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| torch.eq(a,b) torch.all(torch.eq(a,b))
>>> x = torch.arange(5) >>> x tensor([0, 1, 2, 3, 4]) >>> torch.gt(x,1) tensor([0, 0, 1, 1, 1], dtype=torch.uint8) >>> x>1 tensor([0, 0, 1, 1, 1], dtype=torch.uint8) >>> torch.ne(x,1) tensor([1, 0, 1, 1, 1], dtype=torch.uint8) >>> x!=1 tensor([1, 0, 1, 1, 1], dtype=torch.uint8) >>> torch.lt(x,3) tensor([1, 1, 1, 0, 0], dtype=torch.uint8) >>> x<3 tensor([1, 1, 1, 0, 0], dtype=torch.uint8) >>> torch.eq(x,3) tensor([0, 0, 0, 1, 0], dtype=torch.uint8) >>> x==3 tensor([0, 0, 0, 1, 0], dtype=torch.uint8)
>>> torch.nonzero(x) tensor([[1], [2], [3], [4]]) >>> x = torch.Tensor([[0.6, 0.0, 0.0, 0.0],[0.0, 0.4, 0.0, 0.0],[0.0, 0.0, 1.2, 0.0],[0.0, 0.0, 0.0,-0.4]]) >>> x tensor([[ 0.6000, 0.0000, 0.0000, 0.0000], [ 0.0000, 0.4000, 0.0000, 0.0000], [ 0.0000, 0.0000, 1.2000, 0.0000], [ 0.0000, 0.0000, 0.0000, -0.4000]]) >>> torch.nonzero(x) tensor([[0, 0], [1, 1], [2, 2], [3, 3]])
>>> x=torch.arange(12).view(3,4) >>> x tensor([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> (x>4).nonzero() tensor([[1, 1], [1, 2], [1, 3], [2, 0], [2, 1], [2, 2], [2, 3]])
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