pytorch1.60 torch.nn在pycharm中無(wú)法自動(dòng)智能提示的解決

更新時(shí)間：2024年02月26日 11:13:46 作者：雪的期許

這篇文章主要介紹了pytorch1.60 torch.nn在pycharm中無(wú)法自動(dòng)智能提示的解決方案,具有很好的參考價(jià)值,希望對(duì)大家有所幫助,如有錯(cuò)誤或未考慮完全的地方,望不吝賜教

問(wèn)題描述

安裝了pytorch最新版本1.6之后，在pycharm中編輯python代碼時(shí)，輸入torch.nn.看不到提示了，比如torch.nn.MSELoss()。

而在1.4及以前的版本中，直接輸入torch.nn.就會(huì)自動(dòng)提示出很多torch.nn.modules中的API。

該問(wèn)題的討論在前幾年有過(guò)不少，但都是基于老版本，經(jīng)過(guò)嘗試，對(duì)于1.6版本是無(wú)效的。

原因分析

pycharm的自動(dòng)提示是根據(jù)第三方包的每個(gè)文件夾下的__init__.pyi文件來(lái)顯示的，只有__init__.pyi中import了的API才會(huì)被pycharm自動(dòng)提示。

首先對(duì)pytorch.nn模塊要知道，問(wèn)題描述中提到的MSELoss等眾多函數(shù)，真實(shí)位置是torch.nn.modules.MSELoss()，你直接調(diào)用這個(gè)真實(shí)位置是可以自動(dòng)提示的。

但是1.4及以前的版本中大家都熟悉了直接用nn.MSELoss()這樣調(diào)用，如何讓1.6版本也能像歷史版本一樣提示呢？

基于此，我對(duì)比了1.6和1.4的區(qū)別。

在torch 1.6版本包存放位置下，torch/nn/下是有__init__.pyi的，里面有一行from .modules import *，說(shuō)明nn模塊是可以直接調(diào)用子模塊modules中的API的，所以直接調(diào)用nn.MSELoss()不會(huì)報(bào)錯(cuò)，只是不會(huì)自動(dòng)提示。

然后在進(jìn)入torch/nn/modules/發(fā)現(xiàn)，1.6版本中缺少__init__.pyi文件，所以在pycharm輸入nn.的時(shí)候并不會(huì)提示子模塊modules中的API。

解決方案

從pytorch 1.4版本中復(fù)制一份__init__.pyi文件到1.6版本的依賴包的相同目錄下。

具體位置是：

{你的第三方包存放位置}/Lib/site-packages/torch/nn/modules/__init__.pyi

然后就可以在pycharm中愉快使用nn.自動(dòng)提示了。其他模塊不自動(dòng)提示的，解決方法類同。

補(bǔ)充

關(guān)于解決方案中第三方包存放位置不知道的，可以在pycharm左側(cè)項(xiàng)目目錄結(jié)構(gòu)中看到一項(xiàng)External Libraries，點(diǎn)開(kāi)它，你就能直接找到Lib/site-packages/torch/nn/modules/，從而不必去資源管理器找。

附件 __init__.pyi

from .module import Module as Module
from .activation import CELU as CELU, ELU as ELU, GLU as GLU, GELU as GELU, Hardshrink as Hardshrink, \
    Hardtanh as Hardtanh, LeakyReLU as LeakyReLU, LogSigmoid as LogSigmoid, LogSoftmax as LogSoftmax, PReLU as PReLU, \
    RReLU as RReLU, ReLU as ReLU, ReLU6 as ReLU6, SELU as SELU, Sigmoid as Sigmoid, Softmax as Softmax, \
    Softmax2d as Softmax2d, Softmin as Softmin, Softplus as Softplus, Softshrink as Softshrink, Softsign as Softsign, \
    Tanh as Tanh, Tanhshrink as Tanhshrink, Threshold as Threshold
from .adaptive import AdaptiveLogSoftmaxWithLoss as AdaptiveLogSoftmaxWithLoss
from .batchnorm import BatchNorm1d as BatchNorm1d, BatchNorm2d as BatchNorm2d, BatchNorm3d as BatchNorm3d, \
    SyncBatchNorm as SyncBatchNorm
from .container import Container as Container, ModuleDict as ModuleDict, ModuleList as ModuleList, \
    ParameterDict as ParameterDict, ParameterList as ParameterList, Sequential as Sequential
from .conv import Conv1d as Conv1d, Conv2d as Conv2d, Conv3d as Conv3d, ConvTranspose1d as ConvTranspose1d, \
    ConvTranspose2d as ConvTranspose2d, ConvTranspose3d as ConvTranspose3d
from .distance import CosineSimilarity as CosineSimilarity, PairwiseDistance as PairwiseDistance
from .dropout import AlphaDropout as AlphaDropout, Dropout as Dropout, Dropout2d as Dropout2d, Dropout3d as Dropout3d, \
    FeatureAlphaDropout as FeatureAlphaDropout
from .fold import Fold as Fold, Unfold as Unfold
from .instancenorm import InstanceNorm1d as InstanceNorm1d, InstanceNorm2d as InstanceNorm2d, \
    InstanceNorm3d as InstanceNorm3d
from .linear import Bilinear as Bilinear, Identity as Identity, Linear as Linear
from .loss import BCELoss as BCELoss, BCEWithLogitsLoss as BCEWithLogitsLoss, CTCLoss as CTCLoss, \
    CosineEmbeddingLoss as CosineEmbeddingLoss, CrossEntropyLoss as CrossEntropyLoss, \
    HingeEmbeddingLoss as HingeEmbeddingLoss, KLDivLoss as KLDivLoss, L1Loss as L1Loss, MSELoss as MSELoss, \
    MarginRankingLoss as MarginRankingLoss, MultiLabelMarginLoss as MultiLabelMarginLoss, \
    MultiLabelSoftMarginLoss as MultiLabelSoftMarginLoss, MultiMarginLoss as MultiMarginLoss, NLLLoss as NLLLoss, \
    NLLLoss2d as NLLLoss2d, PoissonNLLLoss as PoissonNLLLoss, SmoothL1Loss as SmoothL1Loss, \
    SoftMarginLoss as SoftMarginLoss, TripletMarginLoss as TripletMarginLoss
from .module import Module as Module
from .normalization import CrossMapLRN2d as CrossMapLRN2d, GroupNorm as GroupNorm, LayerNorm as LayerNorm, \
    LocalResponseNorm as LocalResponseNorm
from .padding import ConstantPad1d as ConstantPad1d, ConstantPad2d as ConstantPad2d, ConstantPad3d as ConstantPad3d, \
    ReflectionPad1d as ReflectionPad1d, ReflectionPad2d as ReflectionPad2d, ReplicationPad1d as ReplicationPad1d, \
    ReplicationPad2d as ReplicationPad2d, ReplicationPad3d as ReplicationPad3d, ZeroPad2d as ZeroPad2d
from .pixelshuffle import PixelShuffle as PixelShuffle
from .pooling import AdaptiveAvgPool1d as AdaptiveAvgPool1d, AdaptiveAvgPool2d as AdaptiveAvgPool2d, \
    AdaptiveAvgPool3d as AdaptiveAvgPool3d, AdaptiveMaxPool1d as AdaptiveMaxPool1d, \
    AdaptiveMaxPool2d as AdaptiveMaxPool2d, AdaptiveMaxPool3d as AdaptiveMaxPool3d, AvgPool1d as AvgPool1d, \
    AvgPool2d as AvgPool2d, AvgPool3d as AvgPool3d, FractionalMaxPool2d as FractionalMaxPool2d, \
    FractionalMaxPool3d as FractionalMaxPool3d, LPPool1d as LPPool1d, LPPool2d as LPPool2d, MaxPool1d as MaxPool1d, \
    MaxPool2d as MaxPool2d, MaxPool3d as MaxPool3d, MaxUnpool1d as MaxUnpool1d, MaxUnpool2d as MaxUnpool2d, \
    MaxUnpool3d as MaxUnpool3d
from .rnn import GRU as GRU, GRUCell as GRUCell, LSTM as LSTM, LSTMCell as LSTMCell, RNN as RNN, RNNBase as RNNBase, \
    RNNCell as RNNCell, RNNCellBase as RNNCellBase
from .sparse import Embedding as Embedding, EmbeddingBag as EmbeddingBag
from .upsampling import Upsample as Upsample, UpsamplingBilinear2d as UpsamplingBilinear2d, \
    UpsamplingNearest2d as UpsamplingNearest2d