tf.math.scalar

Computes the mean along segments of a tensor.

View aliases

Compat aliases for migration

tf.compat.v1.math.segment_mean, tf.compat.v1.segment_mean

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

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.

If the mean is empty for a given segment ID i, output[i] = 0.

For example:

c = tf.constant([[1.0,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.segment_mean(c, tf.constant([0, 0, 1]))
# ==> [[2.5, 2.5, 2.5, 2.5],
#      [5, 6, 7, 8]]

Args
`data`	A `Tensor`. Must be one of the following types: `float32`, `float64`, `int32`, `uint8`, `int16`, `int8`, `complex64`, `int64`, `qint8`, `quint8`, `qint32`, `bfloat16`, `uint16`, `complex128`, `half`, `uint32`, `uint64`.
`segment_ids`	A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor whose size is equal to the size 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`.

TensorFlow

tf.math / scalar_mul

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Args

Returns

TensorFlow

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tf.math / scalar_mul

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Args

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