pytorch1.60 torch.nn在pycharm中無法自動智能提示的解決
問題描述
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.就會自動提示出很多torch.nn.modules中的API。
該問題的討論在前幾年有過不少,但都是基于老版本,經(jīng)過嘗試,對于1.6版本是無效的。
原因分析
pycharm的自動提示是根據(jù)第三方包的每個(gè)文件夾下的__init__.pyi文件來顯示的,只有__init__.pyi中import了的API才會被pycharm自動提示。
首先對pytorch.nn模塊要知道,問題描述中提到的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()不會報(bào)錯,只是不會自動提示。
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.自動提示了。其他模塊不自動提示的,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
總結(jié)
以上為個(gè)人經(jīng)驗(yàn),希望能給大家一個(gè)參考,也希望大家多多支持腳本之家。
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