Dataset: The Dataset returned by applying transformation_func to this dataset.Ĭombines consecutive elements of this dataset into batches.transformation_func: A function that takes one Dataset argument and returns a Dataset.apply(group_by_window(key_func, reduce_func, window_size)) RuntimeError: If eager execution is not enabled.Īpply a transformation function to this dataset.Īpply enables chaining of custom Dataset transformations, which are represented as functions that take one Dataset argument and return a transformed Dataset.įor example: dataset = (dataset.map(lambda x: x ** 2).Returns:Īn Iterator over the elements of this dataset. The returned iterator implements the Python iterator protocol and therefore can only be used in eager mode. _iter_ _iter_()Ĭreates an Iterator for enumerating the elements of this dataset. See help(type(self)) for accurate signature. Returns:Ī nested structure of tf.DType objects corresponding to each component of an element of this dataset. Returns the type of each component of an element of this dataset. Returns:Ī nested structure of tf.TensorShape objects corresponding to each component of an element of this dataset. Returns the shape of each component of an element of this dataset. Returns:Ī nested structure of Python type objects corresponding to each component of an element of this dataset. The expected values are tf.Tensor and tf.SparseTensor. Returns the class of each component of an element of this dataset. Represents a potentially large set of elements.Ī Dataset can be used to represent an input pipeline as a collection of elements (nested structures of tensors) and a "logical plan" of transformations that act on those elements. See the guides: Dataset Input Pipeline, Reading data > tf.data API Defined in tensorflow/python/data/ops/dataset_ops.py.
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