使用整个训练集计算样本均值和标准差

Question

如何使用整个训练数据计算统计信息？我想使用从训练集中计算出的统计数据来归一化测试数据。这是函数

[注意]-胸部X射线图像数据

def get_test_and_valid_generator(valid_df, test_df, train_df, image_dir, x_col, y_cols, sample_size=100, batch_size=64, seed=1, target_w = 224, target_h = 224):

    print("getting train and valid generators...")

    raw_train_generator = ImageDataGenerator().flow_from_dataframe(
        dataframe=train_df, 
        directory=IMAGE_DIR, 
        x_col="Image", 
        y_col=labels, 
        class_mode="raw", 
        batch_size=sample_size, 
        shuffle=True, 
        target_size=(target_w, target_h))

    batch = raw_train_generator.next()
    data_sample = batch[0]

    image_generator = ImageDataGenerator(
        featurewise_center=True,
        featurewise_std_normalization= True)

    image_generator.fit(data_sample)

    valid_generator = image_generator.flow_from_dataframe(
            dataframe=valid_df,
            directory=image_dir,
            x_col=x_col,
            y_col=y_cols,
            class_mode="raw",
            batch_size=batch_size,
            shuffle=False,
            seed=seed,
            target_size=(target_w,target_h))

    test_generator = image_generator.flow_from_dataframe(
            dataframe=test_df,
            directory=image_dir,
            x_col=x_col,
            y_col=y_cols,
            class_mode="raw",
            batch_size=batch_size,
            shuffle=False,
            seed=seed,
            target_size=(target_w,target_h))
    return valid_generator, test_generator

我的训练数据大小为78115，测试大小为25595，瓦尔大小为8408。

有人可以帮助我吗？还有其他方法吗？强调文本