Understanding Tensor¶

In [1]:

import torch
torch.cuda.is_available()

import torch torch.cuda.is_available()

Out[1]:

False

In [21]:

import torch

tensor0d = torch.tensor(1)
tensor1d = torch.tensor([1, 2, 3])
tensor2d = torch.tensor([[1, 2], 
                         [3, 4]])
tensor3d = torch.tensor([[[1, 2], [3, 4]], 
                         [[5, 6], [7, 8]]])
tensor4d = torch.tensor([[[[1, 2], [3, 4]], [[5, 6], [7, 8]]]])

import torch tensor0d = torch.tensor(1) tensor1d = torch.tensor([1, 2, 3]) tensor2d = torch.tensor([[1, 2], [3, 4]]) tensor3d = torch.tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]) tensor4d = torch.tensor([[[[1, 2], [3, 4]], [[5, 6], [7, 8]]]])

In [3]:

tensor1d = torch.tensor([1, 2, 3])
print(tensor1d.dtype)

tensor1d = torch.tensor([1, 2, 3]) print(tensor1d.dtype)

torch.int64

In [4]:

floatvec = torch.tensor([1.0, 2.0, 3.0])
print(floatvec.dtype)

floatvec = torch.tensor([1.0, 2.0, 3.0]) print(floatvec.dtype)

torch.float32

In [7]:

floatvec = tensor1d.to(torch.float32)
print(tensor1d)
print(floatvec)
print(floatvec.dtype)

floatvec = tensor1d.to(torch.float32) print(tensor1d) print(floatvec) print(floatvec.dtype)

tensor([1, 2, 3])
tensor([1., 2., 3.])
torch.float32

In [8]:

tensor2d = torch.tensor([[1, 2, 3], 
                         [4, 5, 6]])
print(tensor2d)

tensor2d = torch.tensor([[1, 2, 3], [4, 5, 6]]) print(tensor2d)

tensor([[1, 2, 3],
        [4, 5, 6]])

In [22]:

print(tensor2d.shape)
print(tensor3d.shape)
print(tensor4d.shape)

print(tensor2d.shape) print(tensor3d.shape) print(tensor4d.shape)

torch.Size([2, 2])
torch.Size([2, 2, 2])
torch.Size([1, 2, 2, 2])

Reshape Tensor¶

In [11]:

print(tensor2d.reshape(3, 2))
print(tensor2d.view(3, 2))

print(tensor2d.reshape(3, 2)) print(tensor2d.view(3, 2))

tensor([[1, 2],
        [3, 4],
        [5, 6]])
tensor([[1, 2],
        [3, 4],
        [5, 6]])

Transpose Tensor¶

In [12]:

print(tensor2d.T)

print(tensor2d.T)

tensor([[1, 4],
        [2, 5],
        [3, 6]])

Matrix Multiplication¶

In [14]:

print(tensor2d.matmul(tensor2d.T))
print(tensor2d @ tensor2d.T)

print(tensor2d.matmul(tensor2d.T)) print(tensor2d @ tensor2d.T)

tensor([[14, 32],
        [32, 77]])
tensor([[14, 32],
        [32, 77]])

In [ ]: