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Tag: google-colaboratory

Save failed in Google Colab

I opened a number of tabs at the same time. I think that’s why Google Colab was not able to support the heavy load. The message stated: Save failed This file could not be saved. Please use the File menu to download the .ipynb and upload the notebook to make a copy that includes your recent changes. Is downloading the

How to see complete rows in Google Colab

I am using Google Colab python 3.x and I have a Dataframe as below. I would like to see all cells on each row and column. How can I do this? I tried pd.set_option(‘display.max_columns’, 3000) but it didn’t work. Answer use pd.set_option(‘max_colwidth’, <width>) for column width & pd.set_option(‘max_rows’, <rows>) for number of rows. see https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html

Get LightGBM/ LGBM run with GPU on Google Colabratory

I often run LGBM on Google Colabratory and I just found out this page saying that LGBM it set to CPU by default so you need to set up first. https://medium.com/@am.sharma/lgbm-on-colab-with-gpu-c1c09e83f2af So I executed the code recommended on the page or some other codes recommended on stackoverflow as follows, !git clone –recursive https://github.com/Microsoft/LightGBM %cd LightGBM !mkdir build %cd build !cmake

Get total amount of free GPU memory and available using pytorch

I’m using google colab free Gpu’s for experimentation and wanted to know how much GPU Memory available to play around, torch.cuda.memory_allocated() returns the current GPU memory occupied, but how do we determine total available memory using PyTorch. Answer In the recent version of PyTorch you can also use torch.cuda.mem_get_info: https://pytorch.org/docs/stable/generated/torch.cuda.mem_get_info.html#torch.cuda.mem_get_info

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