Tensorflow Dataset API

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The tf.data.Dataset API supports writing descriptive and efficient input pipelines. Dataset usage follows a common pattern:

1. Create a source dataset from your input data.
2. Apply dataset transformations to preprocess the data.
3. Iterate over the dataset and process the elements.

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Methods:

1. batch 

batch(
    batch_size, drop_remainder=False
)

Combines consecutive elements of this dataset into batches.

把当前的dataset分割成连续的batches

drop_remainder = true时把最后一组那些剩下的，除不尽的元素舍弃

dataset = tf.data.Dataset.range(8)
dataset = dataset.batch(3)
list(dataset.as_numpy_iterator())

输出：Array[[0, 1, 2], [3, 4, 5], [6, 7]]

dataset = tf.data.Dataset.range(8)
dataset = dataset.batch(3, drop_remainder=True)
list(dataset.as_numpy_iterator())

输出：Array[[0, 1, 2], [3, 4, 5]]