tf.segment_mean()

tf.segment_mean(data, segment_ids, name=None)

Computes the mean along segments of a tensor.

Read the section on Segmentation for an explanation of segments.

Computes a tensor such that \(output_i = \frac{\sum_j data_j}{N}\) where mean is over j such that segment_ids[j] == i and N is the total number of values summed.

Args:

• data: A Tensor. Must be one of the following types: float32, float64, int32, int64, uint8, int16, int8, uint16, half.
• segment_ids: A Tensor. Must be one of the following types: int32, int64. A 1-D tensor whose rank is equal to the rank of data's first dimension. Values should be sorted and can be repeated.
• name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as data. Has same shape as data, except for dimension 0 which has size k, the number of segments.