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Add start of textmate language grammar.
Basic* grammar to start of with, this doesn't handle custom ops and doesn't handle ops with regions. But useful enough to make reading the .mlir files easier. Followed the approach used for emacs & vim and placed in separate directory under utils. * I got a little bit carried away trying to handle attributes and tried to do some custom op printing handling, but finally abandoned it. Also first time writing a textmate grammar so I assume a lot can be improved :) PiperOrigin-RevId: 262985490
This commit is contained in:
Jacques Pienaar
committed by
A. Unique TensorFlower
A. Unique TensorFlower
parent
e6365f3d02
commit
532c652d6c
387
mlir/utils/textmate/mlir.json
Normal file
387
mlir/utils/textmate/mlir.json
Normal file
@@ -0,0 +1,387 @@
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{
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"fileTypes" : [
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"mlir"
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],
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"repository" : {
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"container" : {
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"end" : ">",
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"begin" : "(complex|tuple)<",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.container.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#types"
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}
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],
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"name" : "meta.types.container.mlir"
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},
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"loc" : {
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"end" : "\\)",
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"begin" : "\\b(loc)\\(",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.loc.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#loc_fusedloc"
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},
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{
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"include" : "#loc_nameloc"
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},
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{
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"include" : "#op_generic"
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}
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],
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"name" : "meta.loc.mlir"
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},
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"integer" : {
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"match" : "[1-9][0-9]*",
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"name" : "constant.numeric.mlir"
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},
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"op" : {
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"patterns" : [
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{
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"include" : "#terminator"
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},
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{
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"include" : "#op_generic"
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}
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]
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},
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"loc_nameloc" : {
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"patterns" : [
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{
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"include" : "#string"
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}
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],
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"name" : "meta.location.mlir"
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},
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"bool_constant" : {
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"match" : "\\b(true|false)\\b",
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"captures" : {
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"1" : {
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"name" : "constant.language.mlir"
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}
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},
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"name" : "constant.language.mlir"
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},
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"string" : {
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"end" : "\"",
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"begin" : "\"",
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"beginCaptures" : {
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"0" : {
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"name" : "punctuation.definition.string.begin.mlir"
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}
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},
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"patterns" : [
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{
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"match" : "\\\\[nt\"]",
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"name" : "constant.character.escape.mlir"
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},
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{
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"match" : "\\\\.",
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"name" : "invalid.illegal.mlir"
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}
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],
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"endCaptures" : {
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"0" : {
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"name" : "punctuation.definition.string.end.mlir"
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}
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},
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"name" : "string.quoted.double.mlir"
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},
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"terminator" : {
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"end" : "\\n",
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"begin" : "(br|cond_br|return)",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.control.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#branch_target"
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},
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{
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"include" : "#identifier"
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},
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{
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"include" : "#types"
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},
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{
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"include" : "#loc"
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}
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]
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},
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"region" : {
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"end" : "(?=})",
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"begin" : "{",
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"patterns" : [
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{
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"include" : "#branch_target"
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},
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{
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"include" : "#op"
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},
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{
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"include" : "#attributes"
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},
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{
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"include" : "#comment"
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},
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{
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"include" : "#string"
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}
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],
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"name" : "meta.region.mlir"
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},
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"constant" : {
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"patterns" : [
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{
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"include" : "#bool_constant"
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},
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{
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"include" : "#integer"
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},
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{
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"include" : "#string"
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}
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],
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"name" : "constants.other.mlir"
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},
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"loc_fusedloc" : {
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"end" : "\\]",
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"begin" : "(fused)(<.*>)?\\[",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.loc.mlir"
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},
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"2" : {
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"patterns" : [
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{
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"include" : "#string"
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}
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]
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}
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},
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"patterns" : [
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{
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"include" : "#string"
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}
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],
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"name" : "meta.location.mlir"
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},
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"branch_target" : {
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"end" : "[:,\\n]",
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"begin" : "(\\^bb[\\w\\d_$\\.-]+)",
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"beginCaptures" : {
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"1" : {
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"name" : "entity.name.label.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#branch_target_region"
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},
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{
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"include" : "#comment"
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}
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],
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"name" : "meta.branch_target.mlir"
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},
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"types" : {
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"patterns" : [
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{
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"include" : "#container"
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},
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{
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"include" : "#shaped_container"
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},
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{
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"include" : "#standard_simple_types"
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}
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],
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"name" : "meta.types.mlir"
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},
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"attribute_keywords" : {
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"match" : "\\b(dense|none|opaque|sparse)\\b",
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"captures" : {
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"1" : {
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"name" : "keyword.attributes.mlir"
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}
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}
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},
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"identifier" : {
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"match" : "[\\%#][a-zA-Z0-9][\\w\\d_]*",
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"captures" : {
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"0" : {
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"name" : "variable.mlir"
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}
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},
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"name" : "meta.identifier.mlir"
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},
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"shaped_container" : {
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"end" : ">",
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"begin" : "(memref|tensor|vector)<",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.shaped_container.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#types"
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}
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],
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"name" : "meta.types.standard.shaped_container.mlir"
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},
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"standard_simple_types" : {
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"match" : "\\b(index|i[1-9]\\d*|f16|bf16|f32|f64)\\b",
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"captures" : {
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"1" : {
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"name" : "keyword.types.standard.simple.mlir"
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}
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},
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"name" : "meta.types.standard.simple.mlir"
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},
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"function_attributes" : {
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"end" : "}",
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"begin" : "(attributes)\\s*{",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.attributes.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#constant"
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}
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],
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"name" : "meta.attributes.function.mlir"
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},
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"op_generic" : {
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"end" : "\\n",
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"begin" : "((%[\\w\\d_]*)\\s*)=\\s*(?=\")",
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"beginCaptures" : {
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"2" : {
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"name" : "variable.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#attributes"
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},
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{
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"include" : "#identifier"
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},
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{
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"include" : "#loc"
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},
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{
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"include" : "#string"
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},
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{
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"include" : "#types"
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}
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],
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"name" : "meta.op.generic.mlir"
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},
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"function_results" : {
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"end" : "\\)",
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"begin" : "->\\s*\\(",
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"patterns" : [
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{
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"include" : "#types"
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}
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],
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"name" : "meta.function.results.mlir"
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},
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"branch_target_region" : {
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"end" : "\\)",
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"begin" : "\\(",
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"patterns" : [
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{
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"include" : "#identifier"
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},
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{
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"include" : "#types"
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}
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],
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"name" : "meta.branch_target.mlir"
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},
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"comment" : {
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"match" : "\/\/.*$",
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"name" : "comment.line.double-slash.mlir"
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},
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"attributes" : {
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"end" : "}",
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"begin" : "{",
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"patterns" : [
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{
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"include" : "#attribute_keywords"
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},
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{
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"include" : "#constant"
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}
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],
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"name" : "meta.attributes.mlir"
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},
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"function_params" : {
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"end" : ")",
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"begin" : "(",
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"patterns" : [
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{
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"include" : "#identifier"
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},
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{
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"include" : "#types"
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}
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]
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}
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},
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"scope" : "mlir",
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"patterns" : [
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{
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"match" : "\\b(module)\\b",
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"name" : "keyword.module.mlir"
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},
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{
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"end" : "}",
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"begin" : "\\b(func)\\b\\s*(@[a-zA-Z_][a-zA-Z_0-9\\.]*)",
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"beginCaptures" : {
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"1" : {
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"name" : "keyword.function.mlir"
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},
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"2" : {
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"name" : "entity.name.function.mlir"
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}
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},
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"patterns" : [
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{
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"include" : "#function_params"
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},
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{
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"include" : "#function_attributes"
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},
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{
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"include" : "#function_results"
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},
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{
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"include" : "#region"
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}
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],
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"name" : "support.function.mlir"
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},
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{
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"include" : "#comment",
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"name" : "comment.line.double-slash.mlir"
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}
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],
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"name" : "MLIR",
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"scopeName" : "source.mlir"
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}
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