Help protect the Great Barrier Reef with TensorFlow on Kaggle

# tf.math.cumsum

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: For example:

````# tf.cumsum([a, b, c])   # [a, a + b, a + b + c]`
`x = tf.constant([2, 4, 6, 8])`
`tf.cumsum(x)`
`<tf.Tensor: shape=(4,), dtype=int32,`
`numpy=array([ 2,  6, 12, 20], dtype=int32)>`
```
````# using varying `axis` values`
`y = tf.constant([[2, 4, 6, 8], [1,3,5,7]])`
`tf.cumsum(y, axis=0)`
`<tf.Tensor: shape=(2, 4), dtype=int32, numpy=`
`array([[ 2,  4,  6,  8],`
`       [ 3,  7, 11, 15]], dtype=int32)>`
`tf.cumsum(y, axis=1)`
`<tf.Tensor: shape=(2, 4), dtype=int32, numpy=`
`array([[ 2,  6, 12, 20],`
`       [ 1,  4,  9, 16]], dtype=int32)>`
```

By setting the `exclusive` kwarg to `True`, an exclusive cumsum is performed instead:

````# tf.cumsum([a, b, c], exclusive=True)  => [0, a, a + b]`
`x = tf.constant([2, 4, 6, 8])`
`tf.cumsum(x, exclusive=True)`
`<tf.Tensor: shape=(4,), dtype=int32,`
`numpy=array([ 0,  2,  6, 12], dtype=int32)>`
```

By setting the `reverse` kwarg to `True`, the cumsum is performed in the opposite direction:

````# tf.cumsum([a, b, c], reverse=True)  # [a + b + c, b + c, c]`
`x = tf.constant([2, 4, 6, 8])`
`tf.cumsum(x, reverse=True)`
`<tf.Tensor: shape=(4,), dtype=int32,`
`numpy=array([20, 18, 14,  8], dtype=int32)>`
```

This is more efficient than using separate `tf.reverse` ops. The `reverse` and `exclusive` kwargs can also be combined:

````# tf.cumsum([a, b, c], exclusive=True, reverse=True)  # [b + c, c, 0]`
`x = tf.constant([2, 4, 6, 8])`
`tf.cumsum(x, exclusive=True, reverse=True)`
`<tf.Tensor: shape=(4,), dtype=int32,`
`numpy=array([18, 14,  8,  0], dtype=int32)>`
```

`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). Must be in the range `[-rank(x), rank(x))`.
`exclusive` If `True`, perform exclusive cumsum.
`reverse` A `bool` (default: False).
`name` A name for the operation (optional).

A `Tensor`. Has the same type as `x`.

[]
[]