View source on GitHub |
A transformation that groups windows of elements by key and reduces them.
tf.data.experimental.group_by_window( key_func, reduce_func, window_size=None, window_size_func=None )
This transformation maps each consecutive element in a dataset to a key using key_func
and groups the elements by key. It then applies reduce_func
to at most window_size_func(key)
elements matching the same key. All except the final window for each key will contain window_size_func(key)
elements; the final window may be smaller.
You may provide either a constant window_size
or a window size determined by the key through window_size_func
.
Args | |
---|---|
key_func | A function mapping a nested structure of tensors (having shapes and types defined by self.output_shapes and self.output_types ) to a scalar tf.int64 tensor. |
reduce_func | A function mapping a key and a dataset of up to window_size consecutive elements matching that key to another dataset. |
window_size | A tf.int64 scalar tf.Tensor , representing the number of consecutive elements matching the same key to combine in a single batch, which will be passed to reduce_func . Mutually exclusive with window_size_func . |
window_size_func | A function mapping a key to a tf.int64 scalar tf.Tensor , representing the number of consecutive elements matching the same key to combine in a single batch, which will be passed to reduce_func . Mutually exclusive with window_size . |
Returns | |
---|---|
A Dataset transformation function, which can be passed to tf.data.Dataset.apply . |
Raises | |
---|---|
ValueError | if neither or both of {window_size , window_size_func } are passed. |
© 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/r1.15/api_docs/python/tf/data/experimental/group_by_window