Annotation of /trunk/src/compiler/high-to-mid/probe.sml

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1 :	jhr	328	(* probe.sml
2 :			*
3 :			* COPYRIGHT (c) 2010 The Diderot Project (http://diderot.cs.uchicago.edu)
4 :			* All rights reserved.
5 :			*
6 :			* Expansion of probe operations in the HighIL to MidIL translation.
7 :			*)
8 :
9 :			structure Probe : sig
10 :
11 :	jhr	349	val expand : MidIL.var * FieldDef.field_def * MidIL.var -> MidIL.assign list
12 :	jhr	328
13 :			end = struct
14 :
15 :			structure SrcIL = HighIL
16 :	jhr	334	structure SrcOp = HighOps
17 :	jhr	328	structure DstIL = MidIL
18 :	jhr	334	structure DstOp = MidOps
19 :	jhr	349	structure DstV = DstIL.Var
20 :	jhr	328	structure VMap = SrcIL.Var.Map
21 :	jhr	349	structure IT = Shape
22 :	jhr	328
23 :			(* generate a new variable indexed by dimension *)
24 :			fun newVar_dim (prefix, d) =
25 :	jhr	349	DstV.new (prefix ^ Partials.axisToString(Partials.axis d))
26 :	jhr	328
27 :			fun assign (x, rator, args) = (x, DstIL.OP(rator, args))
28 :			fun cons (x, args) = (x, DstIL.CONS args)
29 :	jhr	334	fun realLit (x, i) = (x, DstIL.LIT(Literal.Float(FloatLit.fromInt i)))
30 :	jhr	328	fun intLit (x, i) = (x, DstIL.LIT(Literal.Int(IntInf.fromInt i)))
31 :
32 :	jhr	349	(* generate code for a evaluating a single element of a probe operation *)
33 :			fun probeElem {
34 :			dim, (* dimension of space *)
35 :			h, s, (* kernel h with support s *)
36 :			n, f, (* Dst vars for integer and fractional components of position *)
37 :			voxIter (* iterator over voxels *)
38 :			} (result, pdOp) = let
39 :			(* generate the variables that hold the convolution coefficients *)
40 :			val convCoeffs = let
41 :			val Partials.D l = pdOp
42 :			fun mkVar 0 = newVar_dim("h", dim)
43 :			| mkVar 1 = newVar_dim("dh", dim)
44 :			| mkVar i = newVar_dim(concat["d", Int.toString i, "h"], dim)
45 :			in
46 :			List.map mkVar l
47 :			end
48 :			(* for each dimension, we evaluate the kernel at the coordinates for that axis *)
49 :			val coeffCode = let
50 :			fun gen (x, k, (d, code)) = let
51 :			val d = d-1
52 :			val fd = newVar_dim ("f", d)
53 :			val a = DstV.new "a"
54 :			val tmps = List.tabulate(2*s, fn i => (DstV.new("t"^Int.toString i), s - (i+1)))
55 :			fun mkArg ((t, n), code) = let
56 :			val t' = DstV.new "r"
57 :			in
58 :			realLit (t', n) ::
59 :			assign (t, DstOp.Add DstOp.realTy, [fd, t']) ::
60 :			code
61 :			end
62 :			(* code in reverse order *)
63 :			val code =
64 :			assign(x, DstOp.EvalKernel(2*s, h, k), [a]) ::
65 :			assign(fd, DstOp.Select(dim, d), [f]) ::
66 :			cons(a, List.map #1 tmps) ::
67 :			(List.foldl mkArg [] tmps)
68 :			in
69 :			(d, List.rev code)
70 :			end
71 :			val Partials.D l = pdOp
72 :			in
73 :			#2 (ListPair.foldr gen (dim, []) (convCoeffs, l))
74 :			end
75 :			(* generate the reduction code *)
76 :			fun genReduce (result, [hh], IT.ND(_, kids), code) = let
77 :			(* the kids will all be leaves *)
78 :			val vv = DstV.new "vv"
79 :			fun getVox (IT.LF{vox, offsets}) = vox
80 :			in
81 :			cons (vv, List.map getVox kids) ::
82 :			assign (result, DstOp.Dot(2*s), [hh, vv]) :: code
83 :			end
84 :			| genReduce (result, hh::r, IT.ND(_, kids), code) = let
85 :			val tv = DstV.new "tv"
86 :			val tmps = List.tabulate(2*s, fn i => DstV.new("t"^Int.toString i))
87 :			fun lp ([], [], code) = code
88 :			| lp (t::ts, kid::kids, code) = genReduce(t, r, kid, lp(ts, kids, code))
89 :			val code = cons(tv, tmps) :: assign(result, DstOp.Dot(2*s), [hh, tv]) :: code
90 :			in
91 :			lp (tmps, kids, code)
92 :			end
93 :			val reduceCode = genReduce (result, convCoeffs, voxIter, [])
94 :			in
95 :			coeffCode @ reduceCode
96 :			end
97 :
98 :	jhr	328	(* generate code for probing the field (D^k (v * h)) at pos *)
99 :			fun probe (result, (k, v, h), pos) = let
100 :			val ImageInfo.ImgInfo{dim, ty=([], ty), ...} = v
101 :			val dimTy = DstOp.VecTy dim
102 :			val s = Kernel.support h
103 :			(* generate the transform code *)
104 :	jhr	349	val x = DstV.new "x" (* image-space position *)
105 :			val f = DstV.new "f"
106 :			val nd = DstV.new "nd"
107 :			val n = DstV.new "n"
108 :	jhr	328	val transformCode = [
109 :	jhr	334	assign(x, DstOp.Transform v, [pos]),
110 :			assign(nd, DstOp.Floor dim, [x]),
111 :			assign(f, DstOp.Sub dimTy, [x, nd]),
112 :	jhr	328	assign(n, DstOp.TruncToInt dim, [nd])
113 :			]
114 :	jhr	349	(* generate the shape of the differentiation tensor with variables representing
115 :			* the elements
116 :			*)
117 :			val diffIter = let
118 :			val partial = Partials.partial dim
119 :			fun f (i, axes) = Partials.axis i :: axes
120 :			fun g axes =
121 :			(DstV.new(String.concat("y" :: List.map Partials.axisToString axes)), partial axes)
122 :			in
123 :			IT.create (k-1, dim, fn _ => (), f, g, [])
124 :			end
125 :	jhr	328	(* generate code to load the voxel data *)
126 :			val voxIter = let
127 :			fun f (i, (offsets, id)) = (i - (s - 1) :: offsets, i::id)
128 :			fun g (offsets, id) = {
129 :			offsets = offsets,
130 :	jhr	349	vox = DstV.new(String.concat("v" :: List.map Int.toString id))
131 :	jhr	328	}
132 :			in
133 :	jhr	334	IT.create (dim-1, 2*s, fn _ => (), f, g, ([], []))
134 :	jhr	328	end
135 :			val loadCode = let
136 :			fun genCode ({offsets, vox}, code) = let
137 :			fun computeIndices (_, []) = ([], [])
138 :			| computeIndices (i, offset::offsets) = let
139 :			val index = newVar_dim("i", i)
140 :	jhr	349	val t1 = DstV.new "t1"
141 :			val t2 = DstV.new "t2"
142 :	jhr	328	val (indices, code) = computeIndices (i+1, offsets)
143 :			val code =
144 :			intLit(t1, offset) ::
145 :	jhr	349	assign(t2, DstOp.Select(2*s, i), [n]) ::
146 :	jhr	328	assign(index, DstOp.Add(DstOp.IntTy), [t1, t2]) ::
147 :			code
148 :			val indices = index::indices
149 :			in
150 :			(indices, code)
151 :			end
152 :			val (indices, indicesCode) = computeIndices (0, ~(s-1) :: offsets)
153 :	jhr	349	val a = DstV.new "a"
154 :	jhr	328	in
155 :	jhr	349	indicesCode @ [
156 :	jhr	334	assign(a, DstOp.VoxelAddress v, indices),
157 :	jhr	349	assign(vox, DstOp.LoadVoxels(ty, 2*s), [a])
158 :	jhr	328	] @ code
159 :			end
160 :			in
161 :			IT.foldr genCode [] voxIter
162 :			end
163 :	jhr	349	(* generate code to evaluate and construct the result tensor *)
164 :			val probeElem = probeElem {dim = dim, h = h, s = s, n = n, f = f, voxIter = voxIter}
165 :			fun genProbe (result, IT.ND(_, kids as (IT.LF _)::_), code) = let
166 :			(* the kids will all be leaves *)
167 :			fun genProbeCode (IT.LF arg, code) = probeElem arg @ code
168 :			fun getProbeVar (IT.LF(t, _)) = t
169 :			in
170 :			cons (result, List.map getProbeVar kids) :: List.foldr genProbeCode code kids
171 :			end
172 :			| genProbe (result, IT.ND(_, kids), code) = let
173 :			val tmps = List.tabulate(dim, fn i => DstV.new("t"^Int.toString i))
174 :			fun lp ([], [], code) = code
175 :			| lp (t::ts, kid::kids, code) = genProbe(t, kid, lp(ts, kids, code))
176 :			val code = cons(result, tmps) :: code
177 :			in
178 :			lp (tmps, kids, code)
179 :			end
180 :			val probeCode = genProbe (result, diffIter, [])
181 :	jhr	328	in
182 :	jhr	349	transformCode @ loadCode @ probeCode
183 :	jhr	328	end
184 :
185 :	jhr	349	fun expand (result, fld, pos) = let
186 :	jhr	328	fun expand' (result, FieldDef.CONV(k, v, h)) = let
187 :	jhr	349	val x = DstV.new "x"
188 :			val xformStm = (x, DstIL.OP(DstOp.Transform v, [pos]))
189 :	jhr	328	in
190 :			probe (result, (k, v, h), x) @ [xformStm]
191 :			end
192 :	jhr	349	(* should push negation down to probe operation
193 :	jhr	328	| expand' (result, FieldDef.NEG fld) = let
194 :	jhr	349	val r = DstV.new "value"
195 :	jhr	328	val stms = expand' (r, fld)
196 :	jhr	349	val ty = ??
197 :	jhr	328	in
198 :			expand' (r, fld) @ [assign(r, DstOp.Neg ty, [r])]
199 :			end
200 :	jhr	349	*)
201 :	jhr	328	| expand' (result, FieldDef.SUM(fld1, dlf2)) = raise Fail "expandInside: SUM"
202 :			in
203 :	jhr	349	List.rev (expand' (result, fld))
204 :	jhr	328	end
205 :
206 :			end

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