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MMLU / Which PyTorch 1.8 command(s) produce 10×5 Gaussian matrix with each…

Problem

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question

Which PyTorch 1.8 command(s) produce 10×510\times 5 Gaussian matrix with each entry i.i.d. sampled from N(μ=5,σ2=16)\mathcal{N}(\mu=5,\sigma^2=16) and a 10×1010\times 10 uniform matrix with each entry i.i.d. sampled from U[−1,1)U[-1,1)?
Plain-text mathematical notation (without MathML)
Which PyTorch 1.8 command(s) produce 10×5 Gaussian matrix with each entry i.i.d. sampled from N(μ=5,σ²=16) and a 10×10 uniform matrix with each entry i.i.d. sampled from U[−1,1)?
Original LaTeX notation
Which PyTorch 1.8 command(s) produce $10\times 5$ Gaussian matrix with each entry i.i.d. sampled from $\mathcal{N}(\mu=5,\sigma^2=16)$ and a $10\times 10$ uniform matrix with each entry i.i.d. sampled from $U[-1,1)$?

choices

  1. \texttt{5 + torch.randn(10,5) * 16} ; \texttt{torch.rand(10,10,low=-1,high=1)}
  2. \texttt{5 + torch.randn(10,5) * 16} ; \texttt{(torch.rand(10,10) - 0.5) / 0.5}
  3. \texttt{5 + torch.randn(10,5) * 4} ; \texttt{2 * torch.rand(10,10) - 1}
  4. \texttt{torch.normal(torch.ones(10,5)*5,torch.ones(5,5)*16)} ; \texttt{2 * torch.rand(10,10) - 1}

subject

machine_learning

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Source and history

task_id
d26ef7f0-bb18-5779-977d-4bf876d6f02c
task_key
all--test--d26ef7f0-bb18-5779-977d-4bf876d6f02c
task_revision_id
1
config / split
all / test

Official source

initial import