# tf.cumsum(x, axis=0, exclusive=False, reverse=False, name=None)

### tf.cumsum(x, axis=0, exclusive=False, reverse=False, name=None)

See the guide: Math > Scan

Compute the cumulative sum of the tensor x along axis.

By default, this op performs an inclusive cumsum, which means that the first element of the input is identical to the first element of the output: prettyprint tf.cumsum([a, b, c]) ==> [a, a + b, a + b + c]

By setting the exclusive kwarg to True, an exclusive cumsum is performed instead: prettyprint tf.cumsum([a, b, c], exclusive=True) ==> [0, a, a + b]

By setting the reverse kwarg to True, the cumsum is performed in the opposite direction: prettyprint tf.cumsum([a, b, c], reverse=True) ==> [a + b + c, b + c, c] This is more efficient than using separate tf.reverse ops.

The reverse and exclusive kwargs can also be combined: prettyprint tf.cumsum([a, b, c], exclusive=True, reverse=True) ==> [b + c, c, 0]

#### Args:

• x: A Tensor. Must be one of the following types: float32, float64, int64, int32, uint8, uint16, int16, int8, complex64, complex128, qint8, quint8, qint32, half. axis: A Tensor of type int32 (default: 0). reverse: A bool (default: False). name: A name for the operation (optional).

#### Returns:

A Tensor. Has the same type as x.

Defined in tensorflow/python/ops/math_ops.py.