lstm_model.py 文件源码

def get_train_val(X,y,idx, options):
    X_train = X[:idx] + X[idx+1:]
    y_train = y[:idx] + y[idx+1:]
    X_train = pad_sequences(X_train, maxlen = options['MAX_LEN'], padding = 'post', value = 0, truncating = 'post')
    y_train = pad_sequences(y_train, maxlen = options['MAX_LEN'], padding = 'post', value = 0, truncating = 'post')
    y_train_categorical = []
    for idx in xrange(y_train.shape[0]):
        y_train_categorical.append( to_categorical(y_train[idx], len(options['CLASSES_2_IX'])))
    return X_train, np.array(y_train_categorical)