prod( x, axis=None, keepdim=False, dtype=None, name=None )
Compute the product of tensor elements over the given axis.
x (Tensor) – The input tensor, its data type should be float32, float64, int32, int64.
axis (int|list|tuple, optional) – The axis along which the product is computed. If
None, multiply all elements of x and return a Tensor with a single element, otherwise must be in the range \([-x.ndim, x.ndim)\). If \(axis[i]<0\), the axis to reduce is \(x.ndim + axis[i]\). Default is None.
dtype (str|np.dtype, optional) – The desired date type of returned tensor, can be float32, float64, int32, int64. If specified, the input tensor is casted to dtype before operator performed. This is very useful for avoiding data type overflows. The default value is None, the dtype of output is the same as input Tensor x.
keepdim (bool, optional) – Whether to reserve the reduced dimension in the output Tensor. The result tensor will have one fewer dimension than the input unless keepdim is true. Default is False.
name (string, optional) – The default value is None. Normally there is no need for user to set this property. For more information, please refer to Name .
Tensor, result of product on the specified dim of input tensor.
ValueError – The
dtypemust be float32, float64, int32 or int64.
TypeError – The type of
axismust be int, list or tuple.
import paddle # the axis is a int element x = paddle.to_tensor([[0.2, 0.3, 0.5, 0.9], [0.1, 0.2, 0.6, 0.7]]) out1 = paddle.prod(x) # [0.0002268] out2 = paddle.prod(x, -1) # [0.027 0.0084] out3 = paddle.prod(x, 0) # [0.02 0.06 0.3 0.63] out4 = paddle.prod(x, 0, keepdim=True) # [[0.02 0.06 0.3 0.63]] out5 = paddle.prod(x, 0, dtype='int64') # [0 0 0 0] # the axis is list y = paddle.to_tensor([[[1.0, 2.0], [3.0, 4.0]], [[5.0, 6.0], [7.0, 8.0]]]) out6 = paddle.prod(y, [0, 1]) # [105. 384.] out7 = paddle.prod(y, (1, 2)) # [ 24. 1680.]