Merge pull request #321 from Visual-Behavior/docker_torch1.13

Docker torch1.13 PL 1.9 - Transform p=1.0

Dockerfile

@@ -0,0 +1,37 @@
+# tagged aloception-oss:cuda-11.3.1-pytorch1.10.1-lightning1.4.1
+
+FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04
+#FROM nvidia/cuda:11.6.0-cudnn8-devel-ubuntu20.04
+
+ARG py=3.9
+ARG pytorch=1.13.1
+ARG torchvision=0.14.1
+ARG torchaudio=0.13.1
+ARG pytorch_lightning=1.9.0
+ARG pycyda=11.7
+
+ENV TZ=Europe/Paris
+ENV DEBIAN_FRONTEND=noninteractive
+
+RUN apt-get update
+RUN apt-get install -y build-essential nano git wget libgl1-mesa-glx
+
+# Usefull for scipy 
+RUN apt-get install -y gfortran 
+# required for aloscene
+RUN apt-get install -y libglib2.0-0
+
+
+RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+RUN bash Miniconda3-latest-Linux-x86_64.sh -b -p /miniconda
+ENV PATH=$PATH:/miniconda/condabin:/miniconda/bin
+RUN /bin/bash -c "source activate base"
+ENV HOME /workspace
+WORKDIR /workspace
+
+# Pytorch & pytorch litning
+RUN conda install pytorch==${pytorch} torchvision==${torchvision} torchaudio==${torchaudio} pytorch-cuda=${pycuda} -c pytorch -c nvidia
+RUN pip install pytorch_lightning==${pytorch_lightning}
+
+COPY requirements-torch1.13.1.txt /install/requirements-torch1.13.1.txt
+RUN pip install -r /install/requirements-torch1.13.1.txt

README.md

@@ -4,7 +4,7 @@
 
 <a href="https://visual-behavior.github.io/aloception-oss/">Documentation</a>
 
-[![Conventional Commits](https://img.shields.io/badge/Conventional%20Commits-0.3.0-green.svg)](https://conventionalcommits.org)
+[![Conventional Commits](https://img.shields.io/badge/Conventional%20Commits-0.5.0-green.svg)](https://conventionalcommits.org)
 
 # Aloception open source software
 
@@ -75,6 +75,26 @@ training pipelines with **augmented tensors**.
 
 ## Installation
 
+### Docker install
+
+```
+docker build -t aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0 .
+```
+
+```
+docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0
+```
+
+Or without building the image
+
+```
+docker run --gpus all -it -v /YOUR/WORKSPACE/:/workspace --privileged -e DISPLAY=$DISPLAY -v /tmp/.X11-unix:/tmp/.X11-unix visualbehaviorofficial/aloception-oss:cuda-11.3.1-pytorch1.13.1-lightning1.9.0
+```
+
+
+
+### Pip install
+
 You first need to install PyTorch 1.10.1 based on your hardware and environment
 configuration. Please refer to the [pytorch website](https://pytorch.org/get-started/locally/) for this installation.
 

alodataset/transforms.py

@@ -14,7 +14,7 @@
 
 
 class AloTransform(object):
-    def __init__(self, same_on_sequence: bool = True, same_on_frames: bool = False, p: float = 0.5):
+    def __init__(self, same_on_sequence: bool = True, same_on_frames: bool = False, p: float = 1.0):
         """Alo Transform. Each transform in the project should
         inhert from this class.
 
@@ -772,7 +772,6 @@ def apply(self, frame: Frame):
         -------
         n_frame: aloscene.Frame
         """
-
         n_frame = frame.norm01()
 
         frame_data = n_frame.data.as_tensor()

requirements-torch1.13.1.txt

@@ -0,0 +1,21 @@
+pycocotools==2.0.2
+PyYAML==5.4.1
+chardet==4.0.0
+idna==2.10
+
+scipy==1.10.0
+
+more_itertools==8.8.0
+requests==2.25.1
+opencv-python==4.7.0.68
+
+python-dateutil==2.8.2
+urllib3==1.26.6
+
+protobuf==4.21.12
+wandb==0.13.9
+
+tqdm==4.62.3
+captum==0.4.0
+
+setuptools==59.5.0

unittest/test_frame.py

@@ -30,7 +30,7 @@ def tensor_equal(frame1, frame2):
 
 def test_frame_from_dt():
     # Go through the loaded sequence
-    for data in waymo_dataset.stream_loader():
+    for data in waymo_dataset.stream_loader(num_workers=1):
         assert data["front"].shape[:2] == (2, 3)
         assert data["front"].names == ("T", "C", "H", "W")
         # It should be instance of list since the dataset return a sequence and the

unittest/test_transformation.py

@@ -2,6 +2,7 @@
 from alodataset import transforms as T
 import numpy as np
 import torch
+import random
 
 
 def test_color_jitter():
@@ -78,4 +79,10 @@ def test_color_jitter():
 
 
 if __name__ == "__main__":
+    # seed everything
+    seed = 42
+    random.seed(seed)
+    np.random.seed(seed)
+    torch.manual_seed(seed)
+    torch.cuda.manual_seed_all(seed)
     test_color_jitter()