def sample_model(model, chars = 5000):
try:
model_path = model.split(';')[0].strip()
temp = model.split(';')[1].strip()
words = rnn.run_temperature(model_path, temp, chars).splitlines()[2:-2]
print model,'generated',len(words)
return words
except:
print traceback.format_exc()
return []
model, words = observed_model.strip().splitlines()
words = words.replace(')', '').replace('(', '').replace(' ', '').split(',')
for index in models[model]:
model_sample = training_data[index:index + 100]
for word in words:
if word in model_sample:
line_end = index - 1
line_start = training_data.rfind('\n', 0, line_end - 1)
generators.add(training_data[line_start + 1:line_end].strip())
model_scores = {}
for model_temp in generators:
model = model_temp.split(';')[0].strip()
temp = model_temp.split(';')[1].replace(':', '').strip()
words = rnn.run_temperature(model, temp, 1000).splitlines()
model_scores[model_temp] = score_words(words)
models_score_ordered = map(lambda x: x[0],
sorted(model_scores.items(), key=lambda x: x[1]))
models_score_ordered.reverse()
print '\n'.join(models_score_ordered[:5])
sys.exit(0)
#pdb.set_trace()
results = sorted(model_samples.items(), key=lambda x: score(x[1]))
results.reverse()
for result in results:
print score(result[1])
model, words = observed_model.strip().splitlines()
words = words.replace(')','').replace('(','').replace(' ','').split(',')
for index in models[model]:
model_sample = training_data[index:index+100]
for word in words:
if word in model_sample:
line_end = index - 1
line_start = training_data.rfind('\n', 0, line_end - 1)
generators.add(training_data[line_start+1:line_end].strip())
model_scores = {}
for model_temp in generators:
model = model_temp.split(';')[0].strip()
temp = model_temp.split(';')[1].replace(':','').strip()
words = rnn.run_temperature(model, temp, 1000).splitlines()
model_scores[model_temp] = score_words(words)
models_score_ordered = map(lambda x:x[0], sorted(model_scores.items(), key = lambda x:x[1]))
models_score_ordered.reverse()
print '\n'.join(models_score_ordered[:5])
sys.exit(0)
#pdb.set_trace()
results = sorted(model_samples.items(), key = lambda x:score(x[1]))
results.reverse()
for result in results:
print score(result[1])
print result[0]
