def generate_data(data_size):
"""
Sample some data according to the target
"""
data = []
for i in range(data_size):
# how many in this set
set_size = weighted_sample( range(1,10+1), probs=[7187, 1484, 593, 334, 297, 165, 151, 86, 105, 112] )
# get the objects in the current set
s = set(sample_sets_of_objects(set_size, all_objects))
# sample according to the target
if random() < ALPHA: r = WORDS[len(s)-1]
else: r = weighted_sample( WORDS )
# and append the sampled utterance
data.append(FunctionData(input=[s], output=r)) # convert to "FunctionData" and store
return data
def make_data(data_size=300, alpha=0.75):
"""
Sample some data according to the target
"""
data = []
for i in range(data_size):
# how many in this set
set_size = weighted_sample(
range(1, 10 + 1),
probs=[7187, 1484, 593, 334, 297, 165, 151, 86, 105, 112])
# get the objects in the current set
s = set(sample_sets_of_objects(set_size, all_objects))
# sample according to the target
if random() < alpha: r = WORDS[len(s) - 1]
else: r = weighted_sample(WORDS)
# and append the sampled utterance
data.append(FunctionData(input=[s], output=r, alpha=alpha))
return data
def sample_output(self, datum):
# return a sample of my output given the input in datum
if random() < datum.alpha:
return self(*datum.input)
else:
return weighted_sample(WORDS) # uniform sample
def sample_output(self, datum):
# return a sample of my output given the input in datum
if random() < datum.alpha:
return self(*datum.input)
else:
return weighted_sample(WORDS) # uniform sample