update examples

Author: reiase

examples/mnist/main_with_hp.py

@@ -96,7 +96,7 @@ def main():
                         help='how many batches to wait before logging training status')
     parser.add_argument('--save-model', action='store_true', default=False,
                         help='For Saving the current Model')
-    parser.add_argument('-D', '--define', nargs='*', default=[])
+    parser.add_argument('-D', '--define', nargs='*', default=[], action="extend")
     args = parser.parse_args()
     use_cuda = not args.no_cuda and torch.cuda.is_available()
 

examples/sparse_lr/example_2.py

@@ -23,14 +23,9 @@ def run(args):
     # create cmd line arguments parser
     import argparse
     parser = argparse.ArgumentParser('example')
-    parser.add_argument(
-        '-D',
-        '--define',
-        nargs='*',
-        default=[],
-        help=
-        'define a parameter `param_name=param_value`, supported parameter list: \n\n  {}'
-        .format('\n  '.join(Tracker.all())))
+    parser.add_argument('-D', '--define', nargs='*', default=[], action="extend",
+        help='define a parameter `param_name=param_value`, supported parameter list: \n\n  {}'
+            .format('\n  '.join(Tracker.all())))
     args = parser.parse_args()
     run(args)
 

examples/sparse_lr/model.py

@@ -5,9 +5,11 @@
 from hyperparameter import auto_param, param_scope
 
 
+MyLogisticRegression = auto_param(LogisticRegression)
+
 @auto_param
 def sparse_lr_plot(X, y, learning_rate=0.01, penalty='l1', C=0.01, tol=0.01):
-    LR = LogisticRegression(C=C, penalty=penalty, tol=tol, solver='saga')
+    LR = MyLogisticRegression(C=C, penalty=penalty, tol=tol, solver='saga')
 
     LR.fit(X, y)
     coef = LR.coef_.ravel()