fix example config list (#5554)

examples/compression/fusion/pd_fuse.py

@@ -72,7 +72,6 @@ if __name__ == '__main__':
 
     config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'lambda': 0.1,
         'apply_method': 'mse',
     }]

examples/compression/fusion/pqd_fuse.py

@@ -94,7 +94,6 @@ if __name__ == '__main__':
 
     d_config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'lambda': 0.1,
         'apply_method': 'mse',
     }]

examples/compression/pruning/norm_pruning.py

@@ -35,7 +35,6 @@ if __name__ == '__main__':
 
     config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'sparse_ratio': 0.5
     }]
     dummy_input = torch.rand(8, 3, 224, 224).to(device)

examples/compression/pruning/scheduled_pruning.py

@@ -32,7 +32,6 @@ if __name__ == '__main__':
 
     config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'sparse_ratio': 0.5
     }]
     dummy_input = torch.rand(8, 3, 224, 224).to(device)

examples/compression/pruning/slim_pruning.py

@@ -30,7 +30,6 @@ if __name__ == '__main__':
 
     config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'sparse_ratio': 0.5
     }]
     dummy_input = torch.rand(8, 3, 224, 224).to(device)

examples/compression/pruning/taylor_pruning.py

@@ -30,7 +30,6 @@ if __name__ == '__main__':
 
     config_list = [{
         'op_types': ['Conv2d'],
-        'op_names_re': ['features.*'],
         'sparse_ratio': 0.5
     }]
     dummy_input = torch.rand(8, 3, 224, 224).to(device)