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Compute the cumulative product of the tensor x
along axis
.
tf.math.cumprod( x, axis=0, exclusive=False, reverse=False, name=None )
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 | 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 cumprod. |
reverse | A bool (default: False). |
name | A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as x . |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/math/cumprod