def testMarginalizeBothAxis(self):
manage.config.MAXPOWER = np.array([10])
a = ExprZp([1], np.array([[1, 0, 0]]))
b = ExprZp([1], np.array([[0, 1, 0]]))
c = ExprZp([2], np.array([[0, 0, 1]]))
expressions = np.array([[a, b, c], [a, b, c]], dtype=np.object)
matrix = ExprMatrix('A', expressions, powers=np.array([1]))
matrix = matrix.Marginalize(axis=None)
self.assertEquals((1, 1), matrix.expressions.shape)
def testHashImmuneToConst(self):
manage.config.MAXPOWER = np.array([10])
a = ExprZp(
[2, 3],
np.array([[1, 2, 3], [4, 5, 6]]))
b = ExprZp(
[4, 6],
np.array([[1, 2, 3], [4, 5, 6]]))
self.assertNotEquals(a, b)
a = ExprMatrix("a", np.array([[a]]), np.array([1]))
b = ExprMatrix("b", np.array([[b]]), np.array([1]))
self.assertEquals(a, b)
def testElementwiseMultiply(self):
manage.config.MAXPOWER = np.array([10, 10])
# a = x1 * x3
# b = x1 * x2^2
# c = x2^3 + x3^4
a = ExprZp([1], np.array([[1, 0, 1]]))
b = ExprZp([1], np.array([[1, 2, 0]]))
c = ExprZp([1, 1], np.array([[0, 3, 0], [0, 0, 4]]))
expressions1 = np.array([[a, b], [c, a]])
expressions2 = np.array([[a, a], [a, a]])
# mat1:
# x1x3 | x1 * x2^2
# x2^3 + x3^4 | x1x3
mat1 = ExprMatrix('M1', expressions1, powers=np.array([1, 0]))
mat2 = ExprMatrix('M2', expressions2, powers=np.array([0, 1]))
mat1.ElementwiseMultiply(mat2)
self.assertEquals((2, 2), mat1.expressions.shape)
def testShapesAfterSumAreCorrec(self):
manage.config.MAXPOWER = np.array([10])
a = ExprZp([1], np.array([[1, 0, 0]]))
b = ExprZp([1], np.array([[0, 1, 0]]))
expressions = np.array([[a, a, a], [b, b, b]])
matrix = ExprMatrix('M', expressions, powers=np.array([1]))
# Exp matrix test
self.assertEquals((2, 3), matrix.expressions.shape)
m0 = copy.copy(matrix)
m0 = m0.Marginalize(axis=0)
self.assertEquals((1, 3), m0.expressions.shape)
self.assertEquals(a + b, m0.expressions[0, 0])
self.assertEquals(a + b, m0.expressions[0, 1])
m1 = copy.copy(matrix)
m1 = m1.Marginalize(axis=1)
self.assertEquals((2, 1), m1.expressions.shape)
self.assertEquals(a + a + a, m1.expressions[0, 0])
self.assertEquals(b + b + b, m1.expressions[1, 0])
def testAddExpressions(self): a = ExprZp([1], np.array([[1, 0, 0]])) # x1 b = ExprZp([1], np.array([[0, 0, 1]])) # x3 c = ExprZp([2], np.array([[1, 0, 1]])) # 2x1x3 d = ExprZp([2], np.array([[1, 0, 0]])) # 2x1 e = ExprZp([2], np.array([[0, 0, 1]])) # 2x3 self.assertEquals(a + a, d) self.assertEquals(b+b, e) print 'Karol D:' d.PrintDebug() print 'Karol E:' e.PrintDebug() print 'Karol D*E:' (d*e).PrintDebug() print 'Karol C+C:' (c+c).PrintDebug() self.assertEquals(d * e, c+c)
def main():
for target, labels in [targets[2]]:
params = {'depth': 5, 'trials': 1, 'run_id': 1}
scheduler = NgramScheduler(params)
solution_tree = None
for i in range(1, 16):
matlab, tree, solution_tree = execute_once(scheduler, params,
target, solution_tree,
i)
if matlab is None:
break
name = get_name_matlab(target, i)
original = target(i).GetTargetExpression()
code = ""
code += original.comp[MATLAB] + "\n"
code += "optimized = "
expr = ""
try:
for w, c in matlab:
if len(expr) > 0:
expr += " + "
expr += "%s * (%s)" % (ExprZp.ToFrac(w), c)
except:
break
if target == RBM:
expr = "2^(n + m - %d) * (%s)" % (manage.config.N +
manage.config.M, expr)
if target == RBMOneSide:
expr = "2^(n - %d) * (%s)" % (manage.config.M, expr)
if target == Sym:
expr = "(%s) / 120" % expr
code += expr + ";\n"
code += "normalization = sum(abs(original(:)));\n"
code += "assert(sum(abs(original(:) - optimized(:))) / normalization < 1e-10);"
f = open("code.m", 'w')
f.write(code)
f.close()
print "Executing matlab code: \n%s\n" % code
ret = os.system(
"matlab -nodesktop -nodisplay -nojvm -nosplash -r \"try run('code.m');catch exit(-1); end; exit(0) \" > /dev/null"
)
if ret != 0:
break
os.rename("code.m", name)
tree_string = ""
for j, t in enumerate(tree):
ProcessLine(j, str(t), get_name_tree(target, i))
generate_sup()
def testEquivalence(self):
targets = [RBMOneSide, SumAmultA, RBM, SumAAT, SumAB, Sym]
for target in targets:
manage.config.EXPR_IMPL = ExprZp
scheduler = NgramScheduler
params = {'depth': 5, 'trials': 1}
matlab = execute(scheduler,
params,
target,
maxpower=4,
record_it=False)[0]["matlab"]
for i, m in enumerate(matlab):
f = open('code.m', 'w')
original = target(i + 1).GetTargetExpression()
code = ""
code += original.comp[MATLAB] + "\n"
code += "optimized = "
expr = ""
for w, c in m:
if len(expr) > 0:
expr += " + "
expr += "%s * (%s)" % (ExprZp.ToFrac(w), c)
if target == RBM:
expr = "2^(n + m - %d) * (%s)" % (manage.config.N +
manage.config.M, expr)
if target == RBMOneSide:
expr = "2^(n - %d) * (%s)" % (manage.config.M, expr)
code += expr + ";\n"
code += "assert(sum(abs(original(:) - optimized(:))) / sum(abs(original(:))) < 1e-8);"
f.write(code)
f.close()
print "Executing matlab code: \n%s\n" % code
ret = os.system(
"matlab -nodesktop -nodisplay -nojvm -nosplash -r \"try run('code.m');catch exit(-1); end; exit(0) \" > /dev/null"
)
if ret == 0:
print "Passed matlab verification\n"
else:
self.assertEquals(ret, 0)
os.remove('code.m')
def testFindLinearCombinationWithMatrix(self):
manage.config.MAXPOWER = np.array([10])
# mat1 mat2 target
# x1 | x1x2 x1 | x1x2 3x1 | 3x1x2
# 2x3 | x2^2 x1 | x3 4x3+x1 | 2x2^2 + x3
mat1_11 = ExprZp([1], np.array([[1, 0, 0]]))
mat1_12 = ExprZp([1], np.array([[1, 1, 0]]))
mat1_21 = ExprZp([2], np.array([[0, 0, 1]]))
mat1_22 = ExprZp([1], np.array([[0, 2, 0]]))
mat2_11 = ExprZp([1], np.array([[1, 0, 0]]))
mat2_12 = ExprZp([1], np.array([[1, 1, 0]]))
mat2_21 = ExprZp([1], np.array([[1, 0, 0]]))
mat2_22 = ExprZp([1], np.array([[0, 0, 1]]))
target_11 = ExprZp([3], np.array([[1, 0, 0]]))
target_12 = ExprZp([3], np.array([[1, 1, 0]]))
target_21 = ExprZp([4, 1], np.array([[0, 0, 1], [1, 0, 0]]))
target_22 = ExprZp([2, 1], np.array([[0, 2, 0], [0, 0, 1]]))
mat1 = ExprMatrix("a",
np.array([[mat1_11, mat1_12], [mat1_21, mat1_22]]), np.array([1]))
mat2 = ExprMatrix("b",
np.array([[mat2_11, mat2_12], [mat2_21, mat2_22]]), np.array([1]))
target = ExprMatrix(
"target",
np.array([[target_11, target_12], [target_21, target_22]]),
np.array([1]))
expressions_list = [mat1, mat2]
weights = ExprZp.FindLinearCombination(expressions_list, target)[0]
self.assertEquals(2, len(weights))
self.assertAlmostEqual(2.0, weights[0])
self.assertAlmostEqual(1.0, weights[1])