tf.raw_ops.SparseSegmentSumWithNumSegments
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Computes the sum along sparse segments of a tensor.
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tf.compat.v1.raw_ops.SparseSegmentSumWithNumSegments
tf . raw_ops . SparseSegmentSumWithNumSegments (
data , indices , segment_ids , num_segments , sparse_gradient = False , name = None
)
Like SparseSegmentSum
, but allows missing ids in segment_ids
. If an id is
missing, the output
tensor at that position will be zeroed.
Read
the section on segmentation
for an explanation of segments.
For example:
c = tf . constant ([[ 1 , 2 , 3 , 4 ], [ - 1 , - 2 , - 3 , - 4 ], [ 5 , 6 , 7 , 8 ]])
tf . sparse_segment_sum_with_num_segments (
c , tf . constant ([ 0 , 1 ]), tf . constant ([ 0 , 0 ]), num_segments = 3 )
# => [[0 0 0 0]
# [0 0 0 0]
# [0 0 0 0]]
tf . sparse_segment_sum_with_num_segments ( c ,
tf . constant ([ 0 , 1 ]),
tf . constant ([ 0 , 2 ],
num_segments = 4 ))
# => [[ 1 2 3 4]
# [ 0 0 0 0]
# [-1 -2 -3 -4]
# [ 0 0 0 0]]
Args
data
A Tensor
. Must be one of the following types: float32
, float64
, int32
, uint8
, int16
, int8
, int64
, bfloat16
, uint16
, half
, uint32
, uint64
.
indices
A Tensor
. Must be one of the following types: int32
, int64
.
A 1-D tensor. Has same rank as segment_ids
.
segment_ids
A Tensor
. Must be one of the following types: int32
, int64
.
A 1-D tensor. Values should be sorted and can be repeated.
num_segments
A Tensor
. Must be one of the following types: int32
, int64
.
Should equal the number of distinct segment IDs.
sparse_gradient
An optional bool
. Defaults to False
.
name
A name for the operation (optional).
Returns
A Tensor
. Has the same type as data
.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license .
Last updated 2024-01-23 UTC.
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