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Machine-Learning/learning-pytorch/tensor_tutorial.py
T
2020-10-30 19:25:38 +01:00

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Python
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#!/usr/bin/env python
from __future__ import print_function
import torch
# x = torch.empty(5, 3)
# x = torch.rand(5, 3)
# x = torch.zeros(5, 3, dtype=torch.long)
# x = torch.tensor([5.5, 3])
# x = x.new_ones(5, 3, dtype=torch.double)
# print(x)
# x = torch.randn_like(x, dtype=torch.float)
# print(x.size())
# y = torch.rand(5, 3)
# print(x+y)
# print(torch.add(x, y))
# result = torch.empty(5, 3)
# torch.add(x, y, out=result)
# print(result)
# print(x[:, 1])
# x = torch.randn(4, 4)
# y = x.view(16)
# z = x.view(-1, 8) # the size -1 is inferred from other dimensions
# print(x.size(), y.size(), z.size())
x = torch.randn(1)
print(x)
print(x.item())
a = torch.ones(5)
print(a)