g=[-1], in_channels=in_channels, out_channels=out_channels, kernel_size=3)
output_clifford_conv = clifford_conv(x)
w_c = torch.view_as_complex(torch.stack((clifford_conv.weight[0], clifford_conv.weight[1]), -1))
b_c = torch.view_as_complex(clifford_conv.bias.permute(1, 0).contiguous())
input_c = torch.view_as_complex(x)
output_c = F.conv1d(input_c, w_c, b_c)
torch.testing.assert_close(output_clifford_conv, torch.view_as_real(output_c))
def test_Clifford1d_conv_shapes():
"""Test shapes of Clifford1d convolution module."""
in_channels = 8
x = torch.randn(1, 8, 128, 2)
clifford_conv = CliffordConv1d(g=[1], in_channels=in_channels, out_channels=in_channels, kernel_size=3, padding=1)
x_out = clifford_conv(x)
assert x.shape == x_out.shape
def test_Clifford2d_conv_shapes():
"""Test shapes of Clifford2d convolution module."""
in_channels = 8
x = torch.randn(1, 8, 128, 128, 4)
clifford_conv = CliffordConv2d(
g=[1, 1], in_channels=in_channels, out_channels=in_channels, kernel_size=3, padding=1
)
x_out = clifford_conv(x)
clifford_conv_rotation = CliffordConv2d(
g=[-1, -1], in_channels=8, out_channels=8, kernel_size=3, padding=1, rotation=True
)
x_out_rot = clifford_conv_rotation(x)
assert x.shape == x_out.shape
assert x.shape == x_out_rot.shape
def test_Clifford2d_conv_params():
"""Test parameters of Clifford2d convolution using g = [-1, -1] vs Clifford2d rotational convolution.
When bias is set to False the ration needs to be 4/5.
"""
in_channels = 8
out_channels = 16
torch.randn(1, in_channels, 128, 128, 4)
clifford_conv = CliffordConv2d(
g=[-1, -1], in_channels=in_channels, out_channels=out_channels, kernel_size=3, padding=1, bias=False
)
clifford_conv_rotation = CliffordConv2d(
g=[-1, -1],
in_channels=in_channels,
out_channels=out_channels,
kernel_size=3,
padding=1,
bias=False,
rotation=True,
)
torch.testing.assert_close(float(count_params(clifford_conv) / count_params(clifford_conv_rotation)), 0.8)
def test_Clifford3d_conv_shapes():
"""Test shapes of Clifford2d convolution module."""
in_channels = 8
x = torch.randn(1, in_channels, 32, 32, 32, 8)
clifford_conv = CliffordConv3d(
g=[1, 1, 1], in_channels=in_channels, out_channels=in_channels, kernel_size=3, padding=1
)
x_out = clifford_conv(x)
assert x.shape == x_out.shape
|
cliffordlayers/tests/test_clifford_convolution.py/0
|
{
"file_path": "cliffordlayers/tests/test_clifford_convolution.py",
"repo_id": "cliffordlayers",
"token_count": 1316
}
| 735 |
pragma solidity ^0.6;
/**
* @title Math
* @dev Custom math operations.
*/
library Math {
/**
* @return The square root of `x` using the Babylonian method.
*/
// Copied from https://github.com/ethereum/dapp-bin/pull/50 and modified slightly.
function sqrt(uint x) internal pure returns (uint) {
if (x == 0) return 0;
else if (x <= 3) return 1;
uint z = (x + 1) / 2;
uint y = x;
while (z < y)
{
y = z;
z = (x / z + z) / 2;
}
return y;
}
}
|
0xDeCA10B/demo/client/lib/Math.sol/0
|
{
"file_path": "0xDeCA10B/demo/client/lib/Math.sol",
"repo_id": "0xDeCA10B",
"token_count": 270
}
| 0 |
import AppBar from '@material-ui/core/AppBar'
import Button from '@material-ui/core/Button'
import Drawer from '@material-ui/core/Drawer'
import Hidden from '@material-ui/core/Hidden'
import IconButton from '@material-ui/core/IconButton'
import List from '@material-ui/core/List'
import ListItem from '@material-ui/core/ListItem'
import ListItemIcon from '@material-ui/core/ListItemIcon'
import ListItemText from '@material-ui/core/ListItemText'
import { withStyles } from '@material-ui/core/styles'
import Toolbar from '@material-ui/core/Toolbar'
import Typography from '@material-ui/core/Typography'
import AddIcon from '@material-ui/icons/Add'
import HomeIcon from '@material-ui/icons/Home'
import InfoIcon from '@material-ui/icons/Info'
import MenuIcon from '@material-ui/icons/Menu'
import clsx from 'clsx'
import PropTypes from 'prop-types'
import React from 'react'
import { Link } from 'react-router-dom'
import logoImg from '../images/logo_transparent_100x73.png'
const drawerWidth = 220
const styles = theme => ({
root: {
flexGrow: 1,
},
flex: {
flex: 1,
},
menuButton: {
marginLeft: -12,
marginRight: 20,
},
navButton: {
textDecoration: 'none',
},
logoContainer: {
marginTop: 10,
},
logo: {
width: 85,
},
drawer: {
width: drawerWidth,
flexShrink: 0,
},
drawerPaper: {
width: drawerWidth,
},
drawerHeader: {
display: 'flex',
alignItems: 'center',
padding: theme.spacing(0, 1),
...theme.mixins.toolbar,
// To keep the icon on the right/end:
// justifyContent: 'flex-end',
},
hide: {
display: 'none',
},
})
class CustomAppBar extends React.Component {
constructor(props) {
super(props)
this.state = {
isDrawerOpen: false,
}
this.handleDrawerOpen = this.handleDrawerOpen.bind(this)
this.handleDrawerClose = this.handleDrawerClose.bind(this)
}
handleDrawerOpen() {
this.setState({ isDrawerOpen: true })
}
handleDrawerClose() {
this.setState({ isDrawerOpen: false })
}
render() {
const { classes } = this.props
return (
<div className={classes.root}>
<AppBar position="static" color="default">
<Toolbar>
<Hidden smUp>
<IconButton
color="inherit"
title="Open drawer"
aria-label="Open drawer"
onClick={this.handleDrawerOpen}
edge="start"
className={clsx(classes.menuButton, this.state.isDrawerOpen && classes.hide)}
>
<MenuIcon />
</IconButton>
</Hidden>
<div className={classes.logoContainer}>
<Link to='/'>
<img className={classes.logo} id="logo" alt="Logo" src={logoImg} />
</Link>
</div>
{/* A title can go here. Removing it breaks right aligning the links.
There's probably a better way to set up the aligning but I didn't want to bother because it was tricky and we might add a title back. */}
<Typography variant="h6" color="inherit" className={classes.flex}></Typography>
<Hidden xsDown>
<Link className={classes.navButton} title="Add a new model" to='/add'>
<Button>
<AddIcon /> Add model
</Button>
</Link>
<Link className={classes.navButton} title="About this site" to='/about'>
<Button>
<InfoIcon /> ABOUT
</Button>
</Link>
<Link className={classes.navButton} title="Go to the home page" to='/'>
<Button>
<HomeIcon /> Home
</Button>
</Link>
</Hidden>
</Toolbar>
</AppBar>
<Drawer
className={classes.drawer}
variant="persistent"
anchor="left"
open={this.state.isDrawerOpen}
classes={{
paper: classes.drawerPaper,
}}
>
<div className={classes.drawerHeader}>
<IconButton onClick={this.handleDrawerClose}>
<MenuIcon />
</IconButton>
</div>
<List>
<ListItem button component={Link} to='/' onClick={this.handleDrawerClose}>
<ListItemIcon><HomeIcon /></ListItemIcon>
<ListItemText primary="HOME" />
</ListItem>
<ListItem button component={Link} to='/about' onClick={this.handleDrawerClose}>
<ListItemIcon><InfoIcon /></ListItemIcon>
<ListItemText primary="ABOUT" />
</ListItem>
<ListItem button component={Link} to='/add' onClick={this.handleDrawerClose}>
<ListItemIcon><AddIcon /></ListItemIcon>
<ListItemText primary="ADD A MODEL" />
</ListItem>
</List>
</Drawer>
</div>
)
}
}
CustomAppBar.propTypes = {
classes: PropTypes.object.isRequired,
}
export default withStyles(styles)(CustomAppBar)
|
0xDeCA10B/demo/client/src/components/appBar.js/0
|
{
"file_path": "0xDeCA10B/demo/client/src/components/appBar.js",
"repo_id": "0xDeCA10B",
"token_count": 1949
}
| 1 |
import Web3 from 'web3'
import { Contract } from 'web3-eth-contract'
import Classifier from './compiled/Classifier64.json'
import CollaborativeTrainer64 from './compiled/CollaborativeTrainer64.json'
import DataHandler from './compiled/DataHandler64.json'
import IncentiveMechanism from './compiled/IncentiveMechanism64.json'
/**
* An already deployed instance of a CollaborativeTrainer contract.
*/
export class CollaborativeTrainer {
constructor(
public mainEntryPoint: Contract,
public classifier: Contract,
public dataHandler: Contract,
public incentiveMechanism: Contract,
) {
}
/**
* @returns The name of the model.
*/
name(): Promise<string> {
return this.mainEntryPoint.methods.name().call()
}
/**
* @returns A description of the model.
*/
description(): Promise<string> {
return this.mainEntryPoint.methods.description().call()
}
/**
* @returns The name of the encoder used by the model.
*/
encoder(): Promise<string> {
return this.mainEntryPoint.methods.encoder().call()
}
/**
* @param data Encoded data.
* Already transformed data by operations such as encoding, normalization, and `web3.utils.toHex`.
* @returns The model's prediction for `data`.
*/
predictEncoded(data: Array<string>): Promise<number> {
return this.classifier.methods.predict(data).call().then(parseInt)
}
}
/**
* Help validate if a contract can be used with the system.
*/
export class ContractLoader {
web3: Web3
constructor(web3: Web3) {
this.web3 = web3
}
getContractInstance(options: { abi: any, address: string }): Contract {
return new this.web3.eth.Contract(options.abi, options.address)
}
/**
* Loads and validates the contracts.
* @param address The address of the main entry point contract.
* @returns An interface to help you use the contracts.
*/
async load(address: string): Promise<CollaborativeTrainer> {
if (!address || address.length === 0) {
return Promise.reject("A blank address was given")
}
const mainEntryPoint = this.getContractInstance({
abi: CollaborativeTrainer64.abi,
address,
})
return Promise.all([
mainEntryPoint.methods.classifier().call().then((classifierAddress: string) => {
return this.getContractInstance({
abi: Classifier.abi,
address: classifierAddress
})
}),
mainEntryPoint.methods.dataHandler().call().then((dataHandlerAddress: string) => {
return this.getContractInstance({
abi: DataHandler.abi,
address: dataHandlerAddress
})
}),
mainEntryPoint.methods.incentiveMechanism().call().then((incentiveMechanismAddress: string) => {
return this.getContractInstance({
abi: IncentiveMechanism.abi,
address: incentiveMechanismAddress
})
})
]).then(async ([
classifier,
dataHandler,
incentiveMechanism,
]) => {
const [classifierOwner, dataHandlerOwner, incentiveMechanismOwner] = await Promise.all([
classifier.methods.owner().call(),
dataHandler.methods.owner().call(),
incentiveMechanism.methods.owner().call(),
])
if (classifierOwner !== address || dataHandlerOwner !== address || incentiveMechanismOwner !== address) {
throw new Error(`The classifer, data handler, and incentive mechanism must be owned by the main interface.\n Main interface address: ${address}\n Classifier owner: ${classifierOwner}\n Data handler owner: ${dataHandlerOwner}\n IM owner: ${incentiveMechanismOwner}.`)
}
return new CollaborativeTrainer(mainEntryPoint,
classifier, dataHandler, incentiveMechanism)
})
}
}
|
0xDeCA10B/demo/client/src/contracts/loader.ts/0
|
{
"file_path": "0xDeCA10B/demo/client/src/contracts/loader.ts",
"repo_id": "0xDeCA10B",
"token_count": 1168
}
| 2 |
import assert from 'assert'
import { DataStoreHealthStatus, ModelInformation, OriginalData } from '../data-store'
import { DataStoreFactory } from '../data-store-factory'
describe("LocalDataStore", () => {
const db = new DataStoreFactory().create('local')
it("should be healthy", async () => {
const status = await db.health()
assert.deepStrictEqual(status, new DataStoreHealthStatus(true))
})
it("should find models", async () => {
const modelInfo = new ModelInformation({
name: 'name', address: 'address',
description: 'description', modelType: 'modelType', encoder: 'encoder'
})
db.saveModelInformation(modelInfo)
const response = await db.getModels(undefined, 1)
const { models, remaining } = response
assert.deepStrictEqual(models, [modelInfo])
assert(remaining === 0)
const model = await db.getModel(modelInfo.id, modelInfo.address)
assert.deepStrictEqual(model, modelInfo)
await db.removeModel(modelInfo)
assert((await db.getModels()).models.length === 0)
})
it("should find original data", async () => {
const transactionHash = 'txHash'
const originalData = new OriginalData('text')
db.saveOriginalData(transactionHash, originalData)
const found = await db.getOriginalData(transactionHash)
assert.deepStrictEqual(found, originalData)
})
})
|
0xDeCA10B/demo/client/src/storage/__tests__/local-data-store.test.ts/0
|
{
"file_path": "0xDeCA10B/demo/client/src/storage/__tests__/local-data-store.test.ts",
"repo_id": "0xDeCA10B",
"token_count": 415
}
| 3 |
const Points64 = artifacts.require("./incentive/Points64")
contract('Points64', function (accounts) {
let im
function parseBN(num) {
if (web3.utils.isBN(num)) {
return num.toNumber()
} else {
assert.typeOf(num, 'number')
return num
}
}
before("deploy Points", async () => {
im = await Points64.new(0, 0, 0)
})
it("...should be free", async () => {
assert.equal(await im.getNextAddDataCost().then(parseBN), 0)
})
it("...should refund and report", async () => {
let totalGoodDataCount = await im.totalGoodDataCount.call().then(parseBN)
const data = []
const prediction = classification = 0
const claimableAmount = cost = await im.handleAddData.call(0, data, classification).then(parseBN)
assert.equal(cost, 0)
// Actually make the transaction.
await im.handleAddData(cost, data, classification)
const ownerAddress = accounts[0]
const otherAddress = accounts[1]
const addedTime = Math.floor(new Date().getTime() / 1000)
const claimedBySubmitter = false
const refundAmount = await im.handleRefund.call(otherAddress, data, classification,
addedTime, claimableAmount, claimedBySubmitter,
prediction, 0, { from: ownerAddress })
assert.equal(refundAmount, 0)
const numValidBefore = await im.numValidForAddress.call(ownerAddress).then(parseBN)
assert.equal(numValidBefore, 0)
let refundResponse = await im.handleRefund(ownerAddress, data, classification,
addedTime, claimableAmount, claimedBySubmitter,
prediction, 0, { from: ownerAddress })
let e = refundResponse.logs.filter(e => e.event == 'Refund')[0]
assert.equal(e.args.recipient, ownerAddress)
totalGoodDataCount += 1
assert.equal(await im.totalGoodDataCount.call().then(parseBN), totalGoodDataCount)
assert.equal(await im.numValidForAddress.call(ownerAddress).then(parseBN), numValidBefore + 1)
const rewardAmount = await im.handleReport.call(otherAddress,
data, classification,
addedTime, ownerAddress,
cost, cost, false,
// Prediction was the wrong classification.
classification + 1, 0).then(parseBN)
assert.equal(rewardAmount, 0)
let reportResponse = await im.handleReport(otherAddress,
data, classification,
addedTime, ownerAddress,
cost, cost, false,
// Prediction was the wrong classification.
classification + 1, 0)
e = reportResponse.logs.filter(e => e.event == 'Report')[0]
assert.equal(e.args.recipient, otherAddress)
})
it("...should not refund twice", async () => {
let totalGoodDataCount = await im.totalGoodDataCount.call().then(parseBN)
const claimableAmount = cost = 0
const data = [0]
const prediction = classification = 0
await im.handleAddData(cost, data, classification)
const ownerAddress = accounts[0]
const otherAddress = accounts[1]
const addedTime = Math.floor(new Date().getTime() / 1000)
const claimedBySubmitter = false
const numValidBefore = await im.numValidForAddress.call(ownerAddress).then(parseBN)
assert.equal(numValidBefore, 1)
const refundResponse = await im.handleRefund(ownerAddress, data, classification,
addedTime, claimableAmount, claimedBySubmitter,
prediction, 0, { from: ownerAddress })
let e = refundResponse.logs.filter(e => e.event == 'Refund')[0]
assert.equal(e.args.recipient, ownerAddress)
totalGoodDataCount += 1
assert.equal(await im.totalGoodDataCount.call().then(parseBN), totalGoodDataCount)
assert.equal(await im.numValidForAddress.call(ownerAddress).then(parseBN), numValidBefore + 1)
await im.handleRefund(otherAddress, data, classification,
addedTime, claimableAmount, claimedBySubmitter,
prediction, 1).then(_ => {
assert.fail("The second refund should have failed.")
}).catch(err => {
const msg = "Already claimed."
assert.equal(err.message, `Returned error: VM Exception while processing transaction: revert ${msg} -- Reason given: ${msg}.`)
})
})
it("...should not report twice", async () => {
const cost = 0
const data = [1]
const classification = 0
// Prediction was the wrong classification.
const prediction = 1
await im.handleAddData(cost, data, classification)
const ownerAddress = accounts[0]
const otherAddress = accounts[1]
const anotherAddress = accounts[2]
const addedTime = Math.floor(new Date().getTime() / 1000)
await im.handleReport(otherAddress,
data, classification,
addedTime, ownerAddress,
cost, cost, false,
prediction, 0)
await im.handleReport(anotherAddress,
data, classification,
addedTime, ownerAddress,
cost, cost, false,
prediction, 1).then(_ => {
assert.fail("The second report should have failed.")
}).catch(err => {
const msg = "Already claimed."
assert.equal(err.message, `Returned error: VM Exception while processing transaction: revert ${msg} -- Reason given: ${msg}.`)
})
})
})
|
0xDeCA10B/demo/client/test/contracts/incentive/points.js/0
|
{
"file_path": "0xDeCA10B/demo/client/test/contracts/incentive/points.js",
"repo_id": "0xDeCA10B",
"token_count": 1590
}
| 4 |
import json
import logging
import os
import time
from dataclasses import dataclass
from logging import Logger
from pathlib import Path
from typing import Any, Callable, List
import joblib
import numpy as np
import scipy.sparse
from injector import ClassAssistedBuilder, Module, inject, provider
from sklearn.linear_model import SGDClassifier
from sklearn.metrics import accuracy_score, classification_report, confusion_matrix
from sklearn.naive_bayes import MultinomialNB
from decai.simulation.contract.classification.classifier import Classifier
from decai.simulation.contract.classification.ncc import NearestCentroidClassifier
from decai.simulation.data.featuremapping.feature_index_mapper import FeatureIndexMapping
# Purposely not a singleton so that it is easy to get a model that has not been initialized.
@inject
@dataclass
class SciKitClassifier(Classifier):
"""
Classifier for a scikit-learn like model.
"""
_logger: Logger
_model_initializer: Callable[[], Any]
_model = None
def __post_init__(self):
self._original_model_path = Path('saved_models') / f'{time.time()}-{id(self)}.joblib'
def evaluate(self, data, labels) -> float:
assert self._model is not None, "The model has not been initialized yet."
assert isinstance(data, np.ndarray) or scipy.sparse.isspmatrix(data), \
f"The data must be a matrix. Got: {type(data)}"
assert isinstance(labels, np.ndarray), "The labels must be an array."
self._logger.debug("Evaluating.")
return self._model.score(data, labels)
def log_evaluation_details(self, data, labels, level=logging.INFO) -> float:
assert self._model is not None, "The model has not been initialized yet."
assert isinstance(data, np.ndarray), "The data must be an array."
assert isinstance(labels, np.ndarray), "The labels must be an array."
self._logger.debug("Evaluating.")
predicted_labels = self._model.predict(data)
result = accuracy_score(labels, predicted_labels)
if self._logger.isEnabledFor(level):
m = confusion_matrix(labels, predicted_labels)
report = classification_report(labels, predicted_labels)
self._logger.log(level,
"Confusion matrix:\n%s"
"\nReport:\n%s"
"\nAccuracy: %0.2f%%",
m, report, result * 100)
return result
def init_model(self, training_data, labels, save_model=False):
assert self._model is None, "The model has already been initialized."
self._logger.debug("Initializing model.")
self._model = self._model_initializer()
self._logger.debug("training_data.shape: %s. dtype: %s", training_data.shape, training_data.dtype)
self._model.fit(training_data, labels)
if save_model:
self._logger.debug("Saving model to \"%s\".", self._original_model_path)
os.makedirs(os.path.dirname(self._original_model_path), exist_ok=True)
joblib.dump(self._model, self._original_model_path)
def predict(self, data):
assert self._model is not None, "The model has not been initialized yet."
assert isinstance(data, np.ndarray), "The data must be an array."
return self._model.predict([data])[0]
def update(self, data, classification):
assert self._model is not None, "The model has not been initialized yet."
self._model.partial_fit([data], [classification])
def reset_model(self):
assert self._model is not None, "The model has not been initialized yet."
assert self._original_model_path.exists(), "The model has not been saved. Perhaps saving was disabled."
self._logger.debug("Loading model from \"%s\".", self._original_model_path)
self._model = joblib.load(self._original_model_path)
def export(self,
path: str,
classifications: List[str] = None,
model_type: str = None,
feature_index_mapping: FeatureIndexMapping = None):
assert self._model is not None, "The model has not been initialized yet."
if isinstance(self._model, SGDClassifier) and self._model.loss == 'perceptron':
if classifications is None:
classifications = ["0", "1"]
model = {
'type': model_type or 'sparse perceptron',
'classifications': classifications,
'weights': self._model.coef_[0].tolist(),
'intercept': self._model.intercept_[0],
}
if feature_index_mapping is not None:
if model_type is None:
model['type'] = 'sparse perceptron'
weights = model['weights']
del model['weights']
weights = {str(i): v for (i, v) in zip(feature_index_mapping, weights) if v != 0}
model['sparseWeights'] = weights
elif isinstance(self._model, MultinomialNB):
if classifications is None:
classifications = list(map(str, range(self._model.feature_count_.shape[1])))
feature_counts = []
for class_features in self._model.feature_count_:
class_feature_counts = []
for index, count in enumerate(class_features):
if count != 0:
# Counts should already be integers.
if feature_index_mapping is not None:
index = feature_index_mapping[index]
class_feature_counts.append((index, int(count)))
feature_counts.append(class_feature_counts)
model = {
'type': model_type or 'naive bayes',
'classifications': classifications,
'classCounts': self._model.class_count_.astype(dtype=np.int64).tolist(),
'featureCounts': feature_counts,
'totalNumFeatures': self._model.feature_count_.shape[1],
'smoothingFactor': self._model.alpha,
}
elif isinstance(self._model, NearestCentroidClassifier):
if feature_index_mapping is not None:
if model_type is None:
model_type = 'sparse nearest centroid classifier'
centroids = dict()
if classifications is None:
classifications = list(map(str, range(len(self.centroids_))))
for i, classification in enumerate(classifications):
centroid = self._model.centroids_[i].tolist()
if feature_index_mapping is not None:
centroid = {str(i): v for (i, v) in zip(feature_index_mapping, centroid) if v != 0}
centroids[classification] = dict(
centroid=centroid,
dataCount=self._model._num_samples_per_centroid[i])
model = {
'type': model_type or 'nearest centroid classifier',
'centroids': centroids,
}
else:
raise Exception("Unrecognized model type.")
with open(path, 'w') as f:
json.dump(model, f, separators=(',', ':'))
@dataclass
class SciKitClassifierModule(Module):
"""
Module to provide SciKit Learn Classifier like models.
"""
_model_initializer: Any
# Purposely not a singleton so that it is easy to get a model that has not been initialized.
@provider
def provide_classifier(self, builder: ClassAssistedBuilder[SciKitClassifier]) -> Classifier:
return builder.build(
_model_initializer=self._model_initializer,
)
|
0xDeCA10B/simulation/decai/simulation/contract/classification/scikit_classifier.py/0
|
{
"file_path": "0xDeCA10B/simulation/decai/simulation/contract/classification/scikit_classifier.py",
"repo_id": "0xDeCA10B",
"token_count": 3335
}
| 5 |
from abc import ABC, abstractmethod
from typing import List
class DataLoader(ABC):
"""
Base class for providing simulation data.
"""
@abstractmethod
def classifications(self) -> List[str]:
"""
:return: The classifications for this dataset.
"""
pass
@abstractmethod
def load_data(self, train_size: int = None, test_size: int = None) -> (tuple, tuple):
"""
:return: Training Data, Test Data: (x_train, y_train), (x_test, y_test)
"""
pass
|
0xDeCA10B/simulation/decai/simulation/data/data_loader.py/0
|
{
"file_path": "0xDeCA10B/simulation/decai/simulation/data/data_loader.py",
"repo_id": "0xDeCA10B",
"token_count": 215
}
| 6 |
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