tf.data.Dataset

Represents a potentially large set of elements.

Used in the notebooks

Used in the guide Used in the tutorials

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.

Iteration happens in a streaming fashion, so the full dataset does not need to fit into memory.

Source Datasets:

The simplest way to create a dataset is to create it from a python list:

dataset = tf.data.Dataset.from_tensor_slices([1, 2, 3])
for element in dataset:
  print(element)
tf.Tensor(1, shape=(), dtype=int32)
tf.Tensor(2, shape