Aliases:
tf.cumprodtf.math.cumprod
tf.math.cumprod(
x,
axis=0,
exclusive=False,
reverse=False,
name=None
)
Defined in tensorflow/python/ops/math_ops.py.
Compute the cumulative product of the tensor x along axis.
By default, this op performs an inclusive cumprod, which means that the first element of the input is identical to the first element of the output:
tf.math.cumprod([a, b, c]) # [a, a * b, a * b * c]
By setting the exclusive kwarg to True, an exclusive cumprod is
performed
instead:
tf.math.cumprod([a, b, c], exclusive=True) # [1, a, a * b]
By setting the reverse kwarg to True, the cumprod is performed in the
opposite direction:
tf.math.cumprod([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:
tf.math.cumprod([a, b, c], exclusive=True, reverse=True) # [b * c, c, 1]
Args:
x: ATensor. Must be one of the following types:float32,float64,int64,int32,uint8,uint16,int16,int8,complex64,complex128,qint8,quint8,qint32,half.axis: ATensorof typeint32(default: 0). Must be in the range[-rank(x), rank(x)).exclusive: IfTrue, perform exclusive cumprod.reverse: Abool(default: False).name: A name for the operation (optional).
Returns:
A Tensor. Has the same type as x.