我对这个模型的批量大小感到困惑。我使用 sgd 即随机梯度下降作为优化器（参见代码）。我知道在 sgd 中，训练集中的单个随机实例用于计算每一步的梯度。因此，根据它，batch_size 应该等于 1。现在，在tf.keras.Sequential.fit()文档中它说：

如果未指定，batch_size 将默认为 32。

那么，我是否必须手动将 batch_size 设置为 1？这是因为默认值 32 将使其成为 Mini-batch Gradient Descent。

    import tensorflow as tf
    from tensorflow import keras

    fashion_mnist = keras.datasets.fashion_mnist
    (X_train_full, y_train_full), (X_test, y_test) = fashion_mnist.load_data()

    X_valid, X_train = X_train_full[:5000]/255.0, X_train_full[5000:]/255.0
    y_valid, y_train = y_train_full[:5000], y_train_full[5000:]

    model = keras.models.Sequential()

    model.add(keras.layers.InputLayer(input_shape = [28, 28]))
    model.add(keras.layers.Flatten())
    model.add(keras.layers.Dense(300, activation = "relu"))
    model.add(keras.layers.Dense(100, activation = "relu"))
    model.add(keras.layers.Dense(10, activation = "softmax"))

    model.compile(loss = "sparse_categorical_crossentropy", optimizer = "sgd", metrics = ["accuracy"])

    history = model.fit(X_train, y_train, epochs = 30, validation_data = (X_valid, y_valid))