pytorch tensor的创建

一、使用实际的数据创建tensor

1、使用list

tensor = torch.tensor([[2, 3, 4],[5, 6, 7]])
print(tensor)

tensor([[2, 3, 4],
        [5, 6, 7]])

2、使用numpy

np_array = np.array([[1,2,3],[1,2,3]])
np_to_tensor = torch.from_numpy(np_array)
print(np_to_tensor)

二、使用维度来创建tensor

1、创建一个float类型的tesor

floattenor1 = torch.FloatTensor(2, 3)
print(floattenor1)

2、创建一个int类型的tensor

inttensor = torch.IntTensor(2, 3)
print(inttensor)

3、创建一个数值在[0,1]之间的tensor

randTensor = torch.rand(3, 3)

4、创建一个在规定范围中随机取值的tensor

randIntTensor = torch.randint(1, 10, [3, 3])
print(randIntTensor)

5、创建一个在标准正太中取值的tensor

randn = torch.randn(3, 3)
print(randn)

6、创建一个值都相同的tensor

fullTensor = torch.full([2, 3],4)
print(fullTensor)

7、创建一个rang(a,b)的tensor

arangeTensor = torch.arange(1,10)
print(arangeTensor)

8、创建全为0或者全为1的tensor

oneTensor = torch.ones(2, 3)
print(oneTensor)
zerosTensor = torch.zeros(2, 3)
print(zerosTensor)

三、tensor相关的属性

1、tensor的类型
tensor.type()

2、tensor的形状
tensor.size()

3、tenor某维的大小
tenor.shape[0]
tesnor.shape[1]

c = torch.tensor([[1, 2, 3], [1, 2, 3]])
print(c)
print(c.shape)
print(c.shape[0])
print(c.shape[1])
print(len(c.shape))
print(c.size())