Numpy Torch对比Pytorch
import torch
import numpy as np
numpy_data = np.arange(6).reshape([2, 3])
torch_data = torch.from_numpy(numpy_data)
tensor2array = torch_data.numpy()
print(
'\nnumpy_data:', numpy_data,
'\ntorch_data:', torch_data,
'\ntensor2array:', tensor2array,
)
'''
运行结果:
numpy_data: [[0 1 2]
[3 4 5]]
torch_data: tensor([[0, 1, 2],
[3, 4, 5]], dtype=torch.int32)
tensor2array: [[0 1 2]
[3 4 5]]
'''
import torch
import numpy as np
data = [-1, -2, 1, 2]
tensor = torch.FloatTensor(data)
print(
'\nabs',
'\nnumpy', np.abs(data),
'\ntorch', torch.abs(tensor),
)
print(
'\nsin',
'\nnumpy', np.sin(data),
'\ntorch', torch.sin(tensor),
)
'''
运行结果:
abs
numpy [1 2 1 2]
torch tensor([1., 2., 1., 2.])
sin
numpy [-0.84147098 -0.90929743 0.84147098 0.90929743]
torch tensor([-0.8415, -0.9093, 0.8415, 0.9093])
'''
import torch
import numpy as np
data = [[-1, -2], [1, 2]]
tensor = torch.FloatTensor(data)
print(
'\nnumpy:', np.matmul(data, data),
'\ntorch:', torch.mm(tensor, tensor),
)
'''
运行结果:
numpy: [[-1 -2]
[ 1 2]]
torch: tensor([[-1., -2.],
[ 1., 2.]])
'''