pfhedge.stochastic.randn_antithetic¶

pfhedge.stochastic.randn_antithetic(*size, dtype=None, device=None, dim=0, shuffle=True)[source]¶

Returns a tensor filled with random numbers obtained by an antithetic sampling.

The output should be a normal distribution with mean 0 and variance 1 (also called the standard normal distribution).

Parameters

size (int…) – a sequence of integers defining the shape of the output tensor. Can be a variable number of arguments or a collection like a list or tuple.
dtype (torch.dtype, optional) – The desired data type of returned tensor. Default: If None, uses a global default (see torch.set_default_tensor_type()).
device (torch.device, optional) – The desired device of returned tensor. Default: If None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.

Returns

torch.Tensor

Examples

>>> from pfhedge.stochastic import randn_antithetic
>>>
>>> _ = torch.manual_seed(42)
>>> output = randn_antithetic(4, 3)
>>> output
tensor([[-0.3367, -0.1288, -0.2345],
        [ 0.2303, -1.1229, -0.1863],
        [-0.2303,  1.1229,  0.1863],
        [ 0.3367,  0.1288,  0.2345]])
>>> output.mean(dim=0).allclose(torch.zeros(3), atol=1e-07, rtol=0.0)
True