![]() ![]() The deleted /data/one file is still in the previous layers, 3 times in fact, and will be copied over the network and stored on disk when you pull the image. The entire file is in each layer when there's an add or change, so each of those chmod commands, despite just changing a permission bit, results in the entire file being copied into the next layer. ![]() Here's the TL DR partĮach of these container filesystem diffs above goes into one "layer" that gets assembled when you run the image as a container. $ docker diff 504c6e9b6637 # rm /data/oneĮach line prefixed with an A is adding the file, the C indicates a change to an existing file, and the D indicates a delete. $ docker diff 038bd2bc5aea # chmod -R 0777 /data $ docker diff f1b72db3bfaa # dd if=/dev/zero bs=1024 count=1024 of=/data/one If you run a docker diff on each of those container id's, you'll see what files were created in those containers: $ docker diff 04c5fa1360b0 # mkdir /data In the output, you'll see each of the running commands happen in a temporary container that we now keep instead of automatically deleting. Lets build the image with an extra flag to save the temporary containers: docker image build -rm=false. # and now this cleans up that downloaded source codeĮach of those dd commands outputs a 1M file to the disk. RUN dd if=/dev/zero bs=1024 count=1024 of=/data/two RUN dd if=/dev/zero bs=1024 count=1024 of=/data/one # imagine this is downloading source code Lets take a contrived example Dockerfile: FROM busybox Examining layers of your own build with docker diff They make the most sense to me with an example. Because layers are intermediate images, if you make a change to your Dockerfile, docker will rebuild only the layer that was changed and the ones after that. The concept of layers comes in handy at the time of building images. Then, we tell docker to run bundle exec puma (which boots up the rails server). We add another layer on top of our starting image, setting the environment variable RAILS_ENV with the ENV command. You can think of it as staging changes when you're using git: You add a file's change, then another one, then another one.Ĭonsider the following Dockerfile: FROM rails:onbuildįirst, we choose a starting image: rails:onbuild, which in turn has many layers. Every command you specify ( FROM, RUN, COPY, etc.) in your Dockerfile causes the previous image to change, thus creating a new layer. ![]() model.get_submodule('.'.join(parent)) = nn.I might be late, but here's my 10 cents (complementing ashishjain's answer):īasically, a layer, or image layer is a change on an image, or an intermediate image. Finally, we can fetch the layer reference in order to overwrite their value: > for *parent, k in maxpools: Here they all come from the same parent module model.features. We can extract the parent module name for each of those layers: > maxpools = [k.split('.') for k, m in model.named_modules() A canonical approach is to filter the layers of model.modules and only keep the max pool layers, then replace those with average pool layers: > maxpools = [k for k, m in model.named_modules() Also do note: not all layers are registered inside the nn.Module, non-parametric functions such as most activation functions can be applied via the functional approach directly in the forward of the module.įor a given nn.Module m you can extract its layer name by using type(m)._name_. model.features), however this is not always the case, for instance nn.Sequential use indices: model.features to select one of the relu activations. For example, submodule are often accessible via attributes ( e.g. This will depend on your model's implementation. Select a submodule and interact with it as you would with any other nn.Module. Assuming you know the structure of your model, you can: > model = torchvision.models(pretrained=True) ![]()
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