fixed argparse descriptions

Author: toenshoff

Benchmarks/test_cifar.py

@@ -4,18 +4,18 @@
 from data_utils import CRaWlLoader
 from Benchmarks.test import test
 import argparse
+from glob import glob
 import torch
 import numpy as np
-from glob import glob
 
 from Benchmarks.train_cifar import load_split_data
 
 
 def main():
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_dir", type=str, help="path to config file")
+    parser.add_argument("--model_dir", type=str, help="path to the model directories")
     parser.add_argument("--reps", type=int, default=10, help="Number of eval repetitions")
-    parser.add_argument("--steps", type=int, default=50, help="Number of steps in each walk")
+    parser.add_argument("--steps", type=int, default=150, help="Number of steps in each walk")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     parser.add_argument("--split", type=str, default='test', choices={'test', 'val'}, help="split to evaluate on")
     parser.add_argument("--batch_size", type=int, default=50, help="Batch size used for testing")

Benchmarks/test_mnist.py

@@ -13,8 +13,8 @@
 
 def main():
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_dir", type=str, help="path to config file")
-    parser.add_argument("--steps", type=int, default=50, help="Number of steps in each walk")
+    parser.add_argument("--model_dir", type=str, help="path to the model directories")
+    parser.add_argument("--steps", type=int, default=150, help="Number of steps in each walk")
     parser.add_argument("--reps", type=int, default=10, help="Number of eval repetitions")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     parser.add_argument("--split", type=str, default='test', choices={'test', 'val'}, help="split to evaluate on")

Benchmarks/test_zinc.py

@@ -49,9 +49,9 @@ def test(model, iter, repeats, steps):
 if __name__ == '__main__':
 
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_dir", type=str, default=None, help="path to config file")
+    parser.add_argument("--model_dir", type=str, default=None, help="path to the model directories")
     parser.add_argument("--reps", type=int, default=10, help="Number of eval repetitions")
-    parser.add_argument("--steps", type=int, default=50, help="Number of steps in each walk")
+    parser.add_argument("--steps", type=int, default=150, help="Number of steps in each walk")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     parser.add_argument("--split", type=str, default='test', choices={'test', 'val'}, help="split to evaluate on")
     args = parser.parse_args()

Benchmarks/train_cifar.py

@@ -33,8 +33,8 @@ def load_split_data():
 
 def main():
     parser = argparse.ArgumentParser()
-    parser.add_argument("--config", type=str, default='configs/CIFAR10/default_old.json', help="path to config file")
-    parser.add_argument("--name", type=str, default='CRaWl', help="path to config file")
+    parser.add_argument("--config", type=str, default='configs/CIFAR10/default.json', help="path to config file")
+    parser.add_argument("--name", type=str, default='0', help="path to config file")
     parser.add_argument("--gpu", type=int, default=0, help="id of gpu to be used for training")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     args = parser.parse_args()

Benchmarks/train_csl.py

@@ -70,7 +70,7 @@ def load_split_data(config, fold, use_lap_feat=False):
 
 def main():
     parser = argparse.ArgumentParser()
-    parser.add_argument("--config", type=str, default='configs/CSL/default_old.json', help="path to config file")
+    parser.add_argument("--config", type=str, default='configs/CSL/default.json', help="path to config file")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     parser.add_argument("--steps", type=int, default=150, help="Number of steps in each walk")
     parser.add_argument("--reps", type=int, default=10, help="Number of eval repetitions")

Benchmarks/train_mnist.py

@@ -33,8 +33,8 @@ def load_split_data():
 
 def main():
     parser = argparse.ArgumentParser()
-    parser.add_argument("--config", type=str, default='configs/MNIST/default_old.json', help="path to config file")
-    parser.add_argument("--name", type=str, default='CRaWl', help="path to config file")
+    parser.add_argument("--config", type=str, default='configs/MNIST/default.json', help="path to config file")
+    parser.add_argument("--name", type=str, default='0', help="path to config file")
     parser.add_argument("--gpu", type=int, default=0, help="id of gpu to be used for training")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     args = parser.parse_args()

Benchmarks/train_zinc.py

@@ -111,8 +111,8 @@ def load_split_data(config):
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument("--config", type=str, default='configs/ZINC/default_old.json', help="path to config file")
-    parser.add_argument("--name", type=str, default='CRaWl', help="name of the model")
+    parser.add_argument("--config", type=str, default='configs/ZINC/default.json', help="path to config file")
+    parser.add_argument("--name", type=str, default='0', help="name of the model")
     parser.add_argument("--gpu", type=int, default=0, help="id of gpu to be used for training")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     args = parser.parse_args()

OGB/ogb_utils.py

@@ -27,16 +27,6 @@
                    [0,1],
                    [0,1]]
 
-lsc_atom_labels = [[0,1,3,4,5,6,7,8,10,11,13,14,15,16,17,19,21,29,30,31,32,33,34,52],
-                   [0,1,2],
-                   [0,1,2,3,4,5,6],
-                   [4,5,6,7,8,9],
-                   [0,1,2,3,4],
-                   [0,1,2,3,4],
-                   [0,1,2,3,4,5],
-                   [0,1],
-                   [0,1]]
-
 hiv_bond_labels = [[0,1,2,3],
                    [0],
                    [0,1]]
@@ -45,11 +35,6 @@
                    [0,1,2],
                    [0,1]]
 
-lsc_bond_labels = [[0,1,2,3],
-                   [0,1,2],
-                   [0,1]]
-
-
 class OneHotEncoder(torch.nn.Module):
 
     def __init__(self, train_labels, num_poss_labels, device):
@@ -76,10 +61,6 @@ def get_pcba_encoders(device):
     return OneHotEncoder(pcba_atom_labels, full_atom_feature_dims, device), OneHotEncoder(pcba_bond_labels, full_bond_feature_dims, device)
 
 
-def get_lsc_encoders(device):
-    return OneHotEncoder(lsc_atom_labels, full_atom_feature_dims, device), OneHotEncoder(lsc_bond_labels, full_bond_feature_dims, device)
-
-
 def load_graphs(ogb_name):
 
     dataset = PygGraphPropPredDataset(ogb_name, root='data', transform=preproc)
@@ -96,7 +77,3 @@ def load_graphs(ogb_name):
 
     return out_dim, train_graphs, valid_graphs, test_graphs
 
-
-if __name__ == '__main__':
-    dataset = PygPCQM4MDataset(root='/media/jan/06eeae08-1b88-4399-b775-aaba8efa917f/home/jan/OGB/datasets')
-    print(dataset)

OGB/test_ogb.py

@@ -52,11 +52,11 @@ def test(model, iter, repeats, steps=50):
 if __name__ == '__main__':
 
     parser = argparse.ArgumentParser()
-    parser.add_argument("--model_dir", type=str, default=None, help="path to config file")
-    parser.add_argument("--data", type=str, default='ogbg-molhiv', help="path to config file")
-    parser.add_argument("--reps", type=int, default=2, help="Number of eval repetitions")
-    parser.add_argument("--steps", type=int, default=50, help="Number of steps in each walk")
-    parser.add_argument("--batch_size", type=int, default=50, help="Batch size used for testing")
+    parser.add_argument("--model_dir", type=str, default=None, help="path to the model directories")
+    parser.add_argument("--data", type=str, default='MOLPCBA', choices={'MOLHIV', 'MOLPCBA'}, help="OGB Dataset to use")
+    parser.add_argument("--reps", type=int, default=10, help="Number of eval repetitions")
+    parser.add_argument("--steps", type=int, default=150, help="Number of steps in each walk")
+    parser.add_argument("--batch_size", type=int, default=60, help="Batch size used for testing")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     parser.add_argument("--split", type=str, default='test', choices={'test', 'val'}, help="split to evaluate on")
     args = parser.parse_args()

OGB/train_ogb.py

@@ -107,9 +107,9 @@ def train(model, train_iter, val_iter):
 if __name__ == '__main__':
 
     parser = argparse.ArgumentParser()
-    parser.add_argument("--config", type=str, default='configs/MOLPCBA/default_old.json', help="path to config file")
-    parser.add_argument("--data", type=str, default='MOLHIV', choices={'MOLHIV', 'MOLPCBA'}, help="path to config file")
-    parser.add_argument("--name", type=str, default='OGB', help="path to config file")
+    parser.add_argument("--config", type=str, default='configs/MOLPCBA/default.json', help="path to config file")
+    parser.add_argument("--data", type=str, default='MOLPCBA', choices={'MOLHIV', 'MOLPCBA'}, help="OGB Dataset to use")
+    parser.add_argument("--name", type=str, default='0', help="path to config file")
     parser.add_argument("--gpu", type=int, default=0, help="id of gpu to be used for training")
     parser.add_argument("--seed", type=int, default=0, help="the random seed for torch and numpy")
     args = parser.parse_args()