def __init__(self, tasks, testingTasks=[], cuda=False):
self.lexicon = set(
flatten((t.examples for t in tasks + testingTasks),
abort=lambda x: isinstance(x, str))).union(
{"LIST_START", "LIST_END", "?"})
# Calculate the maximum length
self.maximumLength = float(
'inf') # Believe it or not this is actually important to have here
self.maximumLength = max(
len(l) for t in tasks + testingTasks
for xs, y in self.tokenize(t.examples)
for l in [y] + [x for x in xs])
self.recomputeTasks = True
super(LearnedFeatureExtractor,
self).__init__(lexicon=list(self.lexicon),
tasks=tasks,
cuda=cuda,
H=self.H,
bidirectional=True)
def __init__(self, tasks, testingTasks=[], cuda=False):
self.lexicon = set(
flatten((t.examples for t in tasks + testingTasks),
abort=lambda x: isinstance(x, str))).union(
{"LIST_START", "LIST_END", "?"})
self.num_examples_list = [len(t.examples) for t in tasks]
# Calculate the maximum length
self.maximumLength = POSITIVEINFINITY
self.maximumLength = max(
len(l) for t in tasks + testingTasks
for xs, y in self.tokenize(t.examples)
for l in [y] + [x for x in xs])
super(LearnedFeatureExtractor,
self).__init__(lexicon=list(self.lexicon),
tasks=tasks,
cuda=cuda,
H=self.H,
bidirectional=True)
self.parallelTaskOfProgram = False