# tf.math.reduce_prod

Computes `tf.math.multiply` of elements across dimensions of a tensor.

This is the reduction operation for the elementwise `tf.math.multiply` op.

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.

``````>>> x = tf.constant([[1., 2.], [3., 4.]])
>>> tf.math.reduce_prod(x)
<tf.Tensor: shape=(), dtype=float32, numpy=24.>
>>> tf.math.reduce_prod(x, 0)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([3., 8.], dtype=float32)>
>>> tf.math.reduce_prod(x, 1)
<tf.Tensor: shape=(2,), dtype=float32, numpy=array([2., 12.],
dtype=float32)>
``````

`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).

The reduced tensor.

## numpy compatibility

Equivalent to np.prod

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