tf.raw_ops.LegacyParallelInterleaveDatasetV2
Creates a dataset that applies f to the outputs of input_dataset.
tf.raw_ops.LegacyParallelInterleaveDatasetV2(
input_dataset, other_arguments, cycle_length, block_length,
buffer_output_elements, prefetch_input_elements, f, output_types, output_shapes,
deterministic='default', name=None
)
The resulting dataset is similar to the InterleaveDataset, with the exception that if retrieving the next value from a dataset would cause the requester to block, it will skip that input dataset. This dataset is especially useful when loading data from a variable-latency datastores (e.g. HDFS, GCS), as it allows the training step to proceed so long as some data is available.
!! WARNING !! This dataset is not deterministic!
| 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. |
buffer_output_elements |
A Tensor of type int64. |
prefetch_input_elements |
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. |
deterministic |
An optional string. Defaults to "default". |
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/LegacyParallelInterleaveDatasetV2