问题
I am referring to the models that can be found here: https://pytorch.org/docs/stable/torchvision/models.html#torchvision-models
回答1:
As, @dennlinger mentioned in his answer : torch.utils.model_zoo, is being internally called when you load a pre-trained model.
More specifically, the method: torch.utils.model_zoo.load_url()
is being called every time a pre-trained model is loaded. The documentation for the same, mentions:
The default value of
model_dir
is$TORCH_HOME/models
where$TORCH_HOME
defaults to~/.torch
.The default directory can be overridden with the
$TORCH_HOME
environment variable.
This can be done as follows:
import torch
import torchvision
import os
# Suppose you are trying to load pre-trained resnet model in directory- models\resnet
os.environ['TORCH_HOME'] = 'models\\resnet' #setting the environment variable
resnet = torchvision.models.resnet18(pretrained=True)
I came across the above solution by raising an issue in the PyTorch's GitHub repository: https://github.com/pytorch/vision/issues/616
This led to an improvement in the documentation i.e. the solution mentioned above.
回答2:
Yes, you can simply copy the urls and use wget
to download it to the desired path. Here's an illustration:
For AlexNet:
$ wget -c https://download.pytorch.org/models/alexnet-owt-4df8aa71.pth
For Google Inception (v3):
$ wget -c https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth
For SqueezeNet:
$ wget -c https://download.pytorch.org/models/squeezenet1_1-f364aa15.pth
For MobileNetV2:
$ wget -c https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
For DenseNet201:
$ wget -c https://download.pytorch.org/models/densenet201-c1103571.pth
For MNASNet1_0:
$ wget -c https://download.pytorch.org/models/mnasnet1.0_top1_73.512-f206786ef8.pth
For ShuffleNetv2_x1.0:
$ wget -c https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth
If you want to do it in Python, then use something like:
In [11]: from six.moves import urllib
# resnet 101 host url
In [12]: url = "https://download.pytorch.org/models/resnet101-5d3b4d8f.pth"
# download and rename the file to `resnet_101.pth`
In [13]: urllib.request.urlretrieve(url, "resnet_101.pth")
Out[13]: ('resnet_101.pth', <http.client.HTTPMessage at 0x7f7fd7f53438>)
P.S: You can find all the download URLs in the individual python files in torchvision.models
回答3:
TL;DR: No, it is not possible directly, but you can easily adapt it.
I think what you want to do is to look at torch.utils.model_zoo, which is internally called when you load a pre-trained model:
If we look at the code for the pre-trained models, for example AlexNet here, we can see that it simply calls the previously mentioned model_zoo
function, but without the saved location. You can either modify the PyTorch source to specify this (that would actually be a great addition IMO, so maybe open a pull request for that), or else simply adopt the code in the second link to your own liking (and save it to a custom location under a different name), and then manually insert the relevant location there.
If you want to regularly update PyTorch, I would heavily recommend the second method, since it doesn't involve directly altering PyTorch's code base, and potentially throw errors during updates.
来源:https://stackoverflow.com/questions/52628270/is-there-any-way-i-can-download-the-pre-trained-models-available-in-pytorch-to-a