tf.data.experimental.group_by_window | TensorFlow v2.16.1 (original) (raw)
tf.data.experimental.group_by_window
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A transformation that groups windows of elements by key and reduces them. (deprecated)
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Compat aliases for migration
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tf.compat.v1.data.experimental.group_by_window
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 appliesreduce_func to at most window_size_func(key) elements matching the same key. All except the final window for each key will containwindow_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 andself.output_types) to a scalar tf.int64 tensor. |
| reduce_func | A function mapping a key and a dataset of up to window_sizeconsecutive 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 withwindow_size_func. |
| window_size_func | A function mapping a key to a tf.int64 scalartf.Tensor, representing the number of consecutive elements matching the same key to combine in a single batch, which will be passed toreduce_func. Mutually exclusive with window_size. |
| Returns |
|---|
| A Dataset transformation function, which can be passed totf.data.Dataset.apply. |
| Raises | |
|---|---|
| ValueError | if neither or both of {window_size, window_size_func} are passed. |
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Last updated 2024-04-26 UTC.