def predict(txt):
inp = dm.data_to_input(txt)
prediction = model.predict(inp)
predict = prediction[0][0]
predict_stars = dm.to_stars(predict)
return predict_stars
def predict_data(data):
z = []
for d in data:
z.append(dm.data_to_input(d)[0])
z = np.array(z)
prediction = zip(z, model.predict(data))
return prediction
def generate(forever = False):
inp = ''
print('Model: ' + model_name)
while forever or not any(inp == w for w in stop_words):
inp = input('Sample review:\n')
z = dm.data_to_input(inp)
prediction = model.predict(z)
predict = prediction[0][0]
predict_stars = dm.to_stars(predict)
print(dm.truncate_text('', char_to_display) + ' ----- predicted ' + predict_stars)
def generate_set(X_data, _rev_data):
print("---------------------------------------- Data Set ----------------------------------------")
print('Model: ' + model_name)
z = []
for data in X_data:
z.append(dm.data_to_input(data)[0])
X_data = np.array(z)
prediction = model.predict(X_data)
for i in range(len(_rev_data)):
predict = prediction[i][0]
predict_stars = dm.to_stars(predict)
text = str(i + 1) + ') ' + _rev_data[i]
print(dm.truncate_text(text, char_to_display) + ' ----- predicted ' + predict_stars)
total += 1
print('Loss:', loss, 'Accuracy:', str(right / total * 100) + '% |', str(right) + '/' + str(total))
print("---------------------------------------- SAMPLE REVIEWS ----------------------------------------")
tests = dm.lines_to_input(file_unlabel)
prediction = model.predict(tests)
for i in range(len(unlabeled)):
predict = prediction[i][0]
predict_stars = dm.to_stars(predict)
text = str(i + 1) + ') ' + _unlabeled[i]
print(dm.truncate_text(text, char_to_display) + ' ----- predicted ' + predict_stars)
print("---------------------------------------- CUSTOM REVIEWS ----------------------------------------")
while True:
inp = input('Sample review:\n')
z = dm.data_to_input(inp)
prediction = model.predict(z)
predict = prediction[0][0]
predict_stars = dm.to_stars(predict)
print(dm.truncate_text('', char_to_display) + ' ----- predicted ' + predict_stars)
import d_m as dm
while True:
inp = input('Word:')
vec = dm.data_to_input(inp, 1)[0][0]
print(vec)
print(vec.shape)
word = dm.vec2word(vec, 2)
print(word)