Merge branch 'master' of triton.inf-cv.uni-jena.de:ComputerVisionJena/cvargparse

README.md

@@ -1,2 +1,58 @@
-# cvargparse
+# Wrapper for `argparse`
+
+Some sample code (with some pseudo DL framework): 
+
+```python
+from cvargparse import GPUParser, ArgFactory, Arg
+
+from dlframework import Model, LRSchedule, Updater, Iterator, to_gpu, load_data
+
+def main(args):
+    data = load_data(args.data, args.labels)
+    model = Model(args.model_weights)
+    # we can select multiple GPUs. use the first GPU for the initial model creation
+    
+    GPU = args.gpu[0]
+    if GPU >= 0:
+        to_gpu(model, GPU)
+    
+    lr_schedule = LRSchedule(args.lr, args.lr_shift, args.lr_decrease_rate, args.lr_target)
+    
+    updater = Updater(model, lr_schedule, decay=args.decay)
+    
+    it = Iterator(data, args.batch_size)
+    
+    for epoch in range(args.epochs):
+        for batch in it:
+            updater.train(model, batch)
+    
+    parser = GPUParser(ArgFactory([
+		Arg("data", type=str),
+		Arg("labels", type=str),
+		Arg("model_weights", type=str),
+	])\
+	.epochs()\
+	.batch_size()\
+	.learning_rate(lr=1e-3)\
+	.weight_decay(5e-3)\
+	.seed()\
+	.debug())
+
+parser.init_logger()
+main(parser.parse_args())
+
+```
+
+This script can be called as following:
+
+```bash
+python script.py path/to/data path/to/labels path/to/model \
+    --gpu 0 1 \
+    -lr 0.001 -lrs 30 -lrd 0.1 -lrt 1e-7 \
+    --batch_size 32 \
+    --epochs 90 \
+    --loglevel DEBUG \
+    --logfile path/to/logs
+    
+```