tf.math.reduce

Computes the product of elements across dimensions of a tensor.

View aliases

Main aliases

tf.reduce_prod

tf.math.reduce_prod(
    input_tensor, axis=None, keepdims=False, name=None
)

Used in the notebooks

Used in the guide	Used in the tutorials
Advanced Automatic Differentiation	TFP Release Notes notebook (0.12.1) TensorFlow Distributions: A Gentle Introduction

Reduces input_tensor along the dimensions given in axis. Unless keepdims is true, the rank of the tensor is reduced by 1 for each entry in axis. If keepdims is true, the reduced dimensions are retained with length 1.

If axis is None, all dimensions are reduced, and a tensor with a single element is returned.

Args
`input_tensor`	The tensor to reduce. Should have numeric type.
`axis`	The dimensions to reduce. If `None` (the default), reduces all dimensions. Must be in the range `[-rank(input_tensor), rank(input_tensor))`.
`keepdims`	If true, retains reduced dimensions with length 1.
`name`	A name for the operation (optional).

Returns
The reduced tensor.

Numpy Compatibility

Equivalent to np.prod

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf.math / reduce_mean

View aliases

Used in the notebooks

Args

Returns

Numpy Compatibility