# tf.math.reduce_prod

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

### Used in the notebooks

Used in the guide Used in the tutorials

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.

#### For example:

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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