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+# Installation guide
+To reproduce results, please install the 3DTrans repository as detailed in the README provided in that repo [here](https://github.com/PJLab-ADG/3DTrans/blob/master/docs/INSTALL.md) 
 
+## Configuration 
+We ran the repository and its model using the following configuration, we strongly advice using a python virtual environment, the 3Dtrans repo has some quirky dependency requirements, the following configuration was created based on numpy 1.19.4: 
+- GCC 10.2.0
+- Python 3.8.6
+- CUDA 11.1 
+- cuDNN 8.0.4.30
+- torch 1.8.1+cu111
+- torchaudio 0.8.1
+- torchvision 0.9.1+cu111
+- waymo-open-dataset-tf-2-4-0 (Needed for dataset evaluation and automatically installs tensorflow)
+- tensorflow 2.4.0
+- tensorboardX 2.6
+- spconv-cu111
+- SharedArray 3.1.0
+- scikit-image 0.19.3
+- PyYAML 6.0.1 (yaml.load needs to be swapped to yaml.full.load or yaml.safe.load see documentation on PyYAML)
+- protobuf 3.19.6
+- Pillow 9.2.0
+- opencv-python 4.8.1.78
+- h5py 2.10.0
+- numba 0.56.4
+- numpy 1.19.4
+
+To train the models we used 2 [NvidiaA100GPUS ](https://www.nvidia.com/en-us/data-center/a100/) with 160 gb of video ram,
+4 cpu cores per GPU and 60gb of memory.
+
+After installation please configure the ONCE and Waymo dataset as detailed in the repository's dedicated dataset [README](https://github.com/PJLab-ADG/3DTrans/blob/master/docs/GETTING_STARTED_DB.md) we used a small subset of the data and split the data using the txt files in the ImageSets folder located in the dedicated dataset folders.  
+
+In order to run the pointContrast pre-training model you need to merge labels, we have provided a script for this called mergeClasses.py in the preProcessScripts folder. 
+Please see the files comments for usage, this file needs to be used to merge the files: once_infos_train.pkl, once_dbinfos_train.pkl and once_infos_val.pkl which are generated from the generate_infos function command in the  [README](https://github.com/PJLab-ADG/3DTrans/blob/master/docs/GETTING_STARTED_DB.md). 
+Additionally the once_dataset.py file in the follwoing located [here](https://github.com/PJLab-ADG/3DTrans/blob/master/pcdet/datasets/once/once_dataset.py)
+on line 416 the list of ignored sets needs to be changed so that the raw_small section is not ignored. 
+
+# Debugging and troubleshooting
+If errors are encountered when running the paradigm we would advice either posting an issue in the 3Dtrans repo or by looking for/posting an error on the opendPCdet repository located [here](https://github.com/open-mmlab/OpenPCDet) as 3Dtrans uses this repository. 
+Moreover debugging code by starting from source and properly configuring CUDA and tensorflow before starting the testing is crucial, make use of the tensorflow installation guide located [here](https://www.tensorflow.org/install/pip) and ensuring that the following command detects both GPUS:
+`python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"`