The requirements.txt has been changed and no longer has torchvision and scikit-learn as one of the requirements. However, it seems to seek a torch version>=1.4 as a result of torchmetrics>=0.2.0 (within requirements.txt). My Jetson even has torch 1.8.0 and torchvision in its pip3 package manager. I was wondering if anyone has successfully set Pytorch Lightning up on ARM64’s new requirement layout. Thanks!
Is there something I’m missing? I have also tried running setup.py to no avail. Thanks!
This is not a script bug as I’m only having trouble with setup using the pip package manager on Jetson/ARM64. The original post of mine is here: https://github.com/PyTorchLightning/pytorch-lightning/issues/7408
When I find a solution, I will likely update every one of my posts with an extensive solution to the issue. Thanks!
Additional context
PyTorch Version (e.g., 1.0): 1.8.0
OS (e.g., Linux): Linux
How you installed PyTorch ( conda , pip , source): pip
Build command you used (if compiling from source): pip3 install pytorch-lighting/pip3 install -r requirements.txt
I ended up fixing the problem. In short, the problem seemed to be that either the torch version that I possessed was not 1.4.0, or that I needed to use pip instead of pip3. For some reason, pip installed for both pip python 2 and pip3. I would invite other people to evaluate this further. This is a rundown of my documentation on the process:
Pytorch Lightning Setup on Jetson Xavier NX
The general theme seems that we need to install pytorch lightning with the Pip package manager instead of pip3
and/or that we need to have torch 1.4.0 with its corresponding torchvision in order to pass the torch>=1.4 requirement
Not sure which, but it seemsl ike having both also works
1. We need to retrieve the Pytorch Variant 1.4.0 and torchvision 0.5.0 (Torch needs to bne >=1.4 but it seems 1.4.0 may be necessary). Prior to this, we already possessed pip3 and a torch and torchvision installation corresponding to that.
$ wget https://nvidia.box.com/shared/static/1v2cc4ro6zvsbu0p8h6qcuaqco1qcsif.whl -O torch-1.4.0-cp27-cp27mu-linux_aarch64.whl
$ git clone --branch v0.5.0 https://github.com/pytorch/vision torchvision # see below for version of torchvision to download
2. We will need both pip and pip3 to install pytorch lightning
$ sudo apt-get update
$ sudo apt-get install libhdf5-serial-dev hdf5-tools libhdf5-dev zlib1g-dev zip libjpeg8-dev liblapack-dev libblas-dev gfortran
$ sudo apt-get install python-pip
$ sudo pip3 install -U pip testresources setuptools==49.6.0 # This step wasn't necessary but was done during the installation process for python 2 pip
3. Once we have the pip package manager, we need to install torch 1.4.0 on out python 2 environment. We also need to edit the Requirements.txt within pytorch-lightning environment
$ cd torchvision
$ export BUILD_VERSION=0.5.0
$ python3 setup.py install --user
$ cd path/to/pytorch-lightning
open requirements.txt..
Comment out the torch>=1.4 constraint as follows:
numpy>=1.17.2
#torch>=1.4 <---------------------------------------------------------------
future>=0.17.1 # required for builtins in setup.py
tqdm>=4.41.0
PyYAML>=5.1,<=5.4.1
fsspec[http]>=2021.4.0
tensorboard>=2.2.0, !=2.5.0 # 2.5.0 GPU CI error: 'Couldn't build proto file into descriptor pool!'
torchmetrics>=0.2.0
pyDeprecate==0.3.0
packaging
4. Install (The pip install seems to also install for pip3 manager)
$ pip install pytorch-lightning # Valid for both pip and pip3
5. We can continue to verify with pip list
$ pip3 list
$ pip list
It’s difficult to screencap these results using shutter with highlighted similarities, but your pip and pip3 list should look the same with the following and the same versions:
Sources
Pytorch and Torchvision installation for Python 2 and 3:
Python 2 pip installation:
Pytorch Lightning forum post (seems correct to a degree but non-working for us):
Pytorch Lightning installation (A note article by USAEng on ptl installation):
