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rand It returns a tensor filled with Random floats from a uniform distribution on the interval [0, 1]. Uniform distribution on [0, 1] means : Every number between 0 and 1 has an equal probability of being selected. It doesn't mean the numbers will be evenly spaced or look "uniform" when you look at a few samples. For example, torch.rand(4)=> tensor([0.7529, 0.8579, 0.6870, 0.0051]) Each of these..

sample_size = 10000 rand=np.random.rand(sample_size) randn=np.random.randn(sample_size) randint=np.random.randint(low=10, high=15, size=10) random_integers=np.random.random_integers(1, 6, 10) pdf, bins, patches = plt.hist(rand, bins=20, range=(0, 1), density=True) plt.title('rand') plt.show() pdf, bins, patches = plt.hist(randn, bins=20, range=(-4, 4), density=True) plt.title('randn') plt.show()..