pytorch白话入门笔记1.1-tensor和numpy array数据转化及运算

# tensor和numpy array数据转化及其对比

代码：

import torch
import numpy as np

# numpy数据转换为torch数据
np_data = np.arange(6).reshape((2,3))
torch_data = torch.from_numpy(np_data)
# torch 数据转化为numpy数据
tensor2array = torch_data.numpy()

print(
    '\nnumpy',np_data,
    '\ntorch',torch_data,
    '\ntensor2array',tensor2array,
)

运行结果：

numpy [[0 1 2]
 [3 4 5]] 
torch tensor([[0, 1, 2],
        [3, 4, 5]], dtype=torch.int32) 
tensor2array [[0 1 2]
 [3 4 5]]

Process finished with exit code 0

# abs

代码：

import torch
import numpy as np

data = [-100,-200,-4,-99,8,9]
tensor = torch.FloatTensor(data)

print(
    '\nabs',
    '\nnumpy',np.abs(data),
    '\ntorch',torch.abs(tensor),
)

运行结果：

abs 
numpy [100 200   4  99   8   9] 
torch tensor([100., 200.,   4.,  99.,   8.,   9.])

Process finished with exit code 0

# sin

代码（类似abs）

import torch
import numpy as np

data = [-100,-200,-4,-99,8,9]
tensor = torch.FloatTensor(data)

print(
    '\nsin',
    '\nnumpy',np.sin(data),
    '\ntorch',torch.sin(tensor),
)

运行结果：

sin 
numpy [0.50636564 0.8732973  0.7568025  0.99920683 0.98935825 0.41211849] 
torch tensor([0.5064, 0.8733, 0.7568, 0.9992, 0.9894, 0.4121])

Process finished with exit code 0

# mean(类似abs)

代码：

import torch
import numpy as np

data = [-100,-200,-4,-99,8,9]
tensor = torch.FloatTensor(data)

print(
    '\nmean',
    '\nnumpy',np.mean(data),
    '\ntorch',torch.mean(tensor),
)

运行结果：

mean 
numpy -64.33333333333333 
torch tensor(-64.3333)

Process finished with exit code 0

# 矩阵相乘1

代码：

import torch
import numpy as np

data = [[2,4],[6,8]]
tensor = torch.FloatTensor(data)

print(
    '\nmul',#矩阵相乘
    '\nnumpy:',np.matmul(data,data),
    '\ntorch:',torch.mm(tensor,tensor),
)

运行结果：

mul 
numpy: [[28 40]
 [60 88]] 
torch: tensor([[28., 40.],
        [60., 88.]])

Process finished with exit code 0

# 矩阵相乘2（对应相乘dot）

代码：

import torch
import numpy as np

#dot
data = [2,4,6,8]
data = np.array(data)
tensor = torch.FloatTensor(data)

print(
    '\ndot',#矩阵相乘
    '\nnumpy:',data.dot(data),
    '\ntorch:',tensor.dot(tensor),
)

运行结果：

dot 
numpy: 120 
torch: tensor(120.)

Process finished with exit code 0