Computes the mean along sparse segments of a tensor.
tf.raw_ops.SparseSegmentMeanWithNumSegments(
data, indices, segment_ids, num_segments, sparse_gradient=False, name=None
)
Like SparseSegmentMean, 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.
Args |
|---|
data
|
A Tensor. Must be one of the following types: bfloat16, half, float32, float64.
|
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.
|
