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.
|
Raises |
|---|
ValueError
|
if neither or both of {window_size, window_size_func} are
passed.
|
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TensorFlow 1 version
View source on GitHub