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refactor objective.Function out of Search #23

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refactor objective.Function out of Search #23

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9677dd6
refactor objective.Function out of Search
nojhan May 14, 2020
6473666
Merge branch 'master' into feat-search-function
brnorris03 Dec 24, 2020
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56 changes: 28 additions & 28 deletions orio/main/tuner/search/exhaustive/exhaustive.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,7 @@ def __init__(self, params):
orio.main.tuner.search.search.Search.__init__(self, params)

self.start_coord = None

# read all algorithm-specific arguments
self.__readAlgoArgs()

Expand All @@ -29,15 +29,15 @@ def __init__(self, params):
if self.total_runs > 1:
err('orio.main.tuner.search.exhaustive: the total number of %s search runs must be one (or can be undefined)' %
self.__class__.__name__, doexit=True)


#-----------------------------------------------------
# Method required by the search interface
def searchBestCoord(self, startCoord=None):
'''
Explore the search space and return the coordinate that yields the best performance
(i.e. minimum performance cost).

@param startCoord: Starting coordinate (optional)
@return: A list of coordinates
'''
Expand All @@ -49,46 +49,46 @@ def searchBestCoord(self, startCoord=None):
if self.use_parallel_search:
coord_count = self.num_procs
top_perf={}

# record the best coordinate and its best performance cost
best_coord = None
top_coords = {}
best_perf_cost = self.MAXFLOAT
corr_transfer = self.MAXFLOAT

# start the timer
start_time = time.time()

if startCoord:
if len(startCoord) != self.total_dims:
if len(startCoord) != self.pb.total_dims:
warn("orio.main.tuner.search.exhaustive: " +
"Invalid starting coordinate %s specified," +
" expected %d elements, but was given %d"
% (startCoord, self.total_dims, len(startCoord)))
% (startCoord, self.pb.total_dims, len(startCoord)))
startCoord = None
else:
coord = startCoord

if not startCoord:
# start from the origin coordinate (i.e. [0,0,...])
coord = [0] * self.total_dims
coord = [0] * self.pb.total_dims

coords = [coord]
while len(coords) < coord_count:
coord = self.__getNextCoord(coord)
if coord:
coords.append(coord)
else:
break

recFlag = True

# evaluate every coordinate in the search space
while True:

# determine the performance cost of all chosen coordinates
perf_costs = self.getPerfCosts(coords)
perf_costs = self.pb.getPerfCosts(coords)

# compare to the best result
pcost_items = perf_costs.items()
pcost_items.sort(lambda x,y: cmp(eval(x[0]),eval(y[0])))
Expand Down Expand Up @@ -126,13 +126,13 @@ def searchBestCoord(self, startCoord=None):
json.dump(Globals().metadata, outfile)
except Exception, e:
err('orio.search.Exhaustive: failed to execute meta export: "%s"\n --> %s: %s' % (Globals().meta,e.__class__.__name__, e),doexit = False)

if mean_perf_cost < best_perf_cost and perf_cost > 0.0:
best_coord = coord_val
best_perf_cost = mean_perf_cost
corr_transfer = mean_transfer
info('>>>> best coordinate found: %s, average cost: %e, average transfer time: %s' % (coord_val, mean_perf_cost, mean_transfer))

# record time elapsed vs best perf cost found so far in a format that could be read in by matlab/octave
#progress = 'init' if recFlag else 'continue'
#recFlag = False
Expand Down Expand Up @@ -163,25 +163,25 @@ def searchBestCoord(self, startCoord=None):
search_time = time.time() - start_time

info('----- end exhaustive search -----')

# record time elapsed vs best perf cost found so far in a format that could be read in by matlab/octave
#Globals().stats.record(time.time()-start_time, best_perf_cost, best_coord, 'done')

# return the best coordinate
return best_coord,(best_perf_cost,corr_transfer),search_time,len(coords)

# Private methods
#--------------------------------------------------

def __readAlgoArgs(self):
'''To read all algorithm-specific arguments'''

for vname, rhs in self.search_opts.iteritems():
if vname == 'start_coord':
if not isinstance(rhs,list):
err('%s argument "%s" must be a list of coordinate indices' % (self.__class__.__name__,'start_coord'))
elif len(rhs) != self.total_dims:
err('%s dimension of start_coord must be %d, but was instead %d' % (self.__class__.__name__, self.total_dims, len(rhs)))
elif len(rhs) != self.pb.total_dims:
err('%s dimension of start_coord must be %d, but was instead %d' % (self.__class__.__name__, self.pb.total_dims, len(rhs)))
self.start_coord = rhs
else:
err('orio.main.tuner.search.exhaustive: unrecognized %s algorithm-specific argument: "%s"' %
Expand All @@ -193,19 +193,19 @@ def __getNextCoord(self, coord):
'''
Return the next neighboring coordinate to be considered in the search space.
Return None if all coordinates in the search space have been visited.

@return: the next coordinate
'''
next_coord = coord[:]
for i in range(0, self.total_dims):
for i in range(0, self.pb.total_dims):
ipoint = next_coord[i]
iuplimit = self.dim_uplimits[i]
iuplimit = self.pb.dim_uplimits[i]
if ipoint < iuplimit-1:
next_coord[i] += 1
break
else:
next_coord[i] = 0
if i == self.total_dims - 1:
if i == self.pb.total_dims - 1:
return None
return next_coord

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