added map,conv and permute
map - maps points based on equations conv - allows running convolution filter permute - switches dimension position
This commit is contained in:
mcDandy
@@ -104,13 +104,18 @@ class FloatEvalVisitor(MathExprVisitor):
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def visitAsinhFunc(self, ctx): return math.asinh(self.visit(ctx.expr()))
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def visitAcoshFunc(self, ctx): return math.acosh(self.visit(ctx.expr()))
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def visitAtanhFunc(self, ctx): return math.atanh(self.visit(ctx.expr()))
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def visitAbsFunc(self, ctx): return math.abs(self.visit(ctx.expr()))
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def visitAbsExp(self, ctx): return math.abs(self.visit(ctx.expr()))
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def visitAbsFunc(self, ctx): return abs(self.visit(ctx.expr()))
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def visitAbsExp(self, ctx): return abs(self.visit(ctx.expr()))
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def visitListExp(self, ctx): return self.visit(ctx.expr(0))
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def visitSqrtFunc(self, ctx): return math.sqrt(self.visit(ctx.expr()))
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def visitLnFunc(self, ctx): return math.log(self.visit(ctx.expr()))
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def visitLogFunc(self, ctx): return math.log10(self.visit(ctx.expr()))
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def visitExpFunc(self, ctx): return math.exp(self.visit(ctx.expr()))
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def visitNormFunc(self, ctx): return math.sqrt(math.avg(x**2 for x in self.visit(ctx.expr())))
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def visitNormFunc(self, ctx):
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vals = self.visit(ctx.expr())
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if isinstance(vals, (list, tuple)):
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return math.sqrt(sum(x**2 for x in vals) / len(vals))
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return abs(vals)
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def visitFloorFunc(self, ctx): return math.floor(self.visit(ctx.expr()))
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def visitFractFunc(self, ctx):
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val = self.visit(ctx.expr())
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@@ -131,7 +136,7 @@ class FloatEvalVisitor(MathExprVisitor):
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x = self.visit(ctx.expr())
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return math.copysign(1.0, x) if x != 0 else 0.0
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def visitCeilFunc(self, ctx): return math.ceil(self.visit(ctx.expr()))
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def visitRoundFunc(self, ctx): return math.round(self.visit(ctx.expr()))
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def visitRoundFunc(self, ctx): return round(self.visit(ctx.expr()))
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def visitGammaFunc(self, ctx): return math.gamma(self.visit(ctx.expr())).exp()
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def visitPrintFunc(self, ctx):
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val = self.visit(ctx.expr())
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@@ -151,10 +156,10 @@ class FloatEvalVisitor(MathExprVisitor):
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# N-argument functions
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def visitSMinFunc(self, ctx):
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args = [self.visit(e) for e in ctx.expr()]
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return math.min(args)
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return min(args)
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def visitSMaxFunc(self, ctx):
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args = [self.visit(e) for e in ctx.expr()]
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return math.max(args)
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return max(args)
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def visitClampFunc(self, ctx):
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x = self.visit(ctx.expr(0))
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@@ -188,6 +193,13 @@ class FloatEvalVisitor(MathExprVisitor):
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return self.visitChildren(ctx)
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def visitFunc4Exp(self, ctx):
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return self.visitChildren(ctx)
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def visitMapFunc(self, ctx):
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return self.visit(ctx.expr(0))
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def visitConvFunc(self, ctx):
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return self.visit(ctx.expr(0))
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def visitFuncNExp(self, ctx):
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return self.visitChildren(ctx)
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def visitAtomExp(self, ctx):
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@@ -51,6 +51,7 @@ atom
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| CONSTANT # ConstantExp
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| '(' expr ')' # ParenExp
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| PIPE expr PIPE # AbsExp
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| '[' expr (',' expr)* ']' # ListExp
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;
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// Single-argument functions
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@@ -88,7 +89,6 @@ func1
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| SOFTPLUS '(' expr ')' # SoftplusFunc
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| GELU '(' expr ')' # GeluFunc
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| SIGN '(' expr ')' # SignFunc
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;
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// Two-argument functions
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@@ -99,6 +99,7 @@ func2
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| TMAX '(' expr ',' expr ')' # TMaxFunc
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| STEP '(' expr ',' expr ')' # StepFunc
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;
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func3
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: CLAMP '(' expr ',' expr ',' expr ')' # ClampFunc
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| LERP '(' expr ',' expr ',' expr ')' # LerpFunc
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@@ -108,11 +109,14 @@ func3
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func4
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: SWAP '(' expr ',' expr ',' expr ',' expr ')' # SwapFunc
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;
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// N-argument functions (at least 2 arguments)
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funcN
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: SMIN '(' expr (',' expr)+ ')' # SMinFunc
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| SMAX '(' expr (',' expr)+ ')' # SMaxFunc
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// N-argument functions
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funcN
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: SMIN '(' expr (',' expr)* ')' # SMinFunc
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| SMAX '(' expr (',' expr)* ')' # SMaxFunc
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| MAP '(' expr (',' expr)+ ')' # MapFunc
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| CONV '(' expr (',' expr)+ ')' # ConvFunc
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| PERM '(' expr ',' expr ')' # PermuteFunc
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;
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// LEXER RULES
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@@ -160,7 +164,10 @@ RELU : 'relu';
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SOFTPLUS : 'softplus';
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GELU : 'gelu';
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SIGN : 'sign';
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MAP : 'map';
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CONV : 'conv';
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SWAP : 'swap';
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PERM : 'permute';
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PLUS : '+';
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MINUS : '-';
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File diff suppressed because one or more lines are too long
+129
-119
@@ -1,124 +1,134 @@
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T__0=1
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T__1=2
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T__2=3
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SIN=4
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COS=5
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TAN=6
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ASIN=7
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ACOS=8
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ATAN=9
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ATAN2=10
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SINH=11
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COSH=12
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TANH=13
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ASINH=14
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ACOSH=15
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ATANH=16
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ABS=17
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SQRT=18
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LN=19
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LOG=20
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EXP=21
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SMIN=22
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SMAX=23
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TMIN=24
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TMAX=25
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TNORM=26
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SNORM=27
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FLOOR=28
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CEIL=29
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ROUND=30
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GAMMA=31
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POWE=32
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SIGM=33
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CLAMP=34
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SFFT=35
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SIFFT=36
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ANGL=37
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PRNT=38
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LERP=39
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STEP=40
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SMOOTHSTEP=41
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FRACT=42
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RELU=43
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SOFTPLUS=44
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GELU=45
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SIGN=46
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SWAP=47
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PLUS=48
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MINUS=49
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MULT=50
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DIV=51
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MOD=52
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POW=53
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GE=54
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GT=55
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LE=56
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LT=57
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EQ=58
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NE=59
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PIPE=60
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CONSTANT=61
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NUMBER=62
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VARIABLE=63
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WS=64
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T__3=4
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T__4=5
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SIN=6
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COS=7
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TAN=8
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ASIN=9
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ACOS=10
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ATAN=11
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ATAN2=12
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SINH=13
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COSH=14
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TANH=15
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ASINH=16
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ACOSH=17
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ATANH=18
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ABS=19
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SQRT=20
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LN=21
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LOG=22
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EXP=23
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SMIN=24
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SMAX=25
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TMIN=26
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TMAX=27
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TNORM=28
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SNORM=29
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FLOOR=30
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CEIL=31
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ROUND=32
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GAMMA=33
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POWE=34
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SIGM=35
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CLAMP=36
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SFFT=37
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SIFFT=38
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ANGL=39
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PRNT=40
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LERP=41
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STEP=42
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SMOOTHSTEP=43
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FRACT=44
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RELU=45
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SOFTPLUS=46
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GELU=47
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SIGN=48
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MAP=49
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CONV=50
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SWAP=51
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PERM=52
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PLUS=53
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MINUS=54
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MULT=55
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DIV=56
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MOD=57
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POW=58
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GE=59
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GT=60
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LE=61
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LT=62
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EQ=63
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NE=64
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PIPE=65
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CONSTANT=66
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NUMBER=67
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VARIABLE=68
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WS=69
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'('=1
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')'=2
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','=3
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'sin'=4
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'cos'=5
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'tan'=6
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'asin'=7
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'acos'=8
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'atan'=9
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'atan2'=10
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'sinh'=11
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'cosh'=12
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'tanh'=13
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'asinh'=14
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'acosh'=15
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'atanh'=16
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'abs'=17
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'sqrt'=18
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'ln'=19
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'log'=20
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'exp'=21
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'smin'=22
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'smax'=23
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'tmin'=24
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'tmax'=25
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'tnorm'=26
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'snorm'=27
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'floor'=28
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'ceil'=29
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'round'=30
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'gamma'=31
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'pow'=32
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'sigm'=33
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'clamp'=34
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'fft'=35
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'ifft'=36
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'angle'=37
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'print'=38
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'lerp'=39
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'step'=40
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'smoothstep'=41
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'fract'=42
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'relu'=43
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'softplus'=44
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'gelu'=45
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'sign'=46
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'swap'=47
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'+'=48
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'-'=49
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'*'=50
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'/'=51
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'%'=52
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'^'=53
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'>='=54
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'>'=55
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'<='=56
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'<'=57
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'=='=58
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'!='=59
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'|'=60
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'['=3
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','=4
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']'=5
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'sin'=6
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'cos'=7
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'tan'=8
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'asin'=9
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'acos'=10
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'atan'=11
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'atan2'=12
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'sinh'=13
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'cosh'=14
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'tanh'=15
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'asinh'=16
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'acosh'=17
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'atanh'=18
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'abs'=19
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'sqrt'=20
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'ln'=21
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'log'=22
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'exp'=23
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'smin'=24
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'smax'=25
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'tmin'=26
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'tmax'=27
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'tnorm'=28
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'snorm'=29
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'floor'=30
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'ceil'=31
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'round'=32
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'gamma'=33
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'pow'=34
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'sigm'=35
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'clamp'=36
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'fft'=37
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'ifft'=38
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'angle'=39
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'print'=40
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'lerp'=41
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'step'=42
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'smoothstep'=43
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'fract'=44
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'relu'=45
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'softplus'=46
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'gelu'=47
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'sign'=48
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'map'=49
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'conv'=50
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'swap'=51
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'permute'=52
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'+'=53
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'-'=54
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'*'=55
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'/'=56
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'%'=57
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'^'=58
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'>='=59
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'>'=60
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'<='=61
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'<'=62
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'=='=63
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'!='=64
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'|'=65
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File diff suppressed because one or more lines are too long
+242
-224
@@ -10,7 +10,7 @@ else:
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def serializedATN():
|
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return [
|
||||
4,0,64,432,6,-1,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,
|
||||
4,0,69,463,6,-1,2,0,7,0,2,1,7,1,2,2,7,2,2,3,7,3,2,4,7,4,2,5,7,5,
|
||||
2,6,7,6,2,7,7,7,2,8,7,8,2,9,7,9,2,10,7,10,2,11,7,11,2,12,7,12,2,
|
||||
13,7,13,2,14,7,14,2,15,7,15,2,16,7,16,2,17,7,17,2,18,7,18,2,19,7,
|
||||
19,2,20,7,20,2,21,7,21,2,22,7,22,2,23,7,23,2,24,7,24,2,25,7,25,2,
|
||||
@@ -19,149 +19,159 @@ def serializedATN():
|
||||
39,7,39,2,40,7,40,2,41,7,41,2,42,7,42,2,43,7,43,2,44,7,44,2,45,7,
|
||||
45,2,46,7,46,2,47,7,47,2,48,7,48,2,49,7,49,2,50,7,50,2,51,7,51,2,
|
||||
52,7,52,2,53,7,53,2,54,7,54,2,55,7,55,2,56,7,56,2,57,7,57,2,58,7,
|
||||
58,2,59,7,59,2,60,7,60,2,61,7,61,2,62,7,62,2,63,7,63,1,0,1,0,1,1,
|
||||
1,1,1,2,1,2,1,3,1,3,1,3,1,3,1,4,1,4,1,4,1,4,1,5,1,5,1,5,1,5,1,6,
|
||||
1,6,1,6,1,6,1,6,1,7,1,7,1,7,1,7,1,7,1,8,1,8,1,8,1,8,1,8,1,9,1,9,
|
||||
1,9,1,9,1,9,1,9,1,10,1,10,1,10,1,10,1,10,1,11,1,11,1,11,1,11,1,11,
|
||||
1,12,1,12,1,12,1,12,1,12,1,13,1,13,1,13,1,13,1,13,1,13,1,14,1,14,
|
||||
1,14,1,14,1,14,1,14,1,15,1,15,1,15,1,15,1,15,1,15,1,16,1,16,1,16,
|
||||
1,16,1,17,1,17,1,17,1,17,1,17,1,18,1,18,1,18,1,19,1,19,1,19,1,19,
|
||||
1,20,1,20,1,20,1,20,1,21,1,21,1,21,1,21,1,21,1,22,1,22,1,22,1,22,
|
||||
1,22,1,23,1,23,1,23,1,23,1,23,1,24,1,24,1,24,1,24,1,24,1,25,1,25,
|
||||
1,25,1,25,1,25,1,25,1,26,1,26,1,26,1,26,1,26,1,26,1,27,1,27,1,27,
|
||||
1,27,1,27,1,27,1,28,1,28,1,28,1,28,1,28,1,29,1,29,1,29,1,29,1,29,
|
||||
1,29,1,30,1,30,1,30,1,30,1,30,1,30,1,31,1,31,1,31,1,31,1,32,1,32,
|
||||
1,32,1,32,1,32,1,33,1,33,1,33,1,33,1,33,1,33,1,34,1,34,1,34,1,34,
|
||||
1,35,1,35,1,35,1,35,1,35,1,36,1,36,1,36,1,36,1,36,1,36,1,37,1,37,
|
||||
1,37,1,37,1,37,1,37,1,38,1,38,1,38,1,38,1,38,1,39,1,39,1,39,1,39,
|
||||
1,39,1,40,1,40,1,40,1,40,1,40,1,40,1,40,1,40,1,40,1,40,1,40,1,41,
|
||||
1,41,1,41,1,41,1,41,1,41,1,42,1,42,1,42,1,42,1,42,1,43,1,43,1,43,
|
||||
1,43,1,43,1,43,1,43,1,43,1,43,1,44,1,44,1,44,1,44,1,44,1,45,1,45,
|
||||
1,45,1,45,1,45,1,46,1,46,1,46,1,46,1,46,1,47,1,47,1,48,1,48,1,49,
|
||||
1,49,1,50,1,50,1,51,1,51,1,52,1,52,1,53,1,53,1,53,1,54,1,54,1,55,
|
||||
1,55,1,55,1,56,1,56,1,57,1,57,1,57,1,58,1,58,1,58,1,59,1,59,1,60,
|
||||
1,60,1,60,1,60,1,60,3,60,404,8,60,1,61,4,61,407,8,61,11,61,12,61,
|
||||
408,1,61,1,61,4,61,413,8,61,11,61,12,61,414,3,61,417,8,61,1,62,1,
|
||||
62,5,62,421,8,62,10,62,12,62,424,9,62,1,63,4,63,427,8,63,11,63,12,
|
||||
63,428,1,63,1,63,0,0,64,1,1,3,2,5,3,7,4,9,5,11,6,13,7,15,8,17,9,
|
||||
19,10,21,11,23,12,25,13,27,14,29,15,31,16,33,17,35,18,37,19,39,20,
|
||||
41,21,43,22,45,23,47,24,49,25,51,26,53,27,55,28,57,29,59,30,61,31,
|
||||
63,32,65,33,67,34,69,35,71,36,73,37,75,38,77,39,79,40,81,41,83,42,
|
||||
85,43,87,44,89,45,91,46,93,47,95,48,97,49,99,50,101,51,103,52,105,
|
||||
53,107,54,109,55,111,56,113,57,115,58,117,59,119,60,121,61,123,62,
|
||||
125,63,127,64,1,0,5,2,0,69,69,101,101,1,0,48,57,3,0,65,90,95,95,
|
||||
97,122,4,0,48,57,65,90,95,95,97,122,3,0,9,10,13,13,32,32,438,0,1,
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||||
1,0,0,0,0,3,1,0,0,0,0,5,1,0,0,0,0,7,1,0,0,0,0,9,1,0,0,0,0,11,1,0,
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||||
0,0,0,13,1,0,0,0,0,15,1,0,0,0,0,17,1,0,0,0,0,19,1,0,0,0,0,21,1,0,
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0,0,0,23,1,0,0,0,0,25,1,0,0,0,0,27,1,0,0,0,0,29,1,0,0,0,0,31,1,0,
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0,0,0,33,1,0,0,0,0,35,1,0,0,0,0,37,1,0,0,0,0,39,1,0,0,0,0,41,1,0,
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0,0,0,43,1,0,0,0,0,45,1,0,0,0,0,47,1,0,0,0,0,49,1,0,0,0,0,51,1,0,
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0,0,0,53,1,0,0,0,0,55,1,0,0,0,0,57,1,0,0,0,0,59,1,0,0,0,0,61,1,0,
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0,0,0,63,1,0,0,0,0,65,1,0,0,0,0,67,1,0,0,0,0,69,1,0,0,0,0,71,1,0,
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0,0,0,73,1,0,0,0,0,75,1,0,0,0,0,77,1,0,0,0,0,79,1,0,0,0,0,81,1,0,
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0,0,0,83,1,0,0,0,0,85,1,0,0,0,0,87,1,0,0,0,0,89,1,0,0,0,0,91,1,0,
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0,0,0,93,1,0,0,0,0,95,1,0,0,0,0,97,1,0,0,0,0,99,1,0,0,0,0,101,1,
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0,0,0,0,103,1,0,0,0,0,105,1,0,0,0,0,107,1,0,0,0,0,109,1,0,0,0,0,
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111,1,0,0,0,0,113,1,0,0,0,0,115,1,0,0,0,0,117,1,0,0,0,0,119,1,0,
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0,0,0,121,1,0,0,0,0,123,1,0,0,0,0,125,1,0,0,0,0,127,1,0,0,0,1,129,
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1,0,0,0,3,131,1,0,0,0,5,133,1,0,0,0,7,135,1,0,0,0,9,139,1,0,0,0,
|
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11,143,1,0,0,0,13,147,1,0,0,0,15,152,1,0,0,0,17,157,1,0,0,0,19,162,
|
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1,0,0,0,21,168,1,0,0,0,23,173,1,0,0,0,25,178,1,0,0,0,27,183,1,0,
|
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0,0,29,189,1,0,0,0,31,195,1,0,0,0,33,201,1,0,0,0,35,205,1,0,0,0,
|
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37,210,1,0,0,0,39,213,1,0,0,0,41,217,1,0,0,0,43,221,1,0,0,0,45,226,
|
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1,0,0,0,47,231,1,0,0,0,49,236,1,0,0,0,51,241,1,0,0,0,53,247,1,0,
|
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0,0,55,253,1,0,0,0,57,259,1,0,0,0,59,264,1,0,0,0,61,270,1,0,0,0,
|
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63,276,1,0,0,0,65,280,1,0,0,0,67,285,1,0,0,0,69,291,1,0,0,0,71,295,
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1,0,0,0,73,300,1,0,0,0,75,306,1,0,0,0,77,312,1,0,0,0,79,317,1,0,
|
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0,0,81,322,1,0,0,0,83,333,1,0,0,0,85,339,1,0,0,0,87,344,1,0,0,0,
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89,353,1,0,0,0,91,358,1,0,0,0,93,363,1,0,0,0,95,368,1,0,0,0,97,370,
|
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1,0,0,0,99,372,1,0,0,0,101,374,1,0,0,0,103,376,1,0,0,0,105,378,1,
|
||||
0,0,0,107,380,1,0,0,0,109,383,1,0,0,0,111,385,1,0,0,0,113,388,1,
|
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0,0,0,115,390,1,0,0,0,117,393,1,0,0,0,119,396,1,0,0,0,121,403,1,
|
||||
0,0,0,123,406,1,0,0,0,125,418,1,0,0,0,127,426,1,0,0,0,129,130,5,
|
||||
40,0,0,130,2,1,0,0,0,131,132,5,41,0,0,132,4,1,0,0,0,133,134,5,44,
|
||||
0,0,134,6,1,0,0,0,135,136,5,115,0,0,136,137,5,105,0,0,137,138,5,
|
||||
110,0,0,138,8,1,0,0,0,139,140,5,99,0,0,140,141,5,111,0,0,141,142,
|
||||
5,115,0,0,142,10,1,0,0,0,143,144,5,116,0,0,144,145,5,97,0,0,145,
|
||||
146,5,110,0,0,146,12,1,0,0,0,147,148,5,97,0,0,148,149,5,115,0,0,
|
||||
149,150,5,105,0,0,150,151,5,110,0,0,151,14,1,0,0,0,152,153,5,97,
|
||||
0,0,153,154,5,99,0,0,154,155,5,111,0,0,155,156,5,115,0,0,156,16,
|
||||
1,0,0,0,157,158,5,97,0,0,158,159,5,116,0,0,159,160,5,97,0,0,160,
|
||||
161,5,110,0,0,161,18,1,0,0,0,162,163,5,97,0,0,163,164,5,116,0,0,
|
||||
164,165,5,97,0,0,165,166,5,110,0,0,166,167,5,50,0,0,167,20,1,0,0,
|
||||
0,168,169,5,115,0,0,169,170,5,105,0,0,170,171,5,110,0,0,171,172,
|
||||
5,104,0,0,172,22,1,0,0,0,173,174,5,99,0,0,174,175,5,111,0,0,175,
|
||||
176,5,115,0,0,176,177,5,104,0,0,177,24,1,0,0,0,178,179,5,116,0,0,
|
||||
179,180,5,97,0,0,180,181,5,110,0,0,181,182,5,104,0,0,182,26,1,0,
|
||||
0,0,183,184,5,97,0,0,184,185,5,115,0,0,185,186,5,105,0,0,186,187,
|
||||
5,110,0,0,187,188,5,104,0,0,188,28,1,0,0,0,189,190,5,97,0,0,190,
|
||||
191,5,99,0,0,191,192,5,111,0,0,192,193,5,115,0,0,193,194,5,104,0,
|
||||
0,194,30,1,0,0,0,195,196,5,97,0,0,196,197,5,116,0,0,197,198,5,97,
|
||||
0,0,198,199,5,110,0,0,199,200,5,104,0,0,200,32,1,0,0,0,201,202,5,
|
||||
97,0,0,202,203,5,98,0,0,203,204,5,115,0,0,204,34,1,0,0,0,205,206,
|
||||
5,115,0,0,206,207,5,113,0,0,207,208,5,114,0,0,208,209,5,116,0,0,
|
||||
209,36,1,0,0,0,210,211,5,108,0,0,211,212,5,110,0,0,212,38,1,0,0,
|
||||
0,213,214,5,108,0,0,214,215,5,111,0,0,215,216,5,103,0,0,216,40,1,
|
||||
0,0,0,217,218,5,101,0,0,218,219,5,120,0,0,219,220,5,112,0,0,220,
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||||
42,1,0,0,0,221,222,5,115,0,0,222,223,5,109,0,0,223,224,5,105,0,0,
|
||||
224,225,5,110,0,0,225,44,1,0,0,0,226,227,5,115,0,0,227,228,5,109,
|
||||
0,0,228,229,5,97,0,0,229,230,5,120,0,0,230,46,1,0,0,0,231,232,5,
|
||||
116,0,0,232,233,5,109,0,0,233,234,5,105,0,0,234,235,5,110,0,0,235,
|
||||
48,1,0,0,0,236,237,5,116,0,0,237,238,5,109,0,0,238,239,5,97,0,0,
|
||||
239,240,5,120,0,0,240,50,1,0,0,0,241,242,5,116,0,0,242,243,5,110,
|
||||
0,0,243,244,5,111,0,0,244,245,5,114,0,0,245,246,5,109,0,0,246,52,
|
||||
1,0,0,0,247,248,5,115,0,0,248,249,5,110,0,0,249,250,5,111,0,0,250,
|
||||
251,5,114,0,0,251,252,5,109,0,0,252,54,1,0,0,0,253,254,5,102,0,0,
|
||||
254,255,5,108,0,0,255,256,5,111,0,0,256,257,5,111,0,0,257,258,5,
|
||||
114,0,0,258,56,1,0,0,0,259,260,5,99,0,0,260,261,5,101,0,0,261,262,
|
||||
5,105,0,0,262,263,5,108,0,0,263,58,1,0,0,0,264,265,5,114,0,0,265,
|
||||
266,5,111,0,0,266,267,5,117,0,0,267,268,5,110,0,0,268,269,5,100,
|
||||
0,0,269,60,1,0,0,0,270,271,5,103,0,0,271,272,5,97,0,0,272,273,5,
|
||||
109,0,0,273,274,5,109,0,0,274,275,5,97,0,0,275,62,1,0,0,0,276,277,
|
||||
5,112,0,0,277,278,5,111,0,0,278,279,5,119,0,0,279,64,1,0,0,0,280,
|
||||
281,5,115,0,0,281,282,5,105,0,0,282,283,5,103,0,0,283,284,5,109,
|
||||
0,0,284,66,1,0,0,0,285,286,5,99,0,0,286,287,5,108,0,0,287,288,5,
|
||||
97,0,0,288,289,5,109,0,0,289,290,5,112,0,0,290,68,1,0,0,0,291,292,
|
||||
5,102,0,0,292,293,5,102,0,0,293,294,5,116,0,0,294,70,1,0,0,0,295,
|
||||
296,5,105,0,0,296,297,5,102,0,0,297,298,5,102,0,0,298,299,5,116,
|
||||
0,0,299,72,1,0,0,0,300,301,5,97,0,0,301,302,5,110,0,0,302,303,5,
|
||||
103,0,0,303,304,5,108,0,0,304,305,5,101,0,0,305,74,1,0,0,0,306,307,
|
||||
5,112,0,0,307,308,5,114,0,0,308,309,5,105,0,0,309,310,5,110,0,0,
|
||||
310,311,5,116,0,0,311,76,1,0,0,0,312,313,5,108,0,0,313,314,5,101,
|
||||
0,0,314,315,5,114,0,0,315,316,5,112,0,0,316,78,1,0,0,0,317,318,5,
|
||||
115,0,0,318,319,5,116,0,0,319,320,5,101,0,0,320,321,5,112,0,0,321,
|
||||
80,1,0,0,0,322,323,5,115,0,0,323,324,5,109,0,0,324,325,5,111,0,0,
|
||||
325,326,5,111,0,0,326,327,5,116,0,0,327,328,5,104,0,0,328,329,5,
|
||||
115,0,0,329,330,5,116,0,0,330,331,5,101,0,0,331,332,5,112,0,0,332,
|
||||
82,1,0,0,0,333,334,5,102,0,0,334,335,5,114,0,0,335,336,5,97,0,0,
|
||||
336,337,5,99,0,0,337,338,5,116,0,0,338,84,1,0,0,0,339,340,5,114,
|
||||
0,0,340,341,5,101,0,0,341,342,5,108,0,0,342,343,5,117,0,0,343,86,
|
||||
1,0,0,0,344,345,5,115,0,0,345,346,5,111,0,0,346,347,5,102,0,0,347,
|
||||
348,5,116,0,0,348,349,5,112,0,0,349,350,5,108,0,0,350,351,5,117,
|
||||
0,0,351,352,5,115,0,0,352,88,1,0,0,0,353,354,5,103,0,0,354,355,5,
|
||||
101,0,0,355,356,5,108,0,0,356,357,5,117,0,0,357,90,1,0,0,0,358,359,
|
||||
5,115,0,0,359,360,5,105,0,0,360,361,5,103,0,0,361,362,5,110,0,0,
|
||||
362,92,1,0,0,0,363,364,5,115,0,0,364,365,5,119,0,0,365,366,5,97,
|
||||
0,0,366,367,5,112,0,0,367,94,1,0,0,0,368,369,5,43,0,0,369,96,1,0,
|
||||
0,0,370,371,5,45,0,0,371,98,1,0,0,0,372,373,5,42,0,0,373,100,1,0,
|
||||
0,0,374,375,5,47,0,0,375,102,1,0,0,0,376,377,5,37,0,0,377,104,1,
|
||||
0,0,0,378,379,5,94,0,0,379,106,1,0,0,0,380,381,5,62,0,0,381,382,
|
||||
5,61,0,0,382,108,1,0,0,0,383,384,5,62,0,0,384,110,1,0,0,0,385,386,
|
||||
5,60,0,0,386,387,5,61,0,0,387,112,1,0,0,0,388,389,5,60,0,0,389,114,
|
||||
1,0,0,0,390,391,5,61,0,0,391,392,5,61,0,0,392,116,1,0,0,0,393,394,
|
||||
5,33,0,0,394,395,5,61,0,0,395,118,1,0,0,0,396,397,5,124,0,0,397,
|
||||
120,1,0,0,0,398,399,5,112,0,0,399,404,5,105,0,0,400,401,5,80,0,0,
|
||||
401,404,5,73,0,0,402,404,7,0,0,0,403,398,1,0,0,0,403,400,1,0,0,0,
|
||||
403,402,1,0,0,0,404,122,1,0,0,0,405,407,7,1,0,0,406,405,1,0,0,0,
|
||||
407,408,1,0,0,0,408,406,1,0,0,0,408,409,1,0,0,0,409,416,1,0,0,0,
|
||||
410,412,5,46,0,0,411,413,7,1,0,0,412,411,1,0,0,0,413,414,1,0,0,0,
|
||||
414,412,1,0,0,0,414,415,1,0,0,0,415,417,1,0,0,0,416,410,1,0,0,0,
|
||||
416,417,1,0,0,0,417,124,1,0,0,0,418,422,7,2,0,0,419,421,7,3,0,0,
|
||||
420,419,1,0,0,0,421,424,1,0,0,0,422,420,1,0,0,0,422,423,1,0,0,0,
|
||||
423,126,1,0,0,0,424,422,1,0,0,0,425,427,7,4,0,0,426,425,1,0,0,0,
|
||||
427,428,1,0,0,0,428,426,1,0,0,0,428,429,1,0,0,0,429,430,1,0,0,0,
|
||||
430,431,6,63,0,0,431,128,1,0,0,0,7,0,403,408,414,416,422,428,1,6,
|
||||
0,0
|
||||
58,2,59,7,59,2,60,7,60,2,61,7,61,2,62,7,62,2,63,7,63,2,64,7,64,2,
|
||||
65,7,65,2,66,7,66,2,67,7,67,2,68,7,68,1,0,1,0,1,1,1,1,1,2,1,2,1,
|
||||
3,1,3,1,4,1,4,1,5,1,5,1,5,1,5,1,6,1,6,1,6,1,6,1,7,1,7,1,7,1,7,1,
|
||||
8,1,8,1,8,1,8,1,8,1,9,1,9,1,9,1,9,1,9,1,10,1,10,1,10,1,10,1,10,1,
|
||||
11,1,11,1,11,1,11,1,11,1,11,1,12,1,12,1,12,1,12,1,12,1,13,1,13,1,
|
||||
13,1,13,1,13,1,14,1,14,1,14,1,14,1,14,1,15,1,15,1,15,1,15,1,15,1,
|
||||
15,1,16,1,16,1,16,1,16,1,16,1,16,1,17,1,17,1,17,1,17,1,17,1,17,1,
|
||||
18,1,18,1,18,1,18,1,19,1,19,1,19,1,19,1,19,1,20,1,20,1,20,1,21,1,
|
||||
21,1,21,1,21,1,22,1,22,1,22,1,22,1,23,1,23,1,23,1,23,1,23,1,24,1,
|
||||
24,1,24,1,24,1,24,1,25,1,25,1,25,1,25,1,25,1,26,1,26,1,26,1,26,1,
|
||||
26,1,27,1,27,1,27,1,27,1,27,1,27,1,28,1,28,1,28,1,28,1,28,1,28,1,
|
||||
29,1,29,1,29,1,29,1,29,1,29,1,30,1,30,1,30,1,30,1,30,1,31,1,31,1,
|
||||
31,1,31,1,31,1,31,1,32,1,32,1,32,1,32,1,32,1,32,1,33,1,33,1,33,1,
|
||||
33,1,34,1,34,1,34,1,34,1,34,1,35,1,35,1,35,1,35,1,35,1,35,1,36,1,
|
||||
36,1,36,1,36,1,37,1,37,1,37,1,37,1,37,1,38,1,38,1,38,1,38,1,38,1,
|
||||
38,1,39,1,39,1,39,1,39,1,39,1,39,1,40,1,40,1,40,1,40,1,40,1,41,1,
|
||||
41,1,41,1,41,1,41,1,42,1,42,1,42,1,42,1,42,1,42,1,42,1,42,1,42,1,
|
||||
42,1,42,1,43,1,43,1,43,1,43,1,43,1,43,1,44,1,44,1,44,1,44,1,44,1,
|
||||
45,1,45,1,45,1,45,1,45,1,45,1,45,1,45,1,45,1,46,1,46,1,46,1,46,1,
|
||||
46,1,47,1,47,1,47,1,47,1,47,1,48,1,48,1,48,1,48,1,49,1,49,1,49,1,
|
||||
49,1,49,1,50,1,50,1,50,1,50,1,50,1,51,1,51,1,51,1,51,1,51,1,51,1,
|
||||
51,1,51,1,52,1,52,1,53,1,53,1,54,1,54,1,55,1,55,1,56,1,56,1,57,1,
|
||||
57,1,58,1,58,1,58,1,59,1,59,1,60,1,60,1,60,1,61,1,61,1,62,1,62,1,
|
||||
62,1,63,1,63,1,63,1,64,1,64,1,65,1,65,1,65,1,65,1,65,3,65,435,8,
|
||||
65,1,66,4,66,438,8,66,11,66,12,66,439,1,66,1,66,4,66,444,8,66,11,
|
||||
66,12,66,445,3,66,448,8,66,1,67,1,67,5,67,452,8,67,10,67,12,67,455,
|
||||
9,67,1,68,4,68,458,8,68,11,68,12,68,459,1,68,1,68,0,0,69,1,1,3,2,
|
||||
5,3,7,4,9,5,11,6,13,7,15,8,17,9,19,10,21,11,23,12,25,13,27,14,29,
|
||||
15,31,16,33,17,35,18,37,19,39,20,41,21,43,22,45,23,47,24,49,25,51,
|
||||
26,53,27,55,28,57,29,59,30,61,31,63,32,65,33,67,34,69,35,71,36,73,
|
||||
37,75,38,77,39,79,40,81,41,83,42,85,43,87,44,89,45,91,46,93,47,95,
|
||||
48,97,49,99,50,101,51,103,52,105,53,107,54,109,55,111,56,113,57,
|
||||
115,58,117,59,119,60,121,61,123,62,125,63,127,64,129,65,131,66,133,
|
||||
67,135,68,137,69,1,0,5,2,0,69,69,101,101,1,0,48,57,3,0,65,90,95,
|
||||
95,97,122,4,0,48,57,65,90,95,95,97,122,3,0,9,10,13,13,32,32,469,
|
||||
0,1,1,0,0,0,0,3,1,0,0,0,0,5,1,0,0,0,0,7,1,0,0,0,0,9,1,0,0,0,0,11,
|
||||
1,0,0,0,0,13,1,0,0,0,0,15,1,0,0,0,0,17,1,0,0,0,0,19,1,0,0,0,0,21,
|
||||
1,0,0,0,0,23,1,0,0,0,0,25,1,0,0,0,0,27,1,0,0,0,0,29,1,0,0,0,0,31,
|
||||
1,0,0,0,0,33,1,0,0,0,0,35,1,0,0,0,0,37,1,0,0,0,0,39,1,0,0,0,0,41,
|
||||
1,0,0,0,0,43,1,0,0,0,0,45,1,0,0,0,0,47,1,0,0,0,0,49,1,0,0,0,0,51,
|
||||
1,0,0,0,0,53,1,0,0,0,0,55,1,0,0,0,0,57,1,0,0,0,0,59,1,0,0,0,0,61,
|
||||
1,0,0,0,0,63,1,0,0,0,0,65,1,0,0,0,0,67,1,0,0,0,0,69,1,0,0,0,0,71,
|
||||
1,0,0,0,0,73,1,0,0,0,0,75,1,0,0,0,0,77,1,0,0,0,0,79,1,0,0,0,0,81,
|
||||
1,0,0,0,0,83,1,0,0,0,0,85,1,0,0,0,0,87,1,0,0,0,0,89,1,0,0,0,0,91,
|
||||
1,0,0,0,0,93,1,0,0,0,0,95,1,0,0,0,0,97,1,0,0,0,0,99,1,0,0,0,0,101,
|
||||
1,0,0,0,0,103,1,0,0,0,0,105,1,0,0,0,0,107,1,0,0,0,0,109,1,0,0,0,
|
||||
0,111,1,0,0,0,0,113,1,0,0,0,0,115,1,0,0,0,0,117,1,0,0,0,0,119,1,
|
||||
0,0,0,0,121,1,0,0,0,0,123,1,0,0,0,0,125,1,0,0,0,0,127,1,0,0,0,0,
|
||||
129,1,0,0,0,0,131,1,0,0,0,0,133,1,0,0,0,0,135,1,0,0,0,0,137,1,0,
|
||||
0,0,1,139,1,0,0,0,3,141,1,0,0,0,5,143,1,0,0,0,7,145,1,0,0,0,9,147,
|
||||
1,0,0,0,11,149,1,0,0,0,13,153,1,0,0,0,15,157,1,0,0,0,17,161,1,0,
|
||||
0,0,19,166,1,0,0,0,21,171,1,0,0,0,23,176,1,0,0,0,25,182,1,0,0,0,
|
||||
27,187,1,0,0,0,29,192,1,0,0,0,31,197,1,0,0,0,33,203,1,0,0,0,35,209,
|
||||
1,0,0,0,37,215,1,0,0,0,39,219,1,0,0,0,41,224,1,0,0,0,43,227,1,0,
|
||||
0,0,45,231,1,0,0,0,47,235,1,0,0,0,49,240,1,0,0,0,51,245,1,0,0,0,
|
||||
53,250,1,0,0,0,55,255,1,0,0,0,57,261,1,0,0,0,59,267,1,0,0,0,61,273,
|
||||
1,0,0,0,63,278,1,0,0,0,65,284,1,0,0,0,67,290,1,0,0,0,69,294,1,0,
|
||||
0,0,71,299,1,0,0,0,73,305,1,0,0,0,75,309,1,0,0,0,77,314,1,0,0,0,
|
||||
79,320,1,0,0,0,81,326,1,0,0,0,83,331,1,0,0,0,85,336,1,0,0,0,87,347,
|
||||
1,0,0,0,89,353,1,0,0,0,91,358,1,0,0,0,93,367,1,0,0,0,95,372,1,0,
|
||||
0,0,97,377,1,0,0,0,99,381,1,0,0,0,101,386,1,0,0,0,103,391,1,0,0,
|
||||
0,105,399,1,0,0,0,107,401,1,0,0,0,109,403,1,0,0,0,111,405,1,0,0,
|
||||
0,113,407,1,0,0,0,115,409,1,0,0,0,117,411,1,0,0,0,119,414,1,0,0,
|
||||
0,121,416,1,0,0,0,123,419,1,0,0,0,125,421,1,0,0,0,127,424,1,0,0,
|
||||
0,129,427,1,0,0,0,131,434,1,0,0,0,133,437,1,0,0,0,135,449,1,0,0,
|
||||
0,137,457,1,0,0,0,139,140,5,40,0,0,140,2,1,0,0,0,141,142,5,41,0,
|
||||
0,142,4,1,0,0,0,143,144,5,91,0,0,144,6,1,0,0,0,145,146,5,44,0,0,
|
||||
146,8,1,0,0,0,147,148,5,93,0,0,148,10,1,0,0,0,149,150,5,115,0,0,
|
||||
150,151,5,105,0,0,151,152,5,110,0,0,152,12,1,0,0,0,153,154,5,99,
|
||||
0,0,154,155,5,111,0,0,155,156,5,115,0,0,156,14,1,0,0,0,157,158,5,
|
||||
116,0,0,158,159,5,97,0,0,159,160,5,110,0,0,160,16,1,0,0,0,161,162,
|
||||
5,97,0,0,162,163,5,115,0,0,163,164,5,105,0,0,164,165,5,110,0,0,165,
|
||||
18,1,0,0,0,166,167,5,97,0,0,167,168,5,99,0,0,168,169,5,111,0,0,169,
|
||||
170,5,115,0,0,170,20,1,0,0,0,171,172,5,97,0,0,172,173,5,116,0,0,
|
||||
173,174,5,97,0,0,174,175,5,110,0,0,175,22,1,0,0,0,176,177,5,97,0,
|
||||
0,177,178,5,116,0,0,178,179,5,97,0,0,179,180,5,110,0,0,180,181,5,
|
||||
50,0,0,181,24,1,0,0,0,182,183,5,115,0,0,183,184,5,105,0,0,184,185,
|
||||
5,110,0,0,185,186,5,104,0,0,186,26,1,0,0,0,187,188,5,99,0,0,188,
|
||||
189,5,111,0,0,189,190,5,115,0,0,190,191,5,104,0,0,191,28,1,0,0,0,
|
||||
192,193,5,116,0,0,193,194,5,97,0,0,194,195,5,110,0,0,195,196,5,104,
|
||||
0,0,196,30,1,0,0,0,197,198,5,97,0,0,198,199,5,115,0,0,199,200,5,
|
||||
105,0,0,200,201,5,110,0,0,201,202,5,104,0,0,202,32,1,0,0,0,203,204,
|
||||
5,97,0,0,204,205,5,99,0,0,205,206,5,111,0,0,206,207,5,115,0,0,207,
|
||||
208,5,104,0,0,208,34,1,0,0,0,209,210,5,97,0,0,210,211,5,116,0,0,
|
||||
211,212,5,97,0,0,212,213,5,110,0,0,213,214,5,104,0,0,214,36,1,0,
|
||||
0,0,215,216,5,97,0,0,216,217,5,98,0,0,217,218,5,115,0,0,218,38,1,
|
||||
0,0,0,219,220,5,115,0,0,220,221,5,113,0,0,221,222,5,114,0,0,222,
|
||||
223,5,116,0,0,223,40,1,0,0,0,224,225,5,108,0,0,225,226,5,110,0,0,
|
||||
226,42,1,0,0,0,227,228,5,108,0,0,228,229,5,111,0,0,229,230,5,103,
|
||||
0,0,230,44,1,0,0,0,231,232,5,101,0,0,232,233,5,120,0,0,233,234,5,
|
||||
112,0,0,234,46,1,0,0,0,235,236,5,115,0,0,236,237,5,109,0,0,237,238,
|
||||
5,105,0,0,238,239,5,110,0,0,239,48,1,0,0,0,240,241,5,115,0,0,241,
|
||||
242,5,109,0,0,242,243,5,97,0,0,243,244,5,120,0,0,244,50,1,0,0,0,
|
||||
245,246,5,116,0,0,246,247,5,109,0,0,247,248,5,105,0,0,248,249,5,
|
||||
110,0,0,249,52,1,0,0,0,250,251,5,116,0,0,251,252,5,109,0,0,252,253,
|
||||
5,97,0,0,253,254,5,120,0,0,254,54,1,0,0,0,255,256,5,116,0,0,256,
|
||||
257,5,110,0,0,257,258,5,111,0,0,258,259,5,114,0,0,259,260,5,109,
|
||||
0,0,260,56,1,0,0,0,261,262,5,115,0,0,262,263,5,110,0,0,263,264,5,
|
||||
111,0,0,264,265,5,114,0,0,265,266,5,109,0,0,266,58,1,0,0,0,267,268,
|
||||
5,102,0,0,268,269,5,108,0,0,269,270,5,111,0,0,270,271,5,111,0,0,
|
||||
271,272,5,114,0,0,272,60,1,0,0,0,273,274,5,99,0,0,274,275,5,101,
|
||||
0,0,275,276,5,105,0,0,276,277,5,108,0,0,277,62,1,0,0,0,278,279,5,
|
||||
114,0,0,279,280,5,111,0,0,280,281,5,117,0,0,281,282,5,110,0,0,282,
|
||||
283,5,100,0,0,283,64,1,0,0,0,284,285,5,103,0,0,285,286,5,97,0,0,
|
||||
286,287,5,109,0,0,287,288,5,109,0,0,288,289,5,97,0,0,289,66,1,0,
|
||||
0,0,290,291,5,112,0,0,291,292,5,111,0,0,292,293,5,119,0,0,293,68,
|
||||
1,0,0,0,294,295,5,115,0,0,295,296,5,105,0,0,296,297,5,103,0,0,297,
|
||||
298,5,109,0,0,298,70,1,0,0,0,299,300,5,99,0,0,300,301,5,108,0,0,
|
||||
301,302,5,97,0,0,302,303,5,109,0,0,303,304,5,112,0,0,304,72,1,0,
|
||||
0,0,305,306,5,102,0,0,306,307,5,102,0,0,307,308,5,116,0,0,308,74,
|
||||
1,0,0,0,309,310,5,105,0,0,310,311,5,102,0,0,311,312,5,102,0,0,312,
|
||||
313,5,116,0,0,313,76,1,0,0,0,314,315,5,97,0,0,315,316,5,110,0,0,
|
||||
316,317,5,103,0,0,317,318,5,108,0,0,318,319,5,101,0,0,319,78,1,0,
|
||||
0,0,320,321,5,112,0,0,321,322,5,114,0,0,322,323,5,105,0,0,323,324,
|
||||
5,110,0,0,324,325,5,116,0,0,325,80,1,0,0,0,326,327,5,108,0,0,327,
|
||||
328,5,101,0,0,328,329,5,114,0,0,329,330,5,112,0,0,330,82,1,0,0,0,
|
||||
331,332,5,115,0,0,332,333,5,116,0,0,333,334,5,101,0,0,334,335,5,
|
||||
112,0,0,335,84,1,0,0,0,336,337,5,115,0,0,337,338,5,109,0,0,338,339,
|
||||
5,111,0,0,339,340,5,111,0,0,340,341,5,116,0,0,341,342,5,104,0,0,
|
||||
342,343,5,115,0,0,343,344,5,116,0,0,344,345,5,101,0,0,345,346,5,
|
||||
112,0,0,346,86,1,0,0,0,347,348,5,102,0,0,348,349,5,114,0,0,349,350,
|
||||
5,97,0,0,350,351,5,99,0,0,351,352,5,116,0,0,352,88,1,0,0,0,353,354,
|
||||
5,114,0,0,354,355,5,101,0,0,355,356,5,108,0,0,356,357,5,117,0,0,
|
||||
357,90,1,0,0,0,358,359,5,115,0,0,359,360,5,111,0,0,360,361,5,102,
|
||||
0,0,361,362,5,116,0,0,362,363,5,112,0,0,363,364,5,108,0,0,364,365,
|
||||
5,117,0,0,365,366,5,115,0,0,366,92,1,0,0,0,367,368,5,103,0,0,368,
|
||||
369,5,101,0,0,369,370,5,108,0,0,370,371,5,117,0,0,371,94,1,0,0,0,
|
||||
372,373,5,115,0,0,373,374,5,105,0,0,374,375,5,103,0,0,375,376,5,
|
||||
110,0,0,376,96,1,0,0,0,377,378,5,109,0,0,378,379,5,97,0,0,379,380,
|
||||
5,112,0,0,380,98,1,0,0,0,381,382,5,99,0,0,382,383,5,111,0,0,383,
|
||||
384,5,110,0,0,384,385,5,118,0,0,385,100,1,0,0,0,386,387,5,115,0,
|
||||
0,387,388,5,119,0,0,388,389,5,97,0,0,389,390,5,112,0,0,390,102,1,
|
||||
0,0,0,391,392,5,112,0,0,392,393,5,101,0,0,393,394,5,114,0,0,394,
|
||||
395,5,109,0,0,395,396,5,117,0,0,396,397,5,116,0,0,397,398,5,101,
|
||||
0,0,398,104,1,0,0,0,399,400,5,43,0,0,400,106,1,0,0,0,401,402,5,45,
|
||||
0,0,402,108,1,0,0,0,403,404,5,42,0,0,404,110,1,0,0,0,405,406,5,47,
|
||||
0,0,406,112,1,0,0,0,407,408,5,37,0,0,408,114,1,0,0,0,409,410,5,94,
|
||||
0,0,410,116,1,0,0,0,411,412,5,62,0,0,412,413,5,61,0,0,413,118,1,
|
||||
0,0,0,414,415,5,62,0,0,415,120,1,0,0,0,416,417,5,60,0,0,417,418,
|
||||
5,61,0,0,418,122,1,0,0,0,419,420,5,60,0,0,420,124,1,0,0,0,421,422,
|
||||
5,61,0,0,422,423,5,61,0,0,423,126,1,0,0,0,424,425,5,33,0,0,425,426,
|
||||
5,61,0,0,426,128,1,0,0,0,427,428,5,124,0,0,428,130,1,0,0,0,429,430,
|
||||
5,112,0,0,430,435,5,105,0,0,431,432,5,80,0,0,432,435,5,73,0,0,433,
|
||||
435,7,0,0,0,434,429,1,0,0,0,434,431,1,0,0,0,434,433,1,0,0,0,435,
|
||||
132,1,0,0,0,436,438,7,1,0,0,437,436,1,0,0,0,438,439,1,0,0,0,439,
|
||||
437,1,0,0,0,439,440,1,0,0,0,440,447,1,0,0,0,441,443,5,46,0,0,442,
|
||||
444,7,1,0,0,443,442,1,0,0,0,444,445,1,0,0,0,445,443,1,0,0,0,445,
|
||||
446,1,0,0,0,446,448,1,0,0,0,447,441,1,0,0,0,447,448,1,0,0,0,448,
|
||||
134,1,0,0,0,449,453,7,2,0,0,450,452,7,3,0,0,451,450,1,0,0,0,452,
|
||||
455,1,0,0,0,453,451,1,0,0,0,453,454,1,0,0,0,454,136,1,0,0,0,455,
|
||||
453,1,0,0,0,456,458,7,4,0,0,457,456,1,0,0,0,458,459,1,0,0,0,459,
|
||||
457,1,0,0,0,459,460,1,0,0,0,460,461,1,0,0,0,461,462,6,68,0,0,462,
|
||||
138,1,0,0,0,7,0,434,439,445,447,453,459,1,6,0,0
|
||||
]
|
||||
|
||||
class MathExprLexer(Lexer):
|
||||
@@ -173,82 +183,88 @@ class MathExprLexer(Lexer):
|
||||
T__0 = 1
|
||||
T__1 = 2
|
||||
T__2 = 3
|
||||
SIN = 4
|
||||
COS = 5
|
||||
TAN = 6
|
||||
ASIN = 7
|
||||
ACOS = 8
|
||||
ATAN = 9
|
||||
ATAN2 = 10
|
||||
SINH = 11
|
||||
COSH = 12
|
||||
TANH = 13
|
||||
ASINH = 14
|
||||
ACOSH = 15
|
||||
ATANH = 16
|
||||
ABS = 17
|
||||
SQRT = 18
|
||||
LN = 19
|
||||
LOG = 20
|
||||
EXP = 21
|
||||
SMIN = 22
|
||||
SMAX = 23
|
||||
TMIN = 24
|
||||
TMAX = 25
|
||||
TNORM = 26
|
||||
SNORM = 27
|
||||
FLOOR = 28
|
||||
CEIL = 29
|
||||
ROUND = 30
|
||||
GAMMA = 31
|
||||
POWE = 32
|
||||
SIGM = 33
|
||||
CLAMP = 34
|
||||
SFFT = 35
|
||||
SIFFT = 36
|
||||
ANGL = 37
|
||||
PRNT = 38
|
||||
LERP = 39
|
||||
STEP = 40
|
||||
SMOOTHSTEP = 41
|
||||
FRACT = 42
|
||||
RELU = 43
|
||||
SOFTPLUS = 44
|
||||
GELU = 45
|
||||
SIGN = 46
|
||||
SWAP = 47
|
||||
PLUS = 48
|
||||
MINUS = 49
|
||||
MULT = 50
|
||||
DIV = 51
|
||||
MOD = 52
|
||||
POW = 53
|
||||
GE = 54
|
||||
GT = 55
|
||||
LE = 56
|
||||
LT = 57
|
||||
EQ = 58
|
||||
NE = 59
|
||||
PIPE = 60
|
||||
CONSTANT = 61
|
||||
NUMBER = 62
|
||||
VARIABLE = 63
|
||||
WS = 64
|
||||
T__3 = 4
|
||||
T__4 = 5
|
||||
SIN = 6
|
||||
COS = 7
|
||||
TAN = 8
|
||||
ASIN = 9
|
||||
ACOS = 10
|
||||
ATAN = 11
|
||||
ATAN2 = 12
|
||||
SINH = 13
|
||||
COSH = 14
|
||||
TANH = 15
|
||||
ASINH = 16
|
||||
ACOSH = 17
|
||||
ATANH = 18
|
||||
ABS = 19
|
||||
SQRT = 20
|
||||
LN = 21
|
||||
LOG = 22
|
||||
EXP = 23
|
||||
SMIN = 24
|
||||
SMAX = 25
|
||||
TMIN = 26
|
||||
TMAX = 27
|
||||
TNORM = 28
|
||||
SNORM = 29
|
||||
FLOOR = 30
|
||||
CEIL = 31
|
||||
ROUND = 32
|
||||
GAMMA = 33
|
||||
POWE = 34
|
||||
SIGM = 35
|
||||
CLAMP = 36
|
||||
SFFT = 37
|
||||
SIFFT = 38
|
||||
ANGL = 39
|
||||
PRNT = 40
|
||||
LERP = 41
|
||||
STEP = 42
|
||||
SMOOTHSTEP = 43
|
||||
FRACT = 44
|
||||
RELU = 45
|
||||
SOFTPLUS = 46
|
||||
GELU = 47
|
||||
SIGN = 48
|
||||
MAP = 49
|
||||
CONV = 50
|
||||
SWAP = 51
|
||||
PERM = 52
|
||||
PLUS = 53
|
||||
MINUS = 54
|
||||
MULT = 55
|
||||
DIV = 56
|
||||
MOD = 57
|
||||
POW = 58
|
||||
GE = 59
|
||||
GT = 60
|
||||
LE = 61
|
||||
LT = 62
|
||||
EQ = 63
|
||||
NE = 64
|
||||
PIPE = 65
|
||||
CONSTANT = 66
|
||||
NUMBER = 67
|
||||
VARIABLE = 68
|
||||
WS = 69
|
||||
|
||||
channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ]
|
||||
|
||||
modeNames = [ "DEFAULT_MODE" ]
|
||||
|
||||
literalNames = [ "<INVALID>",
|
||||
"'('", "')'", "','", "'sin'", "'cos'", "'tan'", "'asin'", "'acos'",
|
||||
"'atan'", "'atan2'", "'sinh'", "'cosh'", "'tanh'", "'asinh'",
|
||||
"'acosh'", "'atanh'", "'abs'", "'sqrt'", "'ln'", "'log'", "'exp'",
|
||||
"'smin'", "'smax'", "'tmin'", "'tmax'", "'tnorm'", "'snorm'",
|
||||
"'floor'", "'ceil'", "'round'", "'gamma'", "'pow'", "'sigm'",
|
||||
"'clamp'", "'fft'", "'ifft'", "'angle'", "'print'", "'lerp'",
|
||||
"'step'", "'smoothstep'", "'fract'", "'relu'", "'softplus'",
|
||||
"'gelu'", "'sign'", "'swap'", "'+'", "'-'", "'*'", "'/'", "'%'",
|
||||
"'^'", "'>='", "'>'", "'<='", "'<'", "'=='", "'!='", "'|'" ]
|
||||
"'('", "')'", "'['", "','", "']'", "'sin'", "'cos'", "'tan'",
|
||||
"'asin'", "'acos'", "'atan'", "'atan2'", "'sinh'", "'cosh'",
|
||||
"'tanh'", "'asinh'", "'acosh'", "'atanh'", "'abs'", "'sqrt'",
|
||||
"'ln'", "'log'", "'exp'", "'smin'", "'smax'", "'tmin'", "'tmax'",
|
||||
"'tnorm'", "'snorm'", "'floor'", "'ceil'", "'round'", "'gamma'",
|
||||
"'pow'", "'sigm'", "'clamp'", "'fft'", "'ifft'", "'angle'",
|
||||
"'print'", "'lerp'", "'step'", "'smoothstep'", "'fract'", "'relu'",
|
||||
"'softplus'", "'gelu'", "'sign'", "'map'", "'conv'", "'swap'",
|
||||
"'permute'", "'+'", "'-'", "'*'", "'/'", "'%'", "'^'", "'>='",
|
||||
"'>'", "'<='", "'<'", "'=='", "'!='", "'|'" ]
|
||||
|
||||
symbolicNames = [ "<INVALID>",
|
||||
"SIN", "COS", "TAN", "ASIN", "ACOS", "ATAN", "ATAN2", "SINH",
|
||||
@@ -256,17 +272,19 @@ class MathExprLexer(Lexer):
|
||||
"LOG", "EXP", "SMIN", "SMAX", "TMIN", "TMAX", "TNORM", "SNORM",
|
||||
"FLOOR", "CEIL", "ROUND", "GAMMA", "POWE", "SIGM", "CLAMP",
|
||||
"SFFT", "SIFFT", "ANGL", "PRNT", "LERP", "STEP", "SMOOTHSTEP",
|
||||
"FRACT", "RELU", "SOFTPLUS", "GELU", "SIGN", "SWAP", "PLUS",
|
||||
"MINUS", "MULT", "DIV", "MOD", "POW", "GE", "GT", "LE", "LT",
|
||||
"EQ", "NE", "PIPE", "CONSTANT", "NUMBER", "VARIABLE", "WS" ]
|
||||
"FRACT", "RELU", "SOFTPLUS", "GELU", "SIGN", "MAP", "CONV",
|
||||
"SWAP", "PERM", "PLUS", "MINUS", "MULT", "DIV", "MOD", "POW",
|
||||
"GE", "GT", "LE", "LT", "EQ", "NE", "PIPE", "CONSTANT", "NUMBER",
|
||||
"VARIABLE", "WS" ]
|
||||
|
||||
ruleNames = [ "T__0", "T__1", "T__2", "SIN", "COS", "TAN", "ASIN", "ACOS",
|
||||
"ATAN", "ATAN2", "SINH", "COSH", "TANH", "ASINH", "ACOSH",
|
||||
"ATANH", "ABS", "SQRT", "LN", "LOG", "EXP", "SMIN", "SMAX",
|
||||
"TMIN", "TMAX", "TNORM", "SNORM", "FLOOR", "CEIL", "ROUND",
|
||||
"GAMMA", "POWE", "SIGM", "CLAMP", "SFFT", "SIFFT", "ANGL",
|
||||
"PRNT", "LERP", "STEP", "SMOOTHSTEP", "FRACT", "RELU",
|
||||
"SOFTPLUS", "GELU", "SIGN", "SWAP", "PLUS", "MINUS", "MULT",
|
||||
ruleNames = [ "T__0", "T__1", "T__2", "T__3", "T__4", "SIN", "COS",
|
||||
"TAN", "ASIN", "ACOS", "ATAN", "ATAN2", "SINH", "COSH",
|
||||
"TANH", "ASINH", "ACOSH", "ATANH", "ABS", "SQRT", "LN",
|
||||
"LOG", "EXP", "SMIN", "SMAX", "TMIN", "TMAX", "TNORM",
|
||||
"SNORM", "FLOOR", "CEIL", "ROUND", "GAMMA", "POWE", "SIGM",
|
||||
"CLAMP", "SFFT", "SIFFT", "ANGL", "PRNT", "LERP", "STEP",
|
||||
"SMOOTHSTEP", "FRACT", "RELU", "SOFTPLUS", "GELU", "SIGN",
|
||||
"MAP", "CONV", "SWAP", "PERM", "PLUS", "MINUS", "MULT",
|
||||
"DIV", "MOD", "POW", "GE", "GT", "LE", "LT", "EQ", "NE",
|
||||
"PIPE", "CONSTANT", "NUMBER", "VARIABLE", "WS" ]
|
||||
|
||||
|
||||
@@ -1,124 +1,134 @@
|
||||
T__0=1
|
||||
T__1=2
|
||||
T__2=3
|
||||
SIN=4
|
||||
COS=5
|
||||
TAN=6
|
||||
ASIN=7
|
||||
ACOS=8
|
||||
ATAN=9
|
||||
ATAN2=10
|
||||
SINH=11
|
||||
COSH=12
|
||||
TANH=13
|
||||
ASINH=14
|
||||
ACOSH=15
|
||||
ATANH=16
|
||||
ABS=17
|
||||
SQRT=18
|
||||
LN=19
|
||||
LOG=20
|
||||
EXP=21
|
||||
SMIN=22
|
||||
SMAX=23
|
||||
TMIN=24
|
||||
TMAX=25
|
||||
TNORM=26
|
||||
SNORM=27
|
||||
FLOOR=28
|
||||
CEIL=29
|
||||
ROUND=30
|
||||
GAMMA=31
|
||||
POWE=32
|
||||
SIGM=33
|
||||
CLAMP=34
|
||||
SFFT=35
|
||||
SIFFT=36
|
||||
ANGL=37
|
||||
PRNT=38
|
||||
LERP=39
|
||||
STEP=40
|
||||
SMOOTHSTEP=41
|
||||
FRACT=42
|
||||
RELU=43
|
||||
SOFTPLUS=44
|
||||
GELU=45
|
||||
SIGN=46
|
||||
SWAP=47
|
||||
PLUS=48
|
||||
MINUS=49
|
||||
MULT=50
|
||||
DIV=51
|
||||
MOD=52
|
||||
POW=53
|
||||
GE=54
|
||||
GT=55
|
||||
LE=56
|
||||
LT=57
|
||||
EQ=58
|
||||
NE=59
|
||||
PIPE=60
|
||||
CONSTANT=61
|
||||
NUMBER=62
|
||||
VARIABLE=63
|
||||
WS=64
|
||||
T__3=4
|
||||
T__4=5
|
||||
SIN=6
|
||||
COS=7
|
||||
TAN=8
|
||||
ASIN=9
|
||||
ACOS=10
|
||||
ATAN=11
|
||||
ATAN2=12
|
||||
SINH=13
|
||||
COSH=14
|
||||
TANH=15
|
||||
ASINH=16
|
||||
ACOSH=17
|
||||
ATANH=18
|
||||
ABS=19
|
||||
SQRT=20
|
||||
LN=21
|
||||
LOG=22
|
||||
EXP=23
|
||||
SMIN=24
|
||||
SMAX=25
|
||||
TMIN=26
|
||||
TMAX=27
|
||||
TNORM=28
|
||||
SNORM=29
|
||||
FLOOR=30
|
||||
CEIL=31
|
||||
ROUND=32
|
||||
GAMMA=33
|
||||
POWE=34
|
||||
SIGM=35
|
||||
CLAMP=36
|
||||
SFFT=37
|
||||
SIFFT=38
|
||||
ANGL=39
|
||||
PRNT=40
|
||||
LERP=41
|
||||
STEP=42
|
||||
SMOOTHSTEP=43
|
||||
FRACT=44
|
||||
RELU=45
|
||||
SOFTPLUS=46
|
||||
GELU=47
|
||||
SIGN=48
|
||||
MAP=49
|
||||
CONV=50
|
||||
SWAP=51
|
||||
PERM=52
|
||||
PLUS=53
|
||||
MINUS=54
|
||||
MULT=55
|
||||
DIV=56
|
||||
MOD=57
|
||||
POW=58
|
||||
GE=59
|
||||
GT=60
|
||||
LE=61
|
||||
LT=62
|
||||
EQ=63
|
||||
NE=64
|
||||
PIPE=65
|
||||
CONSTANT=66
|
||||
NUMBER=67
|
||||
VARIABLE=68
|
||||
WS=69
|
||||
'('=1
|
||||
')'=2
|
||||
','=3
|
||||
'sin'=4
|
||||
'cos'=5
|
||||
'tan'=6
|
||||
'asin'=7
|
||||
'acos'=8
|
||||
'atan'=9
|
||||
'atan2'=10
|
||||
'sinh'=11
|
||||
'cosh'=12
|
||||
'tanh'=13
|
||||
'asinh'=14
|
||||
'acosh'=15
|
||||
'atanh'=16
|
||||
'abs'=17
|
||||
'sqrt'=18
|
||||
'ln'=19
|
||||
'log'=20
|
||||
'exp'=21
|
||||
'smin'=22
|
||||
'smax'=23
|
||||
'tmin'=24
|
||||
'tmax'=25
|
||||
'tnorm'=26
|
||||
'snorm'=27
|
||||
'floor'=28
|
||||
'ceil'=29
|
||||
'round'=30
|
||||
'gamma'=31
|
||||
'pow'=32
|
||||
'sigm'=33
|
||||
'clamp'=34
|
||||
'fft'=35
|
||||
'ifft'=36
|
||||
'angle'=37
|
||||
'print'=38
|
||||
'lerp'=39
|
||||
'step'=40
|
||||
'smoothstep'=41
|
||||
'fract'=42
|
||||
'relu'=43
|
||||
'softplus'=44
|
||||
'gelu'=45
|
||||
'sign'=46
|
||||
'swap'=47
|
||||
'+'=48
|
||||
'-'=49
|
||||
'*'=50
|
||||
'/'=51
|
||||
'%'=52
|
||||
'^'=53
|
||||
'>='=54
|
||||
'>'=55
|
||||
'<='=56
|
||||
'<'=57
|
||||
'=='=58
|
||||
'!='=59
|
||||
'|'=60
|
||||
'['=3
|
||||
','=4
|
||||
']'=5
|
||||
'sin'=6
|
||||
'cos'=7
|
||||
'tan'=8
|
||||
'asin'=9
|
||||
'acos'=10
|
||||
'atan'=11
|
||||
'atan2'=12
|
||||
'sinh'=13
|
||||
'cosh'=14
|
||||
'tanh'=15
|
||||
'asinh'=16
|
||||
'acosh'=17
|
||||
'atanh'=18
|
||||
'abs'=19
|
||||
'sqrt'=20
|
||||
'ln'=21
|
||||
'log'=22
|
||||
'exp'=23
|
||||
'smin'=24
|
||||
'smax'=25
|
||||
'tmin'=26
|
||||
'tmax'=27
|
||||
'tnorm'=28
|
||||
'snorm'=29
|
||||
'floor'=30
|
||||
'ceil'=31
|
||||
'round'=32
|
||||
'gamma'=33
|
||||
'pow'=34
|
||||
'sigm'=35
|
||||
'clamp'=36
|
||||
'fft'=37
|
||||
'ifft'=38
|
||||
'angle'=39
|
||||
'print'=40
|
||||
'lerp'=41
|
||||
'step'=42
|
||||
'smoothstep'=43
|
||||
'fract'=44
|
||||
'relu'=45
|
||||
'softplus'=46
|
||||
'gelu'=47
|
||||
'sign'=48
|
||||
'map'=49
|
||||
'conv'=50
|
||||
'swap'=51
|
||||
'permute'=52
|
||||
'+'=53
|
||||
'-'=54
|
||||
'*'=55
|
||||
'/'=56
|
||||
'%'=57
|
||||
'^'=58
|
||||
'>='=59
|
||||
'>'=60
|
||||
'<='=61
|
||||
'<'=62
|
||||
'=='=63
|
||||
'!='=64
|
||||
'|'=65
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
# Generated from MathExpr.g4 by ANTLR 4.13.2
|
||||
from antlr4 import ParseTreeListener
|
||||
# Generated from ./MathExpr.g4 by ANTLR 4.13.2
|
||||
from antlr4 import *
|
||||
if "." in __name__:
|
||||
from .MathExprParser import MathExprParser
|
||||
else:
|
||||
@@ -215,6 +215,15 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#Func4Exp.
|
||||
def enterFunc4Exp(self, ctx:MathExprParser.Func4ExpContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#Func4Exp.
|
||||
def exitFunc4Exp(self, ctx:MathExprParser.Func4ExpContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#FuncNExp.
|
||||
def enterFuncNExp(self, ctx:MathExprParser.FuncNExpContext):
|
||||
pass
|
||||
@@ -260,6 +269,24 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#AbsExp.
|
||||
def enterAbsExp(self, ctx:MathExprParser.AbsExpContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#AbsExp.
|
||||
def exitAbsExp(self, ctx:MathExprParser.AbsExpContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#ListExp.
|
||||
def enterListExp(self, ctx:MathExprParser.ListExpContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#ListExp.
|
||||
def exitListExp(self, ctx:MathExprParser.ListExpContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SinFunc.
|
||||
def enterSinFunc(self, ctx:MathExprParser.SinFuncContext):
|
||||
pass
|
||||
@@ -512,6 +539,51 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#FractFunc.
|
||||
def enterFractFunc(self, ctx:MathExprParser.FractFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#FractFunc.
|
||||
def exitFractFunc(self, ctx:MathExprParser.FractFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#ReluFunc.
|
||||
def enterReluFunc(self, ctx:MathExprParser.ReluFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#ReluFunc.
|
||||
def exitReluFunc(self, ctx:MathExprParser.ReluFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SoftplusFunc.
|
||||
def enterSoftplusFunc(self, ctx:MathExprParser.SoftplusFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#SoftplusFunc.
|
||||
def exitSoftplusFunc(self, ctx:MathExprParser.SoftplusFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#GeluFunc.
|
||||
def enterGeluFunc(self, ctx:MathExprParser.GeluFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#GeluFunc.
|
||||
def exitGeluFunc(self, ctx:MathExprParser.GeluFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SignFunc.
|
||||
def enterSignFunc(self, ctx:MathExprParser.SignFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#SignFunc.
|
||||
def exitSignFunc(self, ctx:MathExprParser.SignFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#PowFunc.
|
||||
def enterPowFunc(self, ctx:MathExprParser.PowFuncContext):
|
||||
pass
|
||||
@@ -548,6 +620,15 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#StepFunc.
|
||||
def enterStepFunc(self, ctx:MathExprParser.StepFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#StepFunc.
|
||||
def exitStepFunc(self, ctx:MathExprParser.StepFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#ClampFunc.
|
||||
def enterClampFunc(self, ctx:MathExprParser.ClampFuncContext):
|
||||
pass
|
||||
@@ -557,6 +638,33 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#LerpFunc.
|
||||
def enterLerpFunc(self, ctx:MathExprParser.LerpFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#LerpFunc.
|
||||
def exitLerpFunc(self, ctx:MathExprParser.LerpFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SmoothstepFunc.
|
||||
def enterSmoothstepFunc(self, ctx:MathExprParser.SmoothstepFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#SmoothstepFunc.
|
||||
def exitSmoothstepFunc(self, ctx:MathExprParser.SmoothstepFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SwapFunc.
|
||||
def enterSwapFunc(self, ctx:MathExprParser.SwapFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#SwapFunc.
|
||||
def exitSwapFunc(self, ctx:MathExprParser.SwapFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#SMinFunc.
|
||||
def enterSMinFunc(self, ctx:MathExprParser.SMinFuncContext):
|
||||
pass
|
||||
@@ -575,5 +683,32 @@ class MathExprListener(ParseTreeListener):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#MapFunc.
|
||||
def enterMapFunc(self, ctx:MathExprParser.MapFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#MapFunc.
|
||||
def exitMapFunc(self, ctx:MathExprParser.MapFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#ConvFunc.
|
||||
def enterConvFunc(self, ctx:MathExprParser.ConvFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#ConvFunc.
|
||||
def exitConvFunc(self, ctx:MathExprParser.ConvFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
# Enter a parse tree produced by MathExprParser#PermuteFunc.
|
||||
def enterPermuteFunc(self, ctx:MathExprParser.PermuteFuncContext):
|
||||
pass
|
||||
|
||||
# Exit a parse tree produced by MathExprParser#PermuteFunc.
|
||||
def exitPermuteFunc(self, ctx:MathExprParser.PermuteFuncContext):
|
||||
pass
|
||||
|
||||
|
||||
|
||||
del MathExprParser
|
||||
+1401
-581
File diff suppressed because it is too large
Load Diff
@@ -159,6 +159,11 @@ class MathExprVisitor(ParseTreeVisitor):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
# Visit a parse tree produced by MathExprParser#ListExp.
|
||||
def visitListExp(self, ctx:MathExprParser.ListExpContext):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
# Visit a parse tree produced by MathExprParser#SinFunc.
|
||||
def visitSinFunc(self, ctx:MathExprParser.SinFuncContext):
|
||||
return self.visitChildren(ctx)
|
||||
@@ -379,5 +384,20 @@ class MathExprVisitor(ParseTreeVisitor):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
# Visit a parse tree produced by MathExprParser#MapFunc.
|
||||
def visitMapFunc(self, ctx:MathExprParser.MapFuncContext):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
# Visit a parse tree produced by MathExprParser#ConvFunc.
|
||||
def visitConvFunc(self, ctx:MathExprParser.ConvFuncContext):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
# Visit a parse tree produced by MathExprParser#PermuteFunc.
|
||||
def visitPermuteFunc(self, ctx:MathExprParser.PermuteFuncContext):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
|
||||
del MathExprParser
|
||||
@@ -1,7 +1,6 @@
|
||||
import torch
|
||||
import torch.special
|
||||
|
||||
from ..helper_functions import freq_to_time, time_to_freq
|
||||
from .MathExprVisitor import MathExprVisitor
|
||||
|
||||
class TensorEvalVisitor(MathExprVisitor):
|
||||
@@ -15,8 +14,66 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
else:
|
||||
self.device = device
|
||||
|
||||
def _fold_nd(self, tsr, spatial_dims):
|
||||
# Ensure tensor has rank (spatial_dims + 2)
|
||||
# 1. Unsqueeze if too low rank (add dummy channel at dim 1)
|
||||
original_shape = tsr.shape
|
||||
added_dims = 0
|
||||
target_rank = spatial_dims + 2
|
||||
|
||||
while tsr.ndim < target_rank:
|
||||
tsr = tsr.unsqueeze(1)
|
||||
added_dims += 1
|
||||
|
||||
# 2. Fold leading dimensions into batch if too high rank
|
||||
folded = False
|
||||
if tsr.ndim > target_rank:
|
||||
fold_count = tsr.ndim - target_rank
|
||||
new_batch = 1
|
||||
for i in range(fold_count + 1):
|
||||
new_batch *= tsr.shape[i]
|
||||
tsr = tsr.reshape(new_batch, *tsr.shape[fold_count+1:])
|
||||
folded = True
|
||||
else:
|
||||
folded = (added_dims > 0)
|
||||
|
||||
return tsr, original_shape, added_dims, folded
|
||||
|
||||
def _unfold_nd(self, tsr, original_shape, added_dims, folded):
|
||||
spatial_dims = tsr.ndim - 2
|
||||
# Restore folded batch if any
|
||||
if folded and added_dims == 0:
|
||||
target_fold_rank = len(original_shape) - (spatial_dims + 1)
|
||||
fold_dims = original_shape[:target_fold_rank]
|
||||
tsr = tsr.reshape(*fold_dims, *tsr.shape[1:])
|
||||
|
||||
# Squeeze added dims (dummy channels)
|
||||
for _ in range(added_dims):
|
||||
if tsr.ndim > len(original_shape) and tsr.shape[1] == 1:
|
||||
tsr = tsr.squeeze(1)
|
||||
|
||||
return tsr
|
||||
|
||||
def visitPermuteFunc(self, ctx):
|
||||
tsr = self.visit(ctx.expr(0))
|
||||
# permute(tsr, [d1, d2, ...]) or permute(tsr, d1, d2, ...)
|
||||
# Actually FuncN grammar was not used for permute but it could be.
|
||||
# Let's check the grammar. I added `PERM '(' expr ',' expr ')'` which is Func2 style.
|
||||
# But for permute we need a list.
|
||||
dims = self.visit(ctx.expr(1))
|
||||
if isinstance(dims, torch.Tensor):
|
||||
dims = dims.flatten().long().tolist()
|
||||
return tsr.permute(*dims)
|
||||
|
||||
def visitReshapeFunc(self, ctx):
|
||||
tsr = self.visit(ctx.expr(0))
|
||||
new_shape = self.visit(ctx.expr(1))
|
||||
if isinstance(new_shape, torch.Tensor):
|
||||
new_shape = new_shape.flatten().long().tolist()
|
||||
return tsr.reshape(*new_shape)
|
||||
|
||||
def visitNumberExp(self, ctx):
|
||||
return torch.full(self.shape, float(ctx.getText()), device=self.device)
|
||||
return torch.tensor(float(ctx.getText()), device=self.device)
|
||||
|
||||
def visitConstantExp(self, ctx):
|
||||
name = ctx.getText().lower()
|
||||
@@ -30,8 +87,10 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
name = ctx.getText()
|
||||
if name not in self.variables:
|
||||
raise ValueError(f"Variable '{name}' not found")
|
||||
if not isinstance(self.variables[name], torch.Tensor): return torch.full(self.shape, self.variables[name], device=self.device)
|
||||
return self.variables[name]
|
||||
val = self.variables[name]
|
||||
if not isinstance(val, torch.Tensor):
|
||||
return torch.tensor(float(val), device=self.device)
|
||||
return val
|
||||
|
||||
def visitParenExp(self, ctx):
|
||||
return self.visit(ctx.expr())
|
||||
@@ -116,7 +175,18 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
def visitAcoshFunc(self, ctx): return torch.acosh(self.visit(ctx.expr()))
|
||||
def visitAtanhFunc(self, ctx): return torch.atanh(self.visit(ctx.expr()))
|
||||
def visitAbsFunc(self, ctx): return torch.abs(self.visit(ctx.expr()))
|
||||
def visitNormExp(self, ctx): return torch.full(self.shape, torch.linalg.norm(self.visit(ctx.expr())).item(), device=self.device)
|
||||
def visitAbsExp(self, ctx): return torch.abs(self.visit(ctx.expr()))
|
||||
|
||||
def visitListExp(self, ctx):
|
||||
vals = [self.visit(e) for e in ctx.expr()]
|
||||
# If any are tensors with shape, stack them or create a tensor
|
||||
if all(v.ndim == 0 for v in vals):
|
||||
return torch.tensor([v.item() for v in vals], device=self.device)
|
||||
else:
|
||||
# Broadcasting stack
|
||||
return torch.stack(torch.broadcast_tensors(*vals), dim=0)
|
||||
|
||||
def visitNormExp(self, ctx): return torch.linalg.norm(self.visit(ctx.expr()))
|
||||
def visitSqrtFunc(self, ctx): return torch.sqrt(self.visit(ctx.expr()))
|
||||
def visitLnFunc(self, ctx): return torch.log(self.visit(ctx.expr()))
|
||||
def visitLogFunc(self, ctx): return torch.log10(self.visit(ctx.expr()))
|
||||
@@ -143,11 +213,17 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
return val
|
||||
|
||||
def visitSfftFunc(self, ctx):
|
||||
"""
|
||||
Spatial FFT - transforms the expression to frequency domain.
|
||||
Applies FFT on all dimensions of the tensor.
|
||||
"""
|
||||
old_vars = self.variables
|
||||
self.variables = self.spatial_variables.copy()
|
||||
try:
|
||||
val = self.visit(ctx.expr())
|
||||
return time_to_freq(val)
|
||||
# Apply FFT on all dimensions
|
||||
dims = tuple(range(val.ndim))
|
||||
return torch.fft.fftn(val, dim=dims)
|
||||
finally:
|
||||
self.variables = old_vars
|
||||
|
||||
@@ -177,50 +253,61 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
return torch.index_select(tsr, dim, indices)
|
||||
|
||||
def visitSifftFunc(self, ctx):
|
||||
"""
|
||||
Spatial IFFT - evaluates expression in frequency domain then transforms back.
|
||||
Provides frequency coordinate variables for each dimension:
|
||||
- Kx, Ky, Kz: frequency indices for last 3 dims (0-indexed)
|
||||
- K: isotropic frequency magnitude (Euclidean distance from DC)
|
||||
- Fx, Fy, Fz: size of each frequency dimension
|
||||
"""
|
||||
old_vars = self.variables
|
||||
# Switch to freq variables
|
||||
self.variables = self.variables.copy()
|
||||
device = self.spatial_variables['a'].device if 'a' in self.spatial_variables else torch.device('cpu')
|
||||
dims = range(2, len(self.shape))
|
||||
for d in dims:
|
||||
size_d = self.shape[d]
|
||||
device = self.device
|
||||
|
||||
ndim = len(self.shape)
|
||||
dim_names = ['x', 'y', 'z', 'w', 'v', 'u'] # Names for dims (from last to first)
|
||||
|
||||
# Generate frequency coordinates for each dimension
|
||||
k_components = []
|
||||
for i in range(ndim):
|
||||
dim_idx = ndim - 1 - i # Start from last dim
|
||||
size_d = self.shape[dim_idx]
|
||||
|
||||
# Create frequency indices (0-indexed, will be shifted for DC centering if needed)
|
||||
values = torch.arange(size_d, dtype=torch.float32, device=device)
|
||||
view_shape = [1] * len(self.shape)
|
||||
view_shape[d] = size_d
|
||||
view_shape = [1] * ndim
|
||||
view_shape[dim_idx] = size_d
|
||||
values = values.view(*view_shape).expand(*self.shape)
|
||||
|
||||
# Bind variables
|
||||
if d == 2:
|
||||
self.variables['K'] = values
|
||||
self.variables['F'] = size_d
|
||||
self.variables['Ky'] = values
|
||||
self.variables['Fy'] = size_d
|
||||
self.variables['frequency'] = self.variables['K'] # K is index
|
||||
self.variables['frequency_count'] = self.variables['F'] # F is scalar
|
||||
if d == 3:
|
||||
self.variables['Kx'] = values
|
||||
self.variables['Fx'] = size_d
|
||||
# Bind named variables (Kx, Ky, Kz for last 3 dims)
|
||||
if i < len(dim_names):
|
||||
var_name = f'K{dim_names[i]}'
|
||||
self.variables[var_name] = values
|
||||
self.variables[f'F{dim_names[i]}'] = float(size_d)
|
||||
|
||||
# Generic fallback
|
||||
self.variables[f'K_dim{d}'] = values
|
||||
self.variables[f'F_dim{d}'] = size_d
|
||||
# Generic fallback for all dims
|
||||
self.variables[f'K_dim{dim_idx}'] = values
|
||||
self.variables[f'F_dim{dim_idx}'] = float(size_d)
|
||||
|
||||
k_components.append(values)
|
||||
|
||||
# Calculate isotropic K (Euclidean distance from DC)
|
||||
# K = sqrt(K_2^2 + K_3^2 + ...)
|
||||
k_sq_sum = torch.zeros(self.shape, device=device)
|
||||
dims = range(2, len(self.shape))
|
||||
for d in dims:
|
||||
# Re-access the K variable for this dim (safe way)
|
||||
k_val = self.variables.get(f'K_dim{d}')
|
||||
if k_val is not None:
|
||||
k_sq_sum = torch.add(k_sq_sum, torch.pow(k_val, 2))
|
||||
for k_val in k_components:
|
||||
k_sq_sum = k_sq_sum + k_val ** 2
|
||||
|
||||
self.variables['K'] = torch.sqrt(k_sq_sum)
|
||||
self.variables['frequency'] = self.variables['K']
|
||||
|
||||
# Legacy aliases
|
||||
if 'Kx' in self.variables:
|
||||
self.variables['frequency_count'] = self.variables.get('Fx', 1.0)
|
||||
|
||||
try:
|
||||
val = self.visit(ctx.expr())
|
||||
return freq_to_time(val)
|
||||
# Apply IFFT on all dimensions
|
||||
dims = tuple(range(val.ndim))
|
||||
return torch.fft.ifftn(val, dim=dims).real
|
||||
finally:
|
||||
self.variables = old_vars
|
||||
|
||||
@@ -244,7 +331,6 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
|
||||
# Scale, bias and saturate x to 0..1 range
|
||||
t = torch.clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0)
|
||||
# Evaluate polynomial
|
||||
return t * t * (3.0 - 2.0 * t)
|
||||
|
||||
def visitStepFunc(self, ctx):
|
||||
@@ -255,9 +341,14 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
# N-argument functions
|
||||
def visitSMinFunc(self, ctx):
|
||||
args = [self.visit(e) for e in ctx.expr()]
|
||||
if len(args) == 1:
|
||||
return torch.min(args[0]) # Global min of single tensor
|
||||
return torch.min(torch.stack(torch.broadcast_tensors(*args)))
|
||||
|
||||
def visitSMaxFunc(self, ctx):
|
||||
args = [self.visit(e) for e in ctx.expr()]
|
||||
if len(args) == 1:
|
||||
return torch.max(args[0]) # Global max of single tensor
|
||||
return torch.max(torch.stack(torch.broadcast_tensors(*args)))
|
||||
|
||||
def visitTMinFunc(self, ctx):
|
||||
@@ -275,6 +366,187 @@ class TensorEvalVisitor(MathExprVisitor):
|
||||
return self.visitChildren(ctx)
|
||||
def visitFunc4Exp(self, ctx):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
def _normalize_coord(self, coord, size):
|
||||
if size > 1:
|
||||
return (coord / (size - 1)) * 2.0 - 1.0
|
||||
return torch.zeros_like(coord)
|
||||
|
||||
def visitMapFunc(self, ctx):
|
||||
tensor = self.visit(ctx.expr(0))
|
||||
coords = [self.visit(ctx.expr(i)) for i in range(1, len(ctx.expr()))]
|
||||
num_coords = len(coords)
|
||||
|
||||
if num_coords == 0:
|
||||
return tensor
|
||||
|
||||
is_1d = (num_coords == 1)
|
||||
if is_1d:
|
||||
tensor = tensor.unsqueeze(-2)
|
||||
zeros = torch.zeros_like(coords[0])
|
||||
coords.append(zeros)
|
||||
|
||||
working_num_coords = len(coords)
|
||||
|
||||
|
||||
spatial_in_shape = tensor.shape[-working_num_coords:]
|
||||
leading_shape = tensor.shape[:-working_num_coords]
|
||||
|
||||
batch_size = 1
|
||||
for s in leading_shape:
|
||||
batch_size *= s
|
||||
|
||||
if len(leading_shape) == 0:
|
||||
input_view = tensor.view(1, 1, *spatial_in_shape)
|
||||
else:
|
||||
input_view = tensor.view(batch_size, 1, *spatial_in_shape)
|
||||
|
||||
norm_coords_list = []
|
||||
for i, coord in enumerate(coords):
|
||||
dim_size = spatial_in_shape[-(i+1)]
|
||||
norm = self._normalize_coord(coord, dim_size)
|
||||
norm_coords_list.append(norm)
|
||||
|
||||
try:
|
||||
broadcasted_coords = torch.broadcast_tensors(*norm_coords_list)
|
||||
except RuntimeError:
|
||||
raise ValueError(f"map(): Coordinate shapes {[c.shape for c in coords]} cannot be broadcast together.")
|
||||
|
||||
grid = torch.stack(broadcasted_coords, dim=-1)
|
||||
|
||||
grid_spatial_shape = grid.shape[:-1]
|
||||
is_batched = False
|
||||
if len(leading_shape) > 0 and len(grid_spatial_shape) >= len(leading_shape):
|
||||
if grid_spatial_shape[:len(leading_shape)] == leading_shape:
|
||||
is_batched = True
|
||||
|
||||
if batch_size > 1 and not is_batched:
|
||||
grid = grid.expand(batch_size, *grid.shape)
|
||||
grid_spatial_shape = grid.shape[1:-1]
|
||||
elif is_batched:
|
||||
flatten_shape = (batch_size,) + grid_spatial_shape[len(leading_shape):] + (grid.shape[-1],)
|
||||
grid = grid.reshape(flatten_shape)
|
||||
grid_spatial_shape = flatten_shape[1:-1]
|
||||
|
||||
total_output_elements = grid.numel() // working_num_coords // batch_size
|
||||
|
||||
if working_num_coords == 2:
|
||||
grid_view = grid.reshape(batch_size, 1, total_output_elements, 2)
|
||||
output = torch.nn.functional.grid_sample(
|
||||
input_view, grid_view, mode='bilinear', padding_mode='zeros', align_corners=True
|
||||
)
|
||||
elif working_num_coords == 3:
|
||||
grid_view = grid.reshape(batch_size, 1, 1, total_output_elements, 3)
|
||||
output = torch.nn.functional.grid_sample(
|
||||
input_view, grid_view, mode='bilinear', padding_mode='zeros', align_corners=True
|
||||
)
|
||||
else:
|
||||
raise ValueError(f"map() supports up to 3 coordinate dimensions, got {num_coords} original coords.")
|
||||
|
||||
output = output.view(batch_size, total_output_elements)
|
||||
|
||||
final_shape = list(leading_shape) + list(grid_spatial_shape)
|
||||
output = output.view(final_shape)
|
||||
|
||||
return output
|
||||
|
||||
def _kernel_coords(self, size, device):
|
||||
half = size // 2
|
||||
return torch.arange(size, device=device).float() - half
|
||||
|
||||
def visitConvFunc(self, ctx):
|
||||
"""
|
||||
N-dimensional convolution.
|
||||
conv(tensor, kw, expr) - 1D conv on last dim
|
||||
conv(tensor, kw, kh, expr) - 2D conv on last 2 dims
|
||||
conv(tensor, kw, kh, kd, expr) - 3D conv on last 3 dims
|
||||
|
||||
Kernel expression uses kX, kY, kZ as centered coordinates.
|
||||
"""
|
||||
img = self.visit(ctx.expr(0))
|
||||
num_args = len(ctx.expr())
|
||||
|
||||
# Parse kernel sizes based on argument count
|
||||
if num_args == 3:
|
||||
kernel_sizes = [int(self.visit(ctx.expr(1)).flatten()[0].item())]
|
||||
k_expr_ctx = ctx.expr(2)
|
||||
elif num_args == 4:
|
||||
kernel_sizes = [
|
||||
int(self.visit(ctx.expr(1)).flatten()[0].item()),
|
||||
int(self.visit(ctx.expr(2)).flatten()[0].item())
|
||||
]
|
||||
k_expr_ctx = ctx.expr(3)
|
||||
elif num_args == 5:
|
||||
kernel_sizes = [
|
||||
int(self.visit(ctx.expr(1)).flatten()[0].item()),
|
||||
int(self.visit(ctx.expr(2)).flatten()[0].item()),
|
||||
int(self.visit(ctx.expr(3)).flatten()[0].item())
|
||||
]
|
||||
k_expr_ctx = ctx.expr(4)
|
||||
else:
|
||||
raise ValueError("conv() expects 3-5 arguments: (tensor, kw, [kh], [kd], kernel_expr|list)")
|
||||
|
||||
num_spatial = len(kernel_sizes)
|
||||
|
||||
kw = kernel_sizes[0]
|
||||
kh = kernel_sizes[1] if num_spatial >= 2 else 1
|
||||
kd = kernel_sizes[2] if num_spatial >= 3 else 1
|
||||
|
||||
kx = self._kernel_coords(kw, self.device).view(1, 1, kw).expand(kd, kh, kw)
|
||||
ky = self._kernel_coords(kh, self.device).view(1, kh, 1).expand(kd, kh, kw)
|
||||
kz = self._kernel_coords(kd, self.device).view(kd, 1, 1).expand(kd, kh, kw)
|
||||
|
||||
k_variables = self.variables.copy()
|
||||
k_variables.update({
|
||||
'kX': kx, 'kY': ky, 'kZ': kz,
|
||||
'kW': float(kw), 'kH': float(kh), 'kD': float(kd)
|
||||
})
|
||||
|
||||
k_visitor = TensorEvalVisitor(k_variables, (kd, kh, kw), device=self.device)
|
||||
kernel = k_visitor.visit(k_expr_ctx)
|
||||
|
||||
if kernel.numel() == 1:
|
||||
kernel = kernel.expand(kd, kh, kw).clone()
|
||||
elif kernel.numel() == kw * kh * kd:
|
||||
kernel = kernel.reshape(kd, kh, kw)
|
||||
|
||||
leading_shape = img.shape[:-num_spatial] if num_spatial < img.ndim else ()
|
||||
spatial_shape = img.shape[-num_spatial:]
|
||||
|
||||
combined_leading = 1
|
||||
for s in leading_shape:
|
||||
combined_leading *= s
|
||||
|
||||
if len(leading_shape) == 0:
|
||||
reshaped = img.unsqueeze(0).unsqueeze(0)
|
||||
else:
|
||||
reshaped = img.reshape(combined_leading, 1, *spatial_shape)
|
||||
|
||||
channels = reshaped.shape[1]
|
||||
|
||||
if num_spatial == 1:
|
||||
kernel_1d = kernel.flatten()[:kw]
|
||||
conv_kernel = kernel_1d.view(1, 1, kw).expand(channels, 1, kw)
|
||||
output = torch.nn.functional.conv1d(reshaped, conv_kernel, padding=kw//2, groups=channels)
|
||||
elif num_spatial == 2:
|
||||
kernel_2d = kernel[0] if kd > 1 else kernel.reshape(kh, kw)
|
||||
conv_kernel = kernel_2d.view(1, 1, kh, kw).expand(channels, 1, kh, kw)
|
||||
output = torch.nn.functional.conv2d(reshaped, conv_kernel, padding=(kh//2, kw//2), groups=channels)
|
||||
elif num_spatial == 3:
|
||||
conv_kernel = kernel.view(1, 1, kd, kh, kw).expand(channels, 1, kd, kh, kw)
|
||||
output = torch.nn.functional.conv3d(reshaped, conv_kernel, padding=(kd//2, kh//2, kw//2), groups=channels)
|
||||
else:
|
||||
raise ValueError(f"conv() supports up to 3 spatial dimensions, got {num_spatial}")
|
||||
|
||||
output = output.squeeze(1)
|
||||
if len(leading_shape) == 0:
|
||||
output = output.squeeze(0)
|
||||
else:
|
||||
final_shape = list(leading_shape) + list(output.shape[1:])
|
||||
output = output.reshape(final_shape)
|
||||
|
||||
return output
|
||||
|
||||
def visitAtomExp(self, ctx):
|
||||
return self.visitChildren(ctx)
|
||||
|
||||
|
||||
Reference in New Issue
Block a user