UPDATE:
after being happy with the platform, and annoyed with the switching notebooks, I decided to purchase a subscription.
Since then I have some problems.
I guess I don’t get the idea of the storage and notebooks. I started a notebook with a cheap CPU computer. I saved the notebook file in the storage folder and later tried to access it from a GPU instance - nothing… the file is not there. Is the storage shared between instances, or is it specific to a “notebook” (which might be a misleading name as its actually a Jupiter server, isn’t it? so I’ll call the paper space notebook NOTEBOOK from now on).
UPDATE: I discovered that some instances are in a different location than others, so they don’t share the storage. Storage sharing is crucial for work continuity so I think this should be more clear to the user when he chooses instance types, which share the storage.
I reproduced my whole work on a GPU notebook instance (the cheap version of K80). When running, the kernel crashed. After it had crashed I could do nothing. I couldn’t restart it, I couldn’t reload or save the notebook. Every time I got back to the console and pressed “open” it showed the top bar but never loaded the notebook. I had to stop the NOTEBOOK and restart it again, which takes around 10 minutes.
During work some functionality suddenly disappears, such as using shift+tab to explore functions. This is one of the most useful features of Jupiter and I can’t see myself working without it.
@Jess Gradient includes a few different free GPU instances. There are other more powerful instances that are not free but we are offering a promo code to the Fast.ai community: FASTAI2020
@Jess@miwojc We still offer referral credit where you can send credit and earn $15 per account You can find your referral code in the console on the settings page:
Here are some hints for Paperspace total beginners. As one, it took me a while to figure out this basic orientation.
Paperspace Notebooks are not the same as Jupyter Notebooks. A Paperspace notebook is a virtual environment. With a free account you can create only one. However, you can create and use multiple Jupyter notebooks within one Paperspace Notebook.
To work with several Jupyter notebooks at once, Ctrl-click the notebook name in the Jupyter file browser. It will open in a new tab.
To use the fastai book…
Open a new Terminal from the Jupyter file browser.
Navigate to the desired location for fastbook. Next…
git clone https://github.com/fastai/fastbook.git
Now you can open the fastbook chapters using the Jupyter notebook browser.
To keep the book up-to-date,
cd fastbook (wherever you placed it)
git pull
You will need to regularly update fastai2 and the course as described in the top post FAQ.
When you get lost, a click in the upper left box that says “Gradient” will go back to the Gradient Notebook console.
Click on “Jupyter” at top to get back to the Jupyter notebook browser.
Hi, yes, I was able to select the GPU and paperspace notebook. I noticed that my GPU wasn’t the P5000 which was recommended, so I just ended up creating a new paperspace notebook using the P5000 GPU and now the jupyter notebook is working and there are no memory errors. thanks for your help
@dkobran hey Daniel I am trying to run line 15 from the 01__intro notebook.
dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test')
learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)
learn.fine_tune(4, 1e-2)```
I have not encountered an error yet (meaning any CUDA out of memory message). However, the cell has been running for almost 10 min is this behavior expected? I am using the free instances and the P5000
@mario_carrillo text learners take a very long time to train. Each epoch is usually around 7-10 minutes + depending on the GPU. So that bit of code right there would take 30+ minutes to run
It works for me to. however when i want to install more packages with pip or conda. do i need to activate fastai enviroent? i noticed there is conda environment called fastai. to access it. first type bash in terminal, and then conda activate fastai. and if you are running it for the first time i don’t remember now but i think conda init
The container by default starts into the fastai virtual env (/opt/conda/envs/fastai) so no need to activate – even though your terminal’s shell won’t be prepended with (fastai) it is already using it. You can verify this by running
conda env list
or by the fact that all required fastai modules are usable since well, they don’t exist outside of this env ;] HTH
P.S. As an aside and I believe Dan already mentioned this, I prefer to use bash when jumping to the terminal since you get fancier shell things like name completion etc but of course shell choice is yours.
hey!
i have a question, How should we use voila on paperspace hosted jupyter notebooks, because when i change the URL(notebooks to voila/render) it gives me an error
Is there a possibility to run JupyterLab on paperspace gradient? JupyterLab released new visual debugger which is very cool. Would be great to have that option on paperspace platform! thanks!
@miwojc Absolutely! Many of our pre-configured templates run Jupyter Lab eg the PyTorch and TensorFlow 2.0 templates. If you’d like to start with your own, just head to the custom container tab and run jupyter lab --allow-root --ip=0.0.0.0 as the command (make sure Jupyter Lab is installed of course ). Here’s an example:
You can find your referral code in the console on the settings page:
