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

[]
[]