tf.raw_ops.InterleaveDataset
Creates a dataset that applies f to the outputs of input_dataset.
tf.raw_ops.InterleaveDataset(
input_dataset, other_arguments, cycle_length, block_length, f, output_types,
output_shapes, name=None
)
Unlike MapDataset, the f in InterleaveDataset is expected to return a Dataset variant, and InterleaveDataset will flatten successive results into a single Dataset. Unlike FlatMapDataset, InterleaveDataset will interleave sequences of up to block_length consecutive elements from cycle_length input elements.
| Args | |
|---|---|
input_dataset |
A Tensor of type variant. |
other_arguments |
A list of Tensor objects. |
cycle_length |
A Tensor of type int64. |
block_length |
A Tensor of type int64. |
f |
A function decorated with @Defun. A function mapping elements of input_dataset, concatenated with other_arguments, to a Dataset variant that contains elements matching output_types and output_shapes. |
output_types |
A list of tf.DTypes that has length >= 1. |
output_shapes |
A list of shapes (each a tf.TensorShape or list of ints) that has length >= 1. |
name |
A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor of type variant. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/raw_ops/InterleaveDataset