log1pexp_to_softplus = gof.PatternSub(
(tensor.log1p, (tensor.exp, "x")),
(softplus, "x"),
values_eq_approx=values_eq_approx_remove_inf,
allow_multiple_clients=True,
)
log1p_neg_sigmoid = gof.PatternSub(
(tensor.log1p, (tensor.neg, (sigmoid, "x"))),
(tensor.neg, (softplus, "x")),
values_eq_approx=values_eq_approx_remove_inf,
allow_multiple_clients=True,
)
opt.register_stabilize(logsigm_to_softplus, name="logsigm_to_softplus")
opt.register_stabilize(log1msigm_to_softplus, name="log1msigm_to_softplus")
opt.register_stabilize(log1pexp_to_softplus, name="log1pexp_to_softplus")
opt.register_stabilize(log1p_neg_sigmoid, name="log1p_neg_sigmoid,")
def is_1pexp(t, only_process_constants=True):
"""
Returns
-------
object
If 't' is of the form (1+exp(x)), return (False, x).
Else return None.
"""
log1msigm_to_softplus = gof.PatternSub(
(tensor.log,
(tensor.sub,
dict(pattern='y', constraint=_is_1),
(sigmoid, 'x'))),
(tensor.neg, (softplus, 'x')),
allow_multiple_clients=True,
skip_identities_fn=_skip_mul_1)
log1pexp_to_softplus = gof.PatternSub(
(tensor.log1p,
(tensor.exp, 'x')),
(softplus, 'x'),
allow_multiple_clients=True)
opt.register_stabilize(logsigm_to_softplus, name='logsigm_to_softplus')
opt.register_stabilize(log1msigm_to_softplus, name='log1msigm_to_softplus')
opt.register_stabilize(log1pexp_to_softplus, name='log1pexp_to_softplus')
def is_1pexp(t):
"""
If 't' is of the form (1+exp(x)), return (False, x).
Else return None.
"""
if t.owner and t.owner.op == tensor.add:
scalars, scalar_inputs, nonconsts = \
opt.scalarconsts_rest(t.owner.inputs)
# scalar_inputs are potentially dimshuffled and fill'd scalars
if len(nonconsts) == 1:
maybe_exp = nonconsts[0]
v = opt.get_scalar_constant_value(expr)
return numpy.allclose(v, 1)
except tensor.NotScalarConstantError:
return False
log1msigm_to_softplus = gof.PatternSub(
(tensor.log, (tensor.sub, dict(pattern="y", constraint=_is_1), (sigmoid, "x"))),
(tensor.neg, (softplus, "x")),
allow_multiple_clients=True,
skip_identities_fn=_skip_mul_1,
)
log1pexp_to_softplus = gof.PatternSub((tensor.log1p, (tensor.exp, "x")), (softplus, "x"), allow_multiple_clients=True)
opt.register_stabilize(logsigm_to_softplus, name="logsigm_to_softplus")
opt.register_stabilize(log1msigm_to_softplus, name="log1msigm_to_softplus")
opt.register_stabilize(log1pexp_to_softplus, name="log1pexp_to_softplus")
def is_1pexp(t):
"""
Returns
-------
object
If 't' is of the form (1+exp(x)), return (False, x).
Else return None.
"""
if t.owner and t.owner.op == tensor.add:
log1pexp_to_softplus = gof.PatternSub(
(tensor.log1p,
(tensor.exp, 'x')),
(softplus, 'x'),
values_eq_approx=values_eq_approx_remove_inf,
allow_multiple_clients=True)
log1p_neg_sigmoid = gof.PatternSub(
(tensor.log1p,
(tensor.neg, (sigmoid, 'x'))),
(tensor.neg, (softplus, 'x')),
values_eq_approx=values_eq_approx_remove_inf,
allow_multiple_clients=True)
opt.register_stabilize(logsigm_to_softplus, name='logsigm_to_softplus')
opt.register_stabilize(log1msigm_to_softplus, name='log1msigm_to_softplus')
opt.register_stabilize(log1pexp_to_softplus, name='log1pexp_to_softplus')
opt.register_stabilize(log1p_neg_sigmoid, name='log1p_neg_sigmoid,')
def is_1pexp(t, only_process_constants=True):
"""
Returns
-------
object
If 't' is of the form (1+exp(x)), return (False, x).
Else return None.
"""
