Partitions data
into num_partitions
tensors using indices from partitions
.
tf.dynamic_partition( data, partitions, num_partitions, name=None )
For each index tuple js
of size partitions.ndim
, the slice data[js, ...]
becomes part of outputs[partitions[js]]
. The slices with partitions[js] = i
are placed in outputs[i]
in lexicographic order of js
, and the first dimension of outputs[i]
is the number of entries in partitions
equal to i
. In detail,
outputs[i].shape = [sum(partitions == i)] + data.shape[partitions.ndim:] outputs[i] = pack([data[js, ...] for js if partitions[js] == i])
data.shape
must start with partitions.shape
.
# Scalar partitions. partitions = 1 num_partitions = 2 data = [10, 20] outputs[0] = [] # Empty with shape [0, 2] outputs[1] = [[10, 20]] # Vector partitions. partitions = [0, 0, 1, 1, 0] num_partitions = 2 data = [10, 20, 30, 40, 50] outputs[0] = [10, 20, 50] outputs[1] = [30, 40]
See dynamic_stitch
for an example on how to merge partitions back.
Args | |
---|---|
data | A Tensor . |
partitions | A Tensor of type int32 . Any shape. Indices in the range [0, num_partitions) . |
num_partitions | An int that is >= 1 . The number of partitions to output. |
name | A name for the operation (optional). |
Returns | |
---|---|
A list of num_partitions Tensor objects with the same type as data . |
© 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/dynamic_partition