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# Define probability distribution weights = torch.tensor([[0.0,1.0],# Probability of the second item category is 1 [0.5,0.5],# Equal probabilities for two item categories [0.2,0.3,0.5]])# Three item categories # Sampling without replacement result = torch.multinomial(weights, num_samples=2, replacement=False) print("Probability distribution:") print(weights) print("Results of sampling without replacement (sampling 2 items per row):") print(result) # Sampling with replacement result_with_replacement = torch.multinomial(weights, num_samples=5, replacement=True) print("Sampling with replacementResults (sampling 5 items per row):") print(result_with_replacement)

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Pytorch torch Reference Manual