def padded_context_features(self, context_w, context_of, context_cvp, max_context_len=5, max_sen_len=20):
    context_w = context_w[(- max_context_len):]
    context_of = context_of[(- max_context_len):]
    context_cvp = context_cvp[(- max_context_len):]
    padded_context = []
    for i in range(len(context_w)):
        p_seq_w = self.paded_word_idx(context_w[i], max_sen_len)
        p_seq_cvp = self.padded_covarep_features(context_cvp[i], max_sen_len)
        p_seq_of = self.padded_openface_features(context_of[i], max_sen_len)
        padded_context.append(np.concatenate((p_seq_w, p_seq_cvp, p_seq_of), axis=1))
    pad_c_len = (max_context_len - len(padded_context))
    padded_context = np.array(padded_context)
    if (not padded_context.any()):
        return np.zeros((max_context_len, max_sen_len, self.total_dim))
    return np.concatenate((np.zeros((pad_c_len, max_sen_len, self.total_dim)), padded_context), axis=0)
def padded_context_features(self, context_w, context_of, context_cvp, max_context_len=5, max_sen_len=20):
    context_w = context_w[(- max_context_len):]
    context_of = context_of[(- max_context_len):]
    context_cvp = context_cvp[(- max_context_len):]
    padded_context = []
    for i in range(len(context_w)):
        p_seq_w = self.paded_word_idx(context_w[i], max_sen_len)
        p_seq_cvp = self.padded_covarep_features(context_cvp[i], max_sen_len)
        p_seq_of = self.padded_openface_features(context_of[i], max_sen_len)
        padded_context.append(np.concatenate((p_seq_w, p_seq_cvp, p_seq_of), axis=1))
    pad_c_len = (max_context_len - len(padded_context))
    padded_context = np.array(padded_context)
    if (not padded_context.any()):
        return np.zeros((max_context_len, max_sen_len, self.total_dim))
    return np.concatenate((np.zeros((pad_c_len, max_sen_len, self.total_dim)), padded_context), axis=0)