pytorch: tensor類型的構(gòu)建與相互轉(zhuǎn)換實例

更新時間：2018年07月26日 14:21:35 作者：JNingWei

今天小編就為大家分享一篇pytorch: tensor類型的構(gòu)建與相互轉(zhuǎn)換實例，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧

Summary

主要包括以下三種途徑：

使用獨立的函數(shù)；

使用torch.type()函數(shù)；

使用type_as(tesnor)將張量轉(zhuǎn)換為給定類型的張量。

使用獨立函數(shù)

import torch

tensor = torch.randn(3, 5)
print(tensor)

# torch.long() 將tensor投射為long類型
long_tensor = tensor.long()
print(long_tensor)

# torch.half()將tensor投射為半精度浮點類型
half_tensor = tensor.half()
print(half_tensor)

# torch.int()將該tensor投射為int類型
int_tensor = tensor.int()
print(int_tensor)

# torch.double()將該tensor投射為double類型
double_tensor = tensor.double()
print(double_tensor)

# torch.float()將該tensor投射為float類型
float_tensor = tensor.float()
print(float_tensor)

# torch.char()將該tensor投射為char類型
char_tensor = tensor.char()
print(char_tensor)

# torch.byte()將該tensor投射為byte類型
byte_tensor = tensor.byte()
print(byte_tensor)

# torch.short()將該tensor投射為short類型
short_tensor = tensor.short()
print(short_tensor)

-0.5841 -1.6370 0.1353 0.6334 -3.0761
-0.2628 0.1245 0.8626 0.4095 -0.3633
 1.3605 0.5055 -2.0090 0.8933 -0.6267
[torch.FloatTensor of size 3x5]


 0 -1 0 0 -3
 0 0 0 0 0
 1 0 -2 0 0
[torch.LongTensor of size 3x5]


-0.5840 -1.6367 0.1353 0.6333 -3.0762
-0.2627 0.1245 0.8628 0.4094 -0.3633
 1.3604 0.5054 -2.0098 0.8936 -0.6265
[torch.HalfTensor of size 3x5]


 0 -1 0 0 -3
 0 0 0 0 0
 1 0 -2 0 0
[torch.IntTensor of size 3x5]


-0.5841 -1.6370 0.1353 0.6334 -3.0761
-0.2628 0.1245 0.8626 0.4095 -0.3633
 1.3605 0.5055 -2.0090 0.8933 -0.6267
[torch.DoubleTensor of size 3x5]


-0.5841 -1.6370 0.1353 0.6334 -3.0761
-0.2628 0.1245 0.8626 0.4095 -0.3633
 1.3605 0.5055 -2.0090 0.8933 -0.6267
[torch.FloatTensor of size 3x5]


 0 -1 0 0 -3
 0 0 0 0 0
 1 0 -2 0 0
[torch.CharTensor of size 3x5]


 0 255 0 0 253
 0 0 0 0 0
 1 0 254 0 0
[torch.ByteTensor of size 3x5]


 0 -1 0 0 -3
 0 0 0 0 0
 1 0 -2 0 0
[torch.ShortTensor of size 3x5]

其中，torch.Tensor、torch.rand、torch.randn 均默認生成 torch.FloatTensor型：

import torch

tensor = torch.Tensor(3, 5)
assert isinstance(tensor, torch.FloatTensor)

tensor = torch.rand(3, 5)
assert isinstance(tensor, torch.FloatTensor)

tensor = torch.randn(3, 5)
assert isinstance(tensor, torch.FloatTensor)

使用torch.type()函數(shù)

type(new_type=None, async=False)

import torch

tensor = torch.randn(3, 5)
print(tensor)

int_tensor = tensor.type(torch.IntTensor)
print(int_tensor)

-0.4449 0.0332 0.5187 0.1271 2.2303
 1.3961 -0.1542 0.8498 -0.3438 -0.2834
-0.5554 0.1684 1.5216 2.4527 0.0379
[torch.FloatTensor of size 3x5]


 0 0 0 0 2
 1 0 0 0 0
 0 0 1 2 0
[torch.IntTensor of size 3x5]

使用type_as(tesnor)將張量轉(zhuǎn)換為給定類型的張量

import torch

tensor_1 = torch.FloatTensor(5)

tensor_2 = torch.IntTensor([10, 20])
tensor_1 = tensor_1.type_as(tensor_2)
assert isinstance(tensor_1, torch.IntTensor)

以上這篇pytorch: tensor類型的構(gòu)建與相互轉(zhuǎn)換實例就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持腳本之家。

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