def compute_prior(self):
"""
Assign 0-probability to hypotheses with repeat values.
BUT we only discover repeat values by reducing.
"""
seen = set()
for k, v in self.value.items():
try:
reduced = str(lambda_reduce(v.value))
except EvaluationException:
return -Infinity
if reduced in seen:
return -Infinity
else:
seen.add(reduced)
return SimpleLexicon.compute_prior(self)
def compute_prior(self):
"""
Assign 0-probability to hypotheses with repeat values.
BUT we only discover repeat values by reducing.
"""
seen = set()
for k,v in self.value.items():
try:
reduced = str(lambda_reduce(v.value))
except EvaluationException:
return -Infinity
if reduced in seen:
return -Infinity
else:
seen.add(reduced)
return SimpleLexicon.compute_prior(self)
def compute_prior(self):
return SimpleLexicon.compute_prior(self) - self.N * log(2.0)/self.prior_temperature # coin flip for each additional word
def compute_prior(self):
return SimpleLexicon.compute_prior(self) - self.N * log(
2.0) / self.prior_temperature # coin flip for each additional word
