removing unused codes
This commit is contained in:
ignis
parent
f7a88aa72a
commit
3d3917a169
2 changed files with 4 additions and 572 deletions
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@ -1,19 +1,9 @@
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#
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# This example shows how to write a basic calculator with variables.
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#
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from lark import Lark, Visitor, Transformer, v_args, Token
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from post import *
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try:
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input = raw_input # For Python2 compatibility
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except NameError:
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pass
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calc_grammar = """
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?varlist: "[" [NAME ("," NAME)*] "]"
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@ -66,548 +56,6 @@ calc_grammar = """
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%ignore WS
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"""
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real_array_decl = "real*8, allocatable, dimension(:,:,:) :: {}"
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real_array_alloc = "allocate({0}(nxp,nyp,nzp), stat=ierr) ; {0} = 0."
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avg_array_decl = "real*8, allocatable, dimension(:) :: {}"
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avg_array_alloc = "allocate({0}(nxp), stat=ierr) ; {0} = 0."
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real_array_free = "deallocate({})"
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real_array_loop = """
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do k = 1, nzp
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do j = 1, nyp
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do i = 1, nxp
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{0[0]}(i,j,k) = {0[1]}
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end do
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end do
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end do
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"""
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avg_array_sum = """
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do k = 1, nzp
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do j = 1, nyp
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do i = 1, nxp
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{0}(i) = {0}(i) + {1} {2}
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end do
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end do
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end do
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"""
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avg_array_write = '''
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integer :: i
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open (200, file="qEdge_X.dat")
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write (200,*) output_header
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do i=1,nxp
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write (200,'({0}e20.10)') real(i)*hxp, {1}
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end do
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close (200)
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'''
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avg_array_divide = """
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call MPI_ALLREDUCE(MPI_IN_PLACE, {0}, nxp, MPI_REAL8, MPI_SUM, MPI_COMM_TASK, mpi_err)
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{0} = {0} / denum {1}
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"""
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real_array_diff = "call {0[0]} ( {0[0]}_{0[1]}, {0[1]} )"
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class FortranCode:
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def __init__ (self, exp):
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self.exp = exp
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def __repr__ (self):
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return self.exp
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'''
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def __add__ (self, other):
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self.exp = "( {} + {} )".format(self.exp, other.exp)
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return self
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def __sub__ (self, other):
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self.exp = "( {} - {} )".format(self.exp, other.exp)
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return self
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'''
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@v_args(inline=True) # Affects the signatures of the methods
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class ToFortran(Transformer):
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def __init__(self, primary_set):
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self.primary = primary_set
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self.derivatives = {}
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self.dependency = {}
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self.codes = {}
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def number(self, numeral):
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return (FortranCode(str(float(numeral))), [])
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def env(self, name):
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return (FortranCode(name.value), [])
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def var(self, name):
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return (FortranCode(name + "(i,j,k)"),
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[name.value] if name.value not in self.primary else [])
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def fluc(self, name):
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fmt = "({0}(i,j,k) - {{0}}avg_{0}(i))"
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return (FortranCode(fmt.format(name)),
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[name.value] if name.value not in self.primary else [])
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def dnx (self, partial, b):
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signature = "{}_{}".format(partial.data, b)
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fcode = FortranCode(signature + "(i,j,k)")
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self.derivatives[signature] = (partial.data, b.value)
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self.dependency[signature] = [b.value]
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self.codes[signature] = {
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"decl" : real_array_decl.format(signature),
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"alloc" : real_array_alloc.format(signature),
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"free" : real_array_free.format(signature),
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"calc" : real_array_diff.format((partial.data, b)),
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"avg" : "",
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}
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return (fcode, [signature])
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def icall (self, a, (b, dep)):
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fcode = "({0})".format(b)
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if a.data == "sqr":
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fcode = "(({0})*({0}))".format(b)
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elif a.data == "pow3":
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fcode = "(({0})*({0})*({0}))".format(b)
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return (fcode, dep)
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def fcall (self, a, (b, dep)):
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fcode = "( {} ( {} ) )".format(a, b)
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return (fcode, dep)
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def neg(self, (b, dep)):
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fcode = "( - {} )".format(b)
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return (fcode, dep)
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def add(self, (a, adep), (b, bdep)):
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fcode = "( {} + {} )".format(a, b)
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return (fcode, adep + bdep)
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def sub(self, (a, adep), (b, bdep)):
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fcode = "( {} - {} )".format(a, b)
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return (fcode, adep + bdep)
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def mul(self, (a, adep), (b, bdep)):
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fcode = "( {} * {} )".format(a, b)
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return (fcode, adep + bdep)
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def div(self, (a, adep), (b, bdep)):
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fcode = "( {} / {} )".format(a, b)
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return (fcode, adep + bdep)
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log = lambda self : "log"
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exp = lambda self : "exp"
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sqrt = lambda self : "sqrt"
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abs = lambda self : "dabs"
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rxn_rate = lambda self : "rxn_rate"
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class CheckPass(Visitor):
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def __init__(self):
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self.hasFluc = False
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@classmethod
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def check(cls, tree):
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self = cls()
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return self(tree)
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def __call__(self, tree):
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self.visit(tree)
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return self.hasFluc
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def fluc(self, tree):
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self.hasFluc = True
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@v_args(inline=True) # Affects the signatures of the methods
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class CalculateTree(Transformer):
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def __init__(self):
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self.primary = []
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self.derived = {}
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self.averaged = {}
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self.averages = []
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self.derivatives = {}
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self.dependency = {}
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self.fluctuation = {}
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self.definitions = {}
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self.exp_parser = ToFortran([])
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self.codes = {}
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def varlist(self, *args):
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for arg in args:
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self.primary.append(arg.value)
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self.dependency[arg.value] = []
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self.fluctuation[arg.value] = False
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return ""
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def assign_var(self, *args):
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vname, vdef = args
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self.definitions[vname.value] = vdef
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code, dep = self.exp_parser.transform(vdef)
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self.dependency[vname.value] = dep
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self.fluctuation[vname.value] = "{0}" in code
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self.codes[vname.value] = {
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"decl" : real_array_decl.format(vname.value),
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"alloc" : real_array_alloc.format(vname.value),
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"free" : real_array_free.format(vname.value),
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"calc" : real_array_loop.format((vname.value, code)),
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"avg" : "",
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}
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return ""
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def assign_avg_var(self, *args):
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weight = args[0]
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vlist = args[1:]
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self.averaged[str(weight)] = map(str, vlist)
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w = str(weight)
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for v in vlist:
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avg_var = ( "" if w == str(None) else w + "_" ) + "avg_" + v
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self.averages.append(avg_var)
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self.fluctuation[avg_var] = False
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var = str(v)
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if self.has_fluc()[str(v)]:
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if w == str(None):
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var = var + "_"
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self.dependency[avg_var] = [str(v)+"_"]
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self.dependency[str(v)+"_"] = self.dependency[str(v)]
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self.fluctuation[str(v)+"_"] = True
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self.codes[var] = {}
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for k,val in self.codes[str(v)].items():
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self.codes[var][k] = val.replace(str(v), var)
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self.codes[var]["calc"] = self.codes[var]["calc"].format("")
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else:
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var = var + "_" + w
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self.dependency[avg_var] = [str(v)+"_"+w, w]
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self.dependency[str(v)+"_"+w] = self.dependency[str(v)]
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self.fluctuation[str(v)+"_"+w] = True
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self.codes[var] = {}
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for k,val in self.codes[str(v)].items():
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self.codes[var][k] = val.replace(str(v), var)
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self.codes[var]["calc"] = self.codes[var]["calc"].format(w+"_")
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else:
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self.dependency[avg_var] = [var] + ( [] if w == str(None) else [w] )
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wfmt = "* {}(i,j,k)"
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pWeight = (wfmt.format(w) if w != str(None) else "")
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meanw = "/ avg_{}"
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dWeight = (meanw.format(w) if w != str(None) else "")
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self.codes[avg_var] = {
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"decl" : avg_array_decl.format(avg_var),
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"alloc" : avg_array_alloc.format(avg_var),
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"free" : real_array_free.format(avg_var),
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"calc" : avg_array_sum.format(avg_var, var+"(i,j,k)", pWeight),
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"avg" : avg_array_divide.format(avg_var, dWeight)
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}
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return ""
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def avg(self, *args):
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try:
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return args[0]
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except IndexError:
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return None
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def dep_graph (self):
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return dict(
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self.dependency.items()
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+ self.exp_parser.dependency.items()
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)
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def has_fluc (self):
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return dict(
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self.fluctuation.items()
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+ [(k, False) for k, v in self.exp_parser.dependency.items()]
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)
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import sys
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import pprint
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pp = pprint.PrettyPrinter()
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class FortranProgram:
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def __init__ (self, terms_input):
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self.tree_parser = Lark(calc_grammar, parser='lalr' )
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self.parser = CalculateTree()
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tree = self.tree_parser.parse(terms_input)
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self.tree = tree
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self.parser.transform(tree)
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dg = self.parser.dep_graph()
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fd = self.parser.has_fluc()
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def isFluc (a):
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for x in dg[a]:
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fd[a] = fd[a] or isFluc(x)
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return fd[a]
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average_names = self.parser.averages
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self.pass1avg = filter(lambda x: not isFluc(x), average_names)
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self.pass2avg = filter(isFluc, average_names)
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pass1var = filter(lambda x: not isFluc(x), average_names)
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pass2var = filter(isFluc, average_names)
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def dep_set (varset):
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c = set([])
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for var in varset:
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c.update(dg[var])
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return c
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def dep_closer (s):
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c = set(s)
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while len(dep_set(s)) > 0:
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s = dep_set(s)
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c.update(s)
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return c
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self.pass1set = dep_closer(set(pass1var)) - set(self.parser.primary)
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self.pass2set = dep_closer(set(pass2var)) - set(self.parser.primary)
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self.pass1list = self.sort_vars(dg, self.pass1set)
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self.pass2list = self.sort_vars(dg, self.pass2set)
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self.codes = dict(self.parser.codes.items() + self.parser.exp_parser.codes.items())
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def sort_vars (self, dependency, group):
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order = []
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remain = set(group)
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while len(remain) > 0:
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for v in remain:
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if len(set(dependency[v]) & remain) == 0:
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order.append(v)
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remain.remove(v)
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break
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return order
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def print_program (self):
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import StringIO
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output = StringIO.StringIO()
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output.write('First line.\n')
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print >>output, 'Second line.'
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decl = StringIO.StringIO()
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alloc = StringIO.StringIO()
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free = StringIO.StringIO()
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calc1 = StringIO.StringIO()
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avg1 = StringIO.StringIO()
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calc2 = StringIO.StringIO()
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avg2 = StringIO.StringIO()
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wres = StringIO.StringIO()
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hfmt = 'character (len = *), parameter :: output_header="{}"'
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print >>decl, hfmt.format(" ".join(["x"] + self.parser.averages))
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avgarr = "{}(i)"
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print >>wres, avg_array_write.format(
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len(self.parser.averages)+1,
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", ".join(map(avgarr.format, self.parser.averages))
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)
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for var in self.pass1set | self.pass2set:
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print >>decl, self.codes[var]["decl"]
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for var in self.pass1set | self.pass2set:
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print >>alloc, self.codes[var]["alloc"]
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for var in self.pass1set | self.pass2set:
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print >>free, self.codes[var]["free"]
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for var in self.pass1list :
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print >>calc1, self.codes[var]["calc"]
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for var in self.pass1avg :
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print >>avg1, self.codes[var]["avg"]
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for var in self.pass2list:
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print >>calc2, self.codes[var]["calc"]
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for var in self.pass2avg:
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print >>avg2, self.codes[var]["avg"]
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md = {}
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md["module_name"] = "terms"
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md["module_data"] = decl.getvalue()
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md["module_init"] = alloc.getvalue()
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md["module_finalize"] = free.getvalue()
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md["module_pass1"] = calc1.getvalue()
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md["module_pass1_avg"] = avg1.getvalue()
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md["module_pass2"] = calc2.getvalue()
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md["module_pass2_avg"] = avg2.getvalue()
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md["module_write_result"] = wres.getvalue()
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return md
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def print_graph (self):
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dg = self.parser.dep_graph()
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dot_shape = "{{ node [shape=box] {} }}"
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dot_rank = "{{ rank=same {} }}"
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dot_edge = "{} -> {}"
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print "digraph G {"
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print dot_shape.format(" ".join( self.pass1avg ))
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print dot_rank.format(" ".join( self.pass1avg ))
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for var in self.pass1list[::-1] :
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for dv in dg[var]:
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if dv in self.pass1set:
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print dot_edge.format(var, dv)
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print "}"
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print (self.pass1list)
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pp.pprint (self.allocate_arr (self.pass1list))
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print len(self.allocate_arr (self.pass1list))
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print (self.pass2list)
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pp.pprint (self.allocate_arr (self.pass2list))
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print len(self.allocate_arr (self.pass2list))
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def save_ir (self):
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import json
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dg = self.parser.dep_graph()
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with open("ir.py", "w") as irf:
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print >>irf, "g = ", json.dumps(dg, indent=4)
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print >>irf, "l1 = ", json.dumps(self.pass1list, indent=4)
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print >>irf, "l2 = ", json.dumps(self.pass2list, indent=4)
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print >>irf, "avg1 = ", json.dumps(self.pass1avg, indent=4)
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print >>irf, "avg2 = ", json.dumps(self.pass2avg, indent=4)
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def liveness (self, l1, g):
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import numpy as np
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img = np.zeros((len(l1), len(l1)))
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for i, v in enumerate(l1):
|
||||
for j in range(i, len(l1)):
|
||||
img[i,i:j] = img[i,i:j] + (1 if v in g[l1[j]] else 0)
|
||||
return img > 0
|
||||
|
||||
|
||||
def allocate_arr (self, l):
|
||||
|
||||
import numpy as np
|
||||
|
||||
dg = self.parser.dep_graph()
|
||||
|
||||
mask = self.liveness(l, dg)
|
||||
|
||||
narr = mask.astype(np.int).sum(axis=0).max()
|
||||
|
||||
livesets = [set(np.asarray(l)[row]) for row in mask.T]
|
||||
|
||||
array_pool = set(["xyzbuffer{}".format(i) for i in range(narr)])
|
||||
|
||||
var2arr = {}
|
||||
|
||||
var2arr[l[0]] = array_pool.pop()
|
||||
|
||||
for i, (s0, s1) in enumerate(zip(livesets[:-1], livesets[1:])):
|
||||
|
||||
array_pool.update(map(var2arr.get, s0 - s1))
|
||||
|
||||
for new in s1 - s0:
|
||||
var2arr[new] = array_pool.pop()
|
||||
|
||||
return var2arr
|
||||
|
||||
|
||||
def main():
|
||||
while True:
|
||||
try:
|
||||
s = input('> ')
|
||||
except EOFError:
|
||||
break
|
||||
print(calc(s))
|
||||
|
||||
|
||||
def test():
|
||||
|
||||
|
|
@ -618,9 +66,9 @@ def test():
|
|||
terms_raw = ((inputfile.read()))
|
||||
|
||||
|
||||
fp = FortranProgram(terms_raw)
|
||||
tree = Lark(calc_grammar, parser='lalr' ).parse(terms_raw)
|
||||
|
||||
ir1 = Stage1(fp.tree)
|
||||
ir1 = Stage1(tree)
|
||||
|
||||
ir2 = Stage2(ir1)
|
||||
|
||||
|
|
@ -636,12 +84,5 @@ def test():
|
|||
|
||||
|
||||
|
||||
|
||||
# print mod_form.format( fp.print_program() )
|
||||
|
||||
# fp.print_graph()
|
||||
|
||||
fp.save_ir()
|
||||
|
||||
if __name__ == '__main__':
|
||||
test()
|
||||
|
|
|
|||
|
|
@ -5,21 +5,16 @@ module m_calculate
|
|||
|
||||
implicit none
|
||||
|
||||
real*8, allocatable :: work(:,:,:,:)
|
||||
|
||||
real*8, allocatable, dimension(:,:) :: xsrc
|
||||
real*8, allocatable, dimension(:,:) :: xdst
|
||||
|
||||
real*8, allocatable, dimension(:,:) :: rsrc
|
||||
real*8, allocatable, dimension(:,:) :: rdst
|
||||
|
||||
real*8, allocatable, dimension(:,:,:) :: zsrc
|
||||
real*8, allocatable, dimension(:,:,:) :: zdst
|
||||
|
||||
integer, parameter :: nb = BLOCKSIZE
|
||||
|
||||
private :: work, nb
|
||||
private :: xsrc, xdst, zsrc, zdst
|
||||
private :: nb
|
||||
private :: xsrc, xdst, rsrc, rdst
|
||||
|
||||
contains
|
||||
|
||||
|
|
@ -27,8 +22,6 @@ contains
|
|||
|
||||
integer :: ierr
|
||||
|
||||
! allocate(work(nxp, nyp, nzp, 3), stat=ierr)
|
||||
|
||||
call ludcmp(nxp,nyp,nzp,1,0,0) ! 1,1,0
|
||||
|
||||
allocate(xsrc(nb, nxp), stat=ierr)
|
||||
|
|
@ -42,8 +35,6 @@ contains
|
|||
|
||||
subroutine m_calculate_finalize
|
||||
|
||||
! deallocate(work)
|
||||
|
||||
deallocate(xsrc)
|
||||
deallocate(xdst)
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue