trackml training

pointcnn_seg/trackml_dev_x8_fps.py

@@ -0,0 +1,69 @@
+#!/usr/bin/python3
+
+num_class = 50
+
+sample_num = 3242
+
+batch_size = 2
+
+num_epochs = 1024
+
+label_weights = []
+
+label_weights = [1.0] * num_class
+
+learning_rate_base = 0.005
+decay_steps = 20000
+decay_rate = 0.9
+learning_rate_min = 0.00001
+step_val = 500
+
+weight_decay = 0.0
+
+jitter = 0.001
+jitter_val = 0.0
+
+rotation_range = [0, 0, 0, 'u']
+rotation_range_val = [0, 0, 0, 'u']
+rotation_order = 'rxyz'
+
+scaling_range = [0.0, 0.0, 0.0, 'g']
+scaling_range_val = [0, 0, 0, 'u']
+
+sample_num_variance = 1 // 8
+sample_num_clip = 1 // 4
+
+x = 8
+
+xconv_param_name = ('K', 'D', 'P', 'C', 'links')
+xconv_params = [dict(zip(xconv_param_name, xconv_param)) for xconv_param in
+                [(8, 1, -1, 32 * x, []),
+                 (12, 2, 768, 32 * x, []),
+                 (16, 2, 384, 64 * x, []),
+                 (16, 6, 128, 128 * x, [])]]
+
+with_global = True
+
+xdconv_param_name = ('K', 'D', 'pts_layer_idx', 'qrs_layer_idx')
+xdconv_params = [dict(zip(xdconv_param_name, xdconv_param)) for xdconv_param in
+                 [(16, 6, 3, 3),
+                  (16, 6, 3, 2),
+                  (12, 6, 2, 1),
+                  (8, 6, 1, 0),
+                  (8, 4, 0, 0)]]
+
+fc_param_name = ('C', 'dropout_rate')
+fc_params = [dict(zip(fc_param_name, fc_param)) for fc_param in
+             [(32 * x, 0.0),
+              (32 * x, 0.5)]]
+
+sampling = 'fps'
+
+optimizer = 'adam'
+epsilon = 1e-3
+
+data_dim = 3
+with_X_transformation = True
+sorting_method = None
+
+keep_remainder = True

pointcnn_seg/train_val_shapenet.sh

@@ -2,7 +2,7 @@
 
 gpu=
 setting=
-models_folder="../../models/seg/"
+models_folder="../../models/trackml/"
 train_files="../../data/shapenet_partseg/train_files.txt"
 val_files="../../data/shapenet_partseg/val_files.txt"
 
@@ -46,4 +46,4 @@ fi
 
 
 echo "Train/Val with setting $setting on GPU $gpu!"
-CUDA_VISIBLE_DEVICES=$gpu python3 ../train_val_seg.py -t $train_files -v $val_files -s $models_folder -m pointcnn_seg -x $setting > $models_folder/pointcnn_seg_$setting.txt 2>&1 &
+CUDA_VISIBLE_DEVICES=$gpu python3 ../train_val_seg.py -t $train_files -v $val_files -s $models_folder -m pointcnn_seg -x $setting > $models_folder/trackml_seg_$setting.txt 2>&1 &

pointcnn_seg/train_val_trackml_dev.sh

@@ -0,0 +1,50 @@
+#!/usr/bin/env bash
+
+gpu=
+setting=
+models_folder="../../models/seg/"
+train_files="/home/tch/roaming/project/trackml/repo/kaggle_trackml/data/train_files.txt"
+val_files="/home/tch/roaming/project/trackml/repo/kaggle_trackml/data/val_files.txt"
+
+
+usage() { echo "train/val pointcnn_seg with -g gpu_id -x setting options"; }
+
+gpu_flag=0
+setting_flag=0
+while getopts g:x:h opt; do
+  case $opt in
+  g)
+    gpu_flag=1;
+    gpu=$(($OPTARG))
+    ;;
+  x)
+    setting_flag=1;
+    setting=${OPTARG}
+    ;;
+  h)
+    usage; exit;;
+  esac
+done
+
+shift $((OPTIND-1))
+
+if [ $gpu_flag -eq 0 ]
+then
+  echo "-g option is not presented!"
+  usage; exit;
+fi
+
+if [ $setting_flag -eq 0 ]
+then
+  echo "-x option is not presented!"
+  usage; exit;
+fi
+
+if [ ! -d "$models_folder" ]
+then
+  mkdir -p "$models_folder"
+fi
+
+
+echo "Train/Val with setting $setting on GPU $gpu!"
+CUDA_VISIBLE_DEVICES=$gpu python3 ../train_val_seg.py -t $train_files -v $val_files -s $models_folder -m pointcnn_seg -x $setting > $models_folder/pointcnn_seg_$setting.txt 2>&1 &

sampling/tf_sampling_compile_tch.sh

@@ -1,5 +1,10 @@
 #/bin/bash
-PYTHON=python
+PYTHON=python3
+
+#patch cuda
+#https://ask.fedoraproject.org/en/question/114489/cuda-9-nvcc-issue/
+#or glibc
+#https://devtalk.nvidia.com/default/topic/1023776/-request-add-nvcc-compatibility-with-glibc-2-26/
 
 CUDA_PATH=/usr/local/cuda
 TF_LIB=$($PYTHON -c 'import tensorflow as tf; print(tf.sysconfig.get_lib())')

train_val_seg.py

@@ -81,7 +81,7 @@ def main():
     batch_num = (num_train * num_epochs + batch_size - 1) // batch_size
     print('{}-{:d} training batches.'.format(datetime.now(), batch_num))
     batch_num_val = math.ceil(num_val / batch_size)
-    print('{}-{:d} testing batches per test.'.format(datetime.now(), batch_num_val))
+    print('{}-{:d} validation batches per test.'.format(datetime.now(), batch_num_val))
 
     ######################################################################
     # Placeholders