torch.prod — PyTorch 2.7 documentation (original) (raw)
torch.prod(input: Tensor, *, dtype: Optional[_dtype]) → Tensor¶
Returns the product of all elements in the input
tensor.
Parameters
input (Tensor) – the input tensor.
Keyword Arguments
dtype (torch.dtype, optional) – the desired data type of returned tensor. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. Default: None.
Example:
a = torch.randn(1, 3) a tensor([[-0.8020, 0.5428, -1.5854]]) torch.prod(a) tensor(0.6902)
torch.prod(input, dim, keepdim=False, *, dtype=None) → Tensor
Returns the product of each row of the input
tensor in the given dimension dim
.
If keepdim
is True
, the output tensor is of the same size as input
except in the dimension dim
where it is of size 1. Otherwise, dim
is squeezed (see torch.squeeze()), resulting in the output tensor having 1 fewer dimension than input
.
Parameters
- input (Tensor) – the input tensor.
- dim (int) – the dimension to reduce.
- keepdim (bool) – whether the output tensor has
dim
retained or not.
Keyword Arguments
dtype (torch.dtype, optional) – the desired data type of returned tensor. If specified, the input tensor is casted to dtype before the operation is performed. This is useful for preventing data type overflows. Default: None.
Example:
a = torch.randn(4, 2) a tensor([[ 0.5261, -0.3837], [ 1.1857, -0.2498], [-1.1646, 0.0705], [ 1.1131, -1.0629]]) torch.prod(a, 1) tensor([-0.2018, -0.2962, -0.0821, -1.1831])