def get_questions_tensor_timeseries(questions, nlp, timesteps):
	assert not isinstance(questions, basestring)
	nb_samples = len(questions)
	word_vec_dim = nlp(questions[0])[0].vector.shape[0]
	questions_tensor = np.zeros((nb_samples, timesteps, word_vec_dim))
	for i in xrange(len(questions)):
		tokens = nlp(questions[i])
		for j in xrange(len(tokens)):
			if j<timesteps:
				questions_tensor[i,j,:] = tokens[j].vector

	return questions_tensor
Returns a time series of word vectors for tokens in the question
dataset/ETHPy150Open avisingh599/visual-qa/scripts/features.py/get_questions_tensor_timeseries