# Python – tensorflow.math.cumsum()

• Last Updated : 20 Jul, 2021

TensorFlow is open-source Python library designed by Google to develop Machine Learning models and deep learning  neural networks. cumsum() is used to calculate the cumulative sum of input tensor.

Syntax: tensorflow.math.cumsum(x, axis, exclusive, reverse, name)

Parameters:

• x: It’s the input tensor. Allowed dtype for this tensor are  float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half.
• axis(optional): It’s a tensor of type int32. It’s value should  be in the range  A Tensor of type int32 (default: 0). Must be in the range [-rank(x), rank(x)).  Default value is 0.
• exclusive(optional): It’s of type bool. Default value is False and if set to true then the output for input [a, b, c] will be [0, a, a+b].
• reverse(optional): It’s of type bool. Default value is False and if set to true then the output for input [a, b, c] will be [a+b+c, a+b, a].
• name(optional): It’s defines the name for the operation.

Returns: It returns a tensor of same dtype as x.

Example 1:

## Python3

 `# importing the library` `import` `tensorflow as tf`   `# initializing the input` `a ``=` `tf.constant([``1``, ``2``, ``4``, ``5``], dtype ``=` `tf.int32)  `   `# Printing the input` `print``(``"Input: "``,a)`   `# Cumulative sum` `res  ``=` `tf.math.cumsum(a)`   `# Printing the result` `print``(``"Output: "``,res)`

Output:

```Input:  tf.Tensor([1 2 4 5], shape=(4,), dtype=int32)
Output:  tf.Tensor([ 1  3  7 12], shape=(4,), dtype=int32)```

Example 2: In this example both reverse and exclusive are set to True.

## Python3

 `# importing the library` `import` `tensorflow as tf`   `# initializing the input` `a ``=` `tf.constant([``2``, ``3``, ``4``, ``5``], dtype ``=` `tf.int32)  `   `# Printing the input` `print``(``"Input: "``,a)`   `# Cumulative sum` `res  ``=` `tf.math.cumsum(a, reverse ``=` `True``, exclusive ``=` `True``)`   `# Printing the result` `print``(``"Output: "``,res)`

Output:

```Input:  tf.Tensor([2 3 4 5], shape=(4,), dtype=int32)
Output:  tf.Tensor([12  9  5  0], shape=(4,), dtype=int32)```

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