Python – tensorflow.math.segment_mean()

• Last Updated : 12 Jun, 2020

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks.

segment_mean() is used to find the mean of elements in segments of a tensor.

Syntax: tensorflow.math.segment_mean(  data, segment_ids, name )

Parameter:

• data: It is a tensor. Allowed dtypes  are float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64.
• segment_ids: It’s 1-D tensor with sorted values. It’s size should be equal to  size of first dimension of data. Allowed dtypes are int32 and int64.
• name(optional): It defines the name for the operation.

Return: It returns a tensor of dtype as x.

Example 1:

Python3

 `# importing the library``import` `tensorflow as tf`` ` `# Initializing the input tensor``data ``=` `tf.constant([``1``, ``2``, ``3``])``segment_ids ``=` `tf.constant([``2``, ``2``, ``2``])`` ` `# Printing the input tensor``print``(``'data: '``, data)``print``(``'segment_ids: '``, segment_ids)`` ` `# Calculating result``res ``=` `tf.math.segment_mean(data, segment_ids)`` ` `# Printing the result``print``(``'Result: '``, res)`

Output:

```data:  tf.Tensor([1 2 3], shape=(3, ), dtype=int32)
segment_ids:  tf.Tensor([2 2 2], shape=(3, ), dtype=int32)
Result:  tf.Tensor([0 0 2], shape=(3, ), dtype=int32)

```

Example 2:

Python3

 `# importing the library``import` `tensorflow as tf`` ` `# Initializing the input tensor``data ``=` `tf.constant([[``1``, ``2``, ``3``], [``4``, ``5``, ``6``], [``7``, ``8``, ``9``]], dtype ``=` `float64)``segment_ids ``=` `tf.constant([``0``, ``0``, ``2``])`` ` `# Printing the input tensor``print``(``'data: '``, data)``print``(``'segment_ids: '``, segment_ids)`` ` `# Calculating result``res ``=` `tf.math.segment_mean(data, segment_ids)`` ` `# Printing the result``print``(``'Result: '``, res)`

Output:

```data:  tf.Tensor(
[[1. 2. 3.]
[4. 5. 6.]
[7. 8. 9.]], shape=(3, 3), dtype=float64)
segment_ids:  tf.Tensor([0 0 2], shape=(3, ), dtype=int32)
Result:  tf.Tensor(
[[2.5 3.5 4.5]
[0.  0.  0. ]
[7.  8.  9. ]], shape=(3, 3), dtype=float64)```

My Personal Notes arrow_drop_up