[GitHub] [incubator-mxnet] TaoLv commented on issue #9730: Check padding size for global pooling

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TaoLv commented on issue #9730: Check padding size for global pooling
URL: https://github.com/apache/incubator-mxnet/pull/9730#issuecomment-494251934
 
 
   I would say these layers finally get the correct input now. :)
   
   For your case, if you want to get the same results as before, please try 
below changes:
   ```python
   import mxnet as mx
   
   class Batch(object):
       def __init__(self, data):
           self.data = data
   
       def get_batch_shape(self):
           return tuple(self.data[0].shape)
   
   data = mx.sym.Variable('data')
   gpool = mx.sym.Pooling(data,
                          name='gpooling',
                          global_pool=False,    # <--- remove global pooling
                          pad=(1,1), pool_type='avg',
                          stride=(5,5),         # <--- add stride
                          kernel=(5,5),)        # <--- change kernel size to 
input size
   mod = mx.mod.Module(gpool, context=mx.cpu(0), label_names=[])
   data = Batch([mx.ndarray.ones((1, 3, 5, 5))])
   mod.bind(for_training=True, force_rebind=True, data_shapes=[('data', 
data.get_batch_shape())],)
   mod.init_params()
   mod.forward(data)
   print(mx.__version__)
   print(mod.get_outputs()[0].asnumpy())
   ```

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