Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://docs.pytorch.org/docs/stable/generated/torch.cumprod.html below:

torch.cumprod — PyTorch 2.7 documentation

torch.cumprod(input, dim, *, dtype=None, out=None) → Tensor¶

Returns the cumulative product of elements of input in the dimension dim.

For example, if input is a vector of size N, the result will also be a vector of size N, with elements.

y i = x 1 × x 2 × x 3 × ⋯ × x i y_i = x_1 \times x_2\times x_3\times \dots \times x_i yi​=x1​×x2​×x3​×⋯×xi​

Parameters

• input (Tensor) – the input tensor.

• dim (int) – the dimension to do the operation over

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.

• out (Tensor, optional) – the output tensor.

Example:

>>> a = torch.randn(10)
>>> a
tensor([ 0.6001,  0.2069, -0.1919,  0.9792,  0.6727,  1.0062,  0.4126,
        -0.2129, -0.4206,  0.1968])
>>> torch.cumprod(a, dim=0)
tensor([ 0.6001,  0.1241, -0.0238, -0.0233, -0.0157, -0.0158, -0.0065,
         0.0014, -0.0006, -0.0001])

>>> a[5] = 0.0
>>> torch.cumprod(a, dim=0)
tensor([ 0.6001,  0.1241, -0.0238, -0.0233, -0.0157, -0.0000, -0.0000,
         0.0000, -0.0000, -0.0000])

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4