def test_local_sigm_times_exp(self):
# Test the `local_sigm_times_exp` optimization.
# exp(x) * sigm(-x) -> sigm(x)
# exp(-x) * sigm(x) -> sigm(-x)
def match(func, ops):
# print [node.op.scalar_op for node in func.maker.fgraph.toposort()]
assert [node.op for node in func.maker.fgraph.toposort()] == ops
m = self.get_mode(excluding=["local_elemwise_fusion", "inplace"])
x, y = tt.vectors("x", "y")
f = aesara.function([x], sigmoid(-x) * tt.exp(x), mode=m)
match(f, [sigmoid])
assert check_stack_trace(f, ops_to_check=sigmoid)
f = aesara.function([x], sigmoid(x) * tt.exp(-x), mode=m)
match(f, [tt.neg, sigmoid])
assert check_stack_trace(f, ops_to_check=sigmoid)
f = aesara.function([x], -(-(-(sigmoid(x)))) * tt.exp(-x), mode=m)
match(f, [tt.neg, sigmoid, tt.neg])
# assert check_stack_trace(f, ops_to_check=sigmoid)
f = aesara.function(
[x, y],
(sigmoid(x) * sigmoid(-y) * -tt.exp(-x) * tt.exp(x * y) *
tt.exp(y)),
mode=m,
)
topo = f.maker.fgraph.toposort()
for op, nb in [(sigmoid, 2), (tt.mul, 2), (tt.neg, 1), (tt.exp, 1)]:
assert sum([n.op == op for n in topo]) == nb
def test_local_ultra_fast_sigmoid(self):
x = tt.matrix("x")
s = sigmoid(x)
mode = self.get_mode("local_ultra_fast_sigmoid")
f = aesara.function([x], s, mode=mode)
assert check_stack_trace(f, ops_to_check=sigmoid)
topo = f.maker.fgraph.toposort()
assert len(topo) == 1
assert topo[0].op == sigmoid
mode = self.get_mode().including("local_ultra_fast_sigmoid")
f = aesara.function([x], s, mode=mode)
assert check_stack_trace(f, ops_to_check=ultra_fast_sigmoid)
topo = f.maker.fgraph.toposort()
assert topo[0].op == ultra_fast_sigmoid
assert len(topo) == 1
f([[-50, -10, -4, -1, 0, 1, 4, 10, 50]])
def test_local_hard_sigmoid(self):
x = tt.matrix("x")
s = sigmoid(x)
mode = self.get_mode("local_hard_sigmoid")
f = aesara.function([x], s, mode=mode)
assert check_stack_trace(f, ops_to_check=sigmoid)
topo = f.maker.fgraph.toposort()
assert topo[0].op == sigmoid
assert len(topo) == 1
mode = self.get_mode().including("local_hard_sigmoid")
f = aesara.function([x], s, mode=mode)
topo = f.maker.fgraph.toposort()
assert not any([n.op == sigmoid for n in topo])
f([[-50, -10, -4, -1, 0, 1, 4, 10, 50]])
mode2 = mode.excluding("fusion").excluding("inplace")
f2 = aesara.function([x], s, mode=mode2)
assert check_stack_trace(f2, ops_to_check=tt.clip)
def test_1msigmoid(self):
if not register_local_1msigmoid:
return
m = self.get_mode()
x = tt.fmatrix()
# tests exp_over_1_plus_exp
f = aesara.function([x], 1 - tt.exp(x) / (1 + tt.exp(x)), mode=m)
assert check_stack_trace(f, ops_to_check=[tt.neg, sigmoid_inplace])
assert [node.op for node in f.maker.fgraph.toposort()] == [
tt.neg,
sigmoid_inplace,
]
# tests inv_1_plus_exp
f = aesara.function([x],
1 - tt.fill(x, 1.0) / (1 + tt.exp(-x)),
mode=m)
assert check_stack_trace(f, ops_to_check=[tt.neg, sigmoid_inplace])
assert [node.op for node in f.maker.fgraph.toposort()] == [
tt.neg,
sigmoid_inplace,
]
def check_diagonal_subtensor_view_traces(fn):
assert check_stack_trace(fn,
ops_to_check=(DiagonalSubtensor,
IncDiagonalSubtensor))