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1 :	jhr	180	(* translate-basis.sml
2 :			*
3 :	jhr	435	* COPYRIGHT (c) 2010 The Diderot Project (http://diderot-language.cs.uchicago.edu)
4 :	jhr	180	* All rights reserved.
5 :			*
6 :			* Translation for basis operations in Simple AST to HighIL code
7 :			*)
8 :
9 :			structure TranslateBasis : sig
10 :
11 :	jhr	189	(* translate(lhs, f, mvs, args) translates the application of f (specialized
12 :			* to the instantiated meta variables mvs) to a list of SSA assignments in
13 :			* reverse order.
14 :			*)
15 :	jhr	180	val translate : (HighIL.var * Var.var * Types.meta_var list * HighIL.var list)
16 :	jhr	2356	-> HighIL.assignment list
17 :	jhr	180
18 :			end = struct
19 :
20 :	jhr	194	structure BV = BasisVars
21 :	jhr	180	structure IL = HighIL
22 :	jhr	392	structure DstTy = HighILTypes
23 :	jhr	180	structure Op = HighOps
24 :	jhr	183	structure Ty = Types
25 :			structure TU = TypeUtil
26 :			structure MV = MetaVar
27 :	jhr	194	structure VTbl = Var.Tbl
28 :	jhr	180
29 :	cchiw	2383	structure EinOp= Operators
30 :			structure R=Rewrite
31 :			structure N=Normalize
32 :
33 :	jhr	2358	fun pruneTy tv = (case TU.prune(MV.toType tv)
34 :			of (ty as Ty.T_Var _) => raise Fail("unresolved type " ^ TU.toString ty)
35 :	jhr	1640	| ty => TranslateTy.tr ty
36 :			(* end case *))
37 :
38 :	jhr	197	fun pruneDim d = (case TU.pruneDim d
39 :	jhr	2356	of (Ty.DimConst n) => n
40 :			| d => raise Fail("unresolved dimension " ^ TU.dimToString d)
41 :			(* end case *))
42 :	jhr	197
43 :	jhr	407	fun pruneShape sv = (case TU.pruneShape(MV.toShape sv)
44 :	jhr	2356	of Ty.Shape dd => DstTy.tensorTy(List.map pruneDim dd)
45 :			| shp => raise Fail("unresolved shape " ^ TU.shapeToString shp)
46 :			(* end case *))
47 :	jhr	183
48 :	jhr	2358	fun dimVarToInt dv = pruneDim(MV.toDim dv)
49 :			fun dimVarToTensor dv = DstTy.tensorTy[dimVarToInt dv]
50 :	jhr	1116	fun dimVarToMatrix dv = let
51 :	jhr	2358	val d = dimVarToInt dv
52 :	jhr	2356	in
53 :			DstTy.tensorTy[d, d] (* square matrix type *)
54 :			end
55 :	jhr	407	fun shapeVarToTensor sv = pruneShape sv
56 :	jhr	197
57 :	jhr	1640	fun assign (y, rator, xs) = [IL.ASSGN(y, IL.OP(rator, xs))]
58 :	jhr	407
59 :	jhr	1640	fun basisFn name (y, [], xs) = [IL.ASSGN(y, IL.APPLY(name, xs))]
60 :	jhr	1116
61 :	jhr	407	fun simpleOp rator (y, [], xs) = assign (y, rator, xs)
62 :
63 :			fun tensorOp rator (y, [sv], xs) = assign (y, rator(shapeVarToTensor sv), xs)
64 :
65 :			fun vectorOp rator (y, [dv], xs) = assign (y, rator(dimVarToTensor dv), xs)
66 :
67 :	jhr	1116	fun kernel h (y, [], []) = assign(y, Op.Kernel(h, 0), [])
68 :	jhr	197
69 :	jhr	1640	(* utility functions for synthesizing eigenvector/eigenvalue code *)
70 :			fun eigenVec (rator, dim) = let
71 :			val ty = DstTy.SeqTy(DstTy.realTy, dim)
72 :			in
73 :			fn (y, _, [m]) => let
74 :			val v = IL.Var.new("evals", ty)
75 :			in
76 :			[IL.MASSGN([v, y], rator, [m])]
77 :			end
78 :			end
79 :			fun eigenVal (rator, dim) = let
80 :			val ty = DstTy.SeqTy(DstTy.vecTy dim, dim)
81 :			in
82 :			fn (y, _, [m]) => let
83 :			val v = IL.Var.new("evecs", ty)
84 :			in
85 :			[IL.MASSGN([y, v], rator, [m])]
86 :			end
87 :			end
88 :
89 :	cchiw	2386	fun createTenEin(operator, sv)=let shape=shapeVarToTensor
90 :			in S.transform(operator,[len(shape), shape]) end
91 :			fun createFldEin(operator, f)=S.transform(operator,[])
92 :	cchiw	2378
93 :
94 :	cchiw	2386	fun assignEin (y, rator, xs) = [IL.ASSGN(y, IL.EINAPP(R.evalEinApp(rator, xs)))]
95 :			fun simpleEinOp rator(y, [],xs)= assignEin (y,S.transform(rator,[]), xs)
96 :			fun tensorEinOp rator(y,[sv],xs)= assignEin(y,createTenEin(rator,sv),xs)
97 :	cchiw	2382
98 :	jhr	184	(* build a table that maps Basis variables to their translation functions *)
99 :	jhr	1640	val tbl : ((IL.var * Ty.meta_var list * IL.var list) -> IL.assignment list) VTbl.hash_table = let
100 :	jhr	2356	val tbl = VTbl.mkTable (128, Fail "Translate table")
101 :			val insert = VTbl.insert tbl
102 :			in
103 :			List.app insert [
104 :			(BV.lt_ii, simpleOp(Op.LT DstTy.IntTy)),
105 :			(BV.lt_rr, simpleOp(Op.LT DstTy.realTy)),
106 :			(BV.lte_ii, simpleOp(Op.LTE DstTy.IntTy)),
107 :			(BV.lte_rr, simpleOp(Op.LTE DstTy.realTy)),
108 :			(BV.gte_ii, simpleOp(Op.GTE DstTy.IntTy)),
109 :			(BV.gte_rr, simpleOp(Op.GTE(DstTy.realTy))),
110 :			(BV.gt_ii, simpleOp(Op.GT DstTy.IntTy)),
111 :			(BV.gt_rr, simpleOp(Op.GT(DstTy.realTy))),
112 :			(BV.equ_bb, simpleOp(Op.EQ DstTy.BoolTy)),
113 :			(BV.equ_ii, simpleOp(Op.EQ DstTy.IntTy)),
114 :			(BV.equ_ss, simpleOp(Op.EQ DstTy.StringTy)),
115 :			(BV.equ_rr, simpleOp(Op.EQ(DstTy.realTy))),
116 :			(BV.neq_bb, simpleOp(Op.NEQ DstTy.BoolTy)),
117 :			(BV.neq_ii, simpleOp(Op.NEQ DstTy.IntTy)),
118 :			(BV.neq_ss, simpleOp(Op.NEQ DstTy.StringTy)),
119 :			(BV.neq_rr, simpleOp(Op.NEQ(DstTy.realTy))),
120 :	cchiw	2378
121 :			(* Changed*)
122 :
123 :	cchiw	2386	(BV.add_ii, simpleEinOp(EinOp.addScalars)),
124 :			(BV.add_tt, tensorEinOp(EinOp.addTensors)),
125 :	cchiw	2378
126 :	cchiw	2383
127 :	cchiw	2380	(BV.add_ff, fn (y, _, [f, g])
128 :			=>assignEin(y, createFldEin(EinOp.addField,f ), [f, g])),
129 :			(BV.add_fr, fn (y, _, [f, s])
130 :			=> assignEin(y, createFldEin(EinOp.addTenField,f ), [f, s])),
131 :			(BV.add_rf, fn (y, _, [s, f])
132 :			=> assignEin(y, createFldEin(EinOp.addTenField,f ), [f, s])),
133 :	cchiw	2378
134 :	cchiw	2386	(BV.sub_ii, simpleEinOp(EinOp.subScalars)), (*DstTy.IntTy*)
135 :			(BV.sub_tt, tensorEinOp(EinOp.subTensor)),
136 :	cchiw	2380	(BV.sub_ff, fn (y, _, [f, g])
137 :			=> assignEin(y, createFldEin(EinOp.subField,f), [f, g])),
138 :
139 :	cchiw	2379	(* UnChanged*)
140 :	jhr	2358	(BV.sub_fr, fn (y, _, [f, s]) => let
141 :			val s' = IL.Var.copy s
142 :			in [
143 :			IL.ASSGN(s', IL.OP(Op.Neg DstTy.realTy, [s])),
144 :			IL.ASSGN(y, IL.OP(Op.OffsetField, [f, s']))
145 :			] end),
146 :	cchiw	2378
147 :	jhr	2358	(BV.sub_rf, fn (y, _, [s, f]) => let
148 :			val f' = IL.Var.copy f
149 :			in [
150 :			IL.ASSGN(f', IL.OP(Op.NegField, [f])),
151 :			IL.ASSGN(y, IL.OP(Op.OffsetField, [f', s]))
152 :			] end),
153 :	cchiw	2378	(* Changed*)
154 :	cchiw	2386	(BV.mul_ii, simpleEinOp(EinOp.scalarxscalar)),
155 :			(BV.mul_rr, simpleEinOp(EinOp.scalarxscalar)),
156 :			(BV.mul_rt, tensorEinOp(EinOp.scaleTensor)), (*tensorOp Op.Scale),*)
157 :	cchiw	2378
158 :	cchiw	2380	(BV.mul_tr, fn (y, sv, [t, r])
159 :	cchiw	2381	=>assignEin(y,createTenEin(EinOp.scaleTensor, sv), [r,t])
160 :	cchiw	2380
161 :
162 :	cchiw	2386	(BV.mul_rf, fn (y, _, [s, f])
163 :			=> assignEin(y, createFldEin(EinOp.scaleField,f), [s, f])),
164 :			(BV.mul_fr, fn (y, _, [f, s])
165 :			=> assignEin(y, createFldEin(EinOp.scaleField,f), [s, f])),
166 :	cchiw	2380
167 :	cchiw	2378	(* UnChanged*)
168 :
169 :	jhr	2356	(BV.div_ii, simpleOp(Op.Div DstTy.IntTy)),
170 :			(BV.div_rr, simpleOp(Op.Div DstTy.realTy)),
171 :			(BV.div_tr, fn (y, [sv], [x, s]) => let
172 :			val one = IL.Var.new("one", DstTy.realTy)
173 :			val s' = IL.Var.new("sInv", DstTy.realTy)
174 :			in [
175 :			IL.ASSGN(one, IL.LIT(Literal.Float(FloatLit.one))),
176 :			IL.ASSGN(s', IL.OP(Op.Div DstTy.realTy, [one, s])),
177 :			IL.ASSGN(y, IL.OP(Op.Scale(shapeVarToTensor sv), [s', x]))
178 :			] end),
179 :			(BV.div_fr, fn (y, _, [f, s]) => let
180 :			val one = IL.Var.new("one", DstTy.realTy)
181 :			val s' = IL.Var.new("sInv", DstTy.realTy)
182 :			in [
183 :			IL.ASSGN(one, IL.LIT(Literal.Float(FloatLit.one))),
184 :			IL.ASSGN(s', IL.OP(Op.Div DstTy.realTy, [one, s])),
185 :			IL.ASSGN(y, IL.OP(Op.ScaleField, [s', f]))
186 :			] end),
187 :			(BV.exp_ri, simpleOp(Op.Power)),
188 :			(BV.exp_rr, basisFn MathFuns.pow),
189 :	cchiw	2378
190 :	cchiw	2379	(* Changed*)
191 :	cchiw	2384	(*Note curl is in Ein and does not need to normalize.*)
192 :	cchiw	2379	(BV.curl2D, fn (y, _, xs) => assignEin(y, EinOp.Curl2d, xs)),
193 :			(BV.curl3D, fn (y, _, xs) => assignEin(y, EinOp.Curl3d, xs)),
194 :	cchiw	2378
195 :
196 :	cchiw	2379	(* UnChanged*)
197 :	jhr	2356	(BV.convolve_vk, fn (y, [_, dv, _], xs) =>
198 :			assign(y, Op.Field(pruneDim(MV.toDim dv)), xs)),
199 :			(BV.convolve_kv, fn (y, [_, dv, _], [k, v]) =>
200 :			assign(y, Op.Field(pruneDim(MV.toDim dv)), [v, k])),
201 :	cchiw	2379
202 :
203 :	jhr	2356	(BV.neg_i, simpleOp(Op.Neg DstTy.IntTy)),
204 :			(BV.neg_t, tensorOp Op.Neg),
205 :			(BV.neg_f, fn (y, _, xs) => assign(y, Op.NegField, xs)),
206 :			(BV.op_probe, fn (y, [_, dv, sv], xs) =>
207 :			assign(y, Op.Probe(dimVarToTensor dv, shapeVarToTensor sv), xs)),
208 :	cchiw	2379
209 :	cchiw	2381	(* Changed*)
210 :	cchiw	2384	(*Um what do I give as the argument to Normalize?*)
211 :	cchiw	2381	(BV.op_D, fn (y, _, xs) => assignEin(y, createFldEin(EinOp.Grad,xs), xs)),
212 :			(BV.op_Dotimes, fn (y, _, xs) => assignEin(y, createFldEin(EinOp.Divergence,xs), xs)),
213 :	cchiw	2379
214 :			(* UnChanged*)
215 :	jhr	2356	(BV.op_norm, fn (y, [sv], xs) => (case shapeVarToTensor sv
216 :			of DstTy.TensorTy[] => assign(y, Op.Abs DstTy.realTy, xs)
217 :			| ty => assign(y, Op.Norm ty, xs)
218 :			(* end case *))),
219 :			(BV.op_not, simpleOp Op.Not),
220 :	cchiw	2379
221 :			(* Changed*)
222 :	cchiw	2381	(BV.op_cross, fn(y, _ , xs )=> assignEin(y,EinOp.crossProductE ,xs)
223 :			(BV.op_outer, fn (y, [dv1, dv2], xs) => let
224 :	jhr	2356	val d1 = pruneDim(MV.toDim dv1)
225 :			val d2 = pruneDim(MV.toDim dv2)
226 :	cchiw	2381	in assignEin( y, S.transform(EinOp.outerProduct,[(length(d1),d1), (length(d2),d2)]),xs)
227 :			end
228 :			(*Here, d1, d2 is an int, but we want a list.*)
229 :	cchiw	2379
230 :	cchiw	2381	(* Assuming dd1, ddd2 are lists of dimensions*)
231 :	cchiw	2380	(BV.op_inner, fn (y, [sh1, sh2, _], xs) => let
232 :	jhr	2356	val ty1 as DstTy.TensorTy dd1 = pruneShape sh1
233 :			val ty2 as DstTy.TensorTy dd2 = pruneShape sh2
234 :	cchiw	2380	val ilist= [(length(dd1)-1, List.take(dd1, length(dd1)-1) ) ,
235 :	cchiw	2381	( length(dd2)-1, tl(dd2)),
236 :			( 0, [hd(dd2)]) ]
237 :	cchiw	2380	in assignEin(y, S.tranform(EinOp.innerProduct, ilist),xs) end),
238 :
239 :
240 :			(BV.op_colon, fn (y, [sh1, sh2, _], xs) => let
241 :	jhr	2358	val ty1 as DstTy.TensorTy dd1 = pruneShape sh1
242 :			val ty2 as DstTy.TensorTy dd2 = pruneShape sh2
243 :	cchiw	2380	val ilist= [ (length(dd1)-2 , List.take(q, length(q)-2)) ,
244 :	cchiw	2381	( length(dd2)-2 , tl(tl(dd2))),
245 :			(_, List.take(dd2,2))]
246 :	cchiw	2380	in assignEin(y, S.transform(EinOp.doubleDot, ilist),xs) end),
247 :
248 :
249 :	cchiw	2379	(* UnChanged*)
250 :	jhr	2356	(BV.fn_inside, fn (y, [_, dv, _], xs) =>
251 :			assign(y, Op.Inside(pruneDim(MV.toDim dv)), xs)),
252 :			(BV.clamp_rrr, simpleOp (Op.Clamp DstTy.realTy)),
253 :			(BV.clamp_vvv, vectorOp Op.Clamp),
254 :			(BV.lerp3, tensorOp Op.Lerp),
255 :			(BV.lerp5, fn (y, [sv], [a, b, x0, x, x1]) => let
256 :			val t1 = IL.Var.new("t1", DstTy.realTy)
257 :			val t2 = IL.Var.new("t2", DstTy.realTy)
258 :			val t3 = IL.Var.new("t3", DstTy.realTy)
259 :			in [
260 :			IL.ASSGN(t1, IL.OP(Op.Sub DstTy.realTy, [x, x0])),
261 :			IL.ASSGN(t2, IL.OP(Op.Sub DstTy.realTy, [x1, x0])),
262 :			IL.ASSGN(t3, IL.OP(Op.Div DstTy.realTy, [t1, t2])),
263 :			IL.ASSGN(y, IL.OP(Op.Lerp(shapeVarToTensor sv), [a, b, t3]))
264 :			] end),
265 :			(BV.evals2x2, eigenVal (Op.Eigen2x2, 2)),
266 :			(BV.evals3x3, eigenVal (Op.Eigen3x3, 3)),
267 :			(BV.evecs2x2, eigenVec (Op.Eigen2x2, 2)),
268 :			(BV.evecs3x3, eigenVec (Op.Eigen3x3, 3)),
269 :			(BV.fn_max, simpleOp Op.Max),
270 :			(BV.fn_min, simpleOp Op.Min),
271 :			(BV.fn_modulate, vectorOp Op.Mul),
272 :			(BV.fn_normalize, vectorOp Op.Normalize),
273 :			(BV.fn_principleEvec, vectorOp Op.PrincipleEvec),
274 :	cchiw	2379
275 :			(* Changed*)
276 :	cchiw	2381	(BV.fn_trace, fn (y, [dv], xs) => (let
277 :			val i=pruneDim(MV.toDim dv) (* (dimVarToMatrix dv)*)
278 :			(*we need i to be the dimension n of an n xn matrix*)
279 :			in assignEin(y,S.transform(EinOp.trace, [1,i]),xs) end)
280 :	cchiw	2379
281 :			(* UnChanged*)
282 :			(BV.fn_transpose, fn (y, [dv1, dv2], xs) =>
283 :	jhr	2358	assign(y, Op.Transpose(dimVarToInt dv1, dimVarToInt dv2), xs)),
284 :	jhr	2356	(BV.kn_bspln3, kernel Kernel.bspln3),
285 :			(BV.kn_bspln5, kernel Kernel.bspln5),
286 :			(BV.kn_ctmr, kernel Kernel.ctmr),
287 :			(BV.kn_c2ctmr, kernel Kernel.ctmr),
288 :	jhr	2358	(BV.kn_c4hexic, kernel Kernel.c4hexic),
289 :	jhr	2356	(BV.kn_tent, kernel Kernel.tent),
290 :			(BV.kn_c1tent, kernel Kernel.tent),
291 :			(BV.i2r, simpleOp Op.IntToReal),
292 :	cchiw	2379
293 :			(* Changed*)
294 :	cchiw	2381	(BV.identity, fn (y, [dv], []) =>(let
295 :			val i=pruneDim(MV.toDim dv)
296 :			(*we need i to be the dimension n of an n xn matrix*)
297 :			in assignEin(y, S.transform(EinOp.identity,[(1,i),(1,i)]),[]) end)),
298 :	cchiw	2380
299 :	cchiw	2379	(* UnChanged*)
300 :	jhr	2356	(BV.zero, fn (y, [sv], []) =>
301 :			assign(y, Op.Zero(shapeVarToTensor sv), [])),
302 :	jhr	1640	(BV.subscript, fn (y, [tv, dv], args) =>
303 :			assign(y,
304 :	jhr	2358	Op.SeqSub(DstTy.SeqTy(pruneTy tv, pruneDim(MV.toDim dv))),
305 :	jhr	1640	args))
306 :	jhr	2356	];
307 :			(* add C math functions *)
308 :			List.app (fn (n, x) => insert(x, basisFn n)) BV.mathFns;
309 :			tbl
310 :			end
311 :	jhr	180
312 :	jhr	194	fun translate (y, f, mvs, xs) = (case VTbl.find tbl f
313 :	jhr	2356	of SOME transFn => transFn(y, mvs, xs)
314 :			| NONE => raise Fail("TranslateBasis.translate: unknown basis function " ^ Var.uniqueNameOf f)
315 :			(* end case *))
316 :	jhr	1116	handle ex => (print(concat["translate (", IL.Var.toString y, ", ",
317 :			Var.uniqueNameOf f, ", ...)\n"]); raise ex)
318 :	jhr	180
319 :			end

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