acphile commented on issue #18412:
URL:
https://github.com/apache/incubator-mxnet/issues/18412#issuecomment-639213050
## A example
```
from mxnet import np, npx
from mxnet.gluon import nn, parameter
npx.set_np()
class Net(nn.HybridBlock):
def __init__(self, **kwargs):
super(Net, self).__init__(**kwargs)
self.hidden1 = nn.Dense(3)
def hybrid_forward(self, F, x):
x = self.hidden1(x)
return x
class Net2(nn.HybridBlock):
def __init__(self, **kwargs):
super(Net2, self).__init__(**kwargs)
self.hidden2 = nn.Dense(3, activation='relu')
def hybrid_forward(self, F, x):
x = self.hidden2(x)
return x
>>> x = np.random.normal(size=(5, 10))
>>> net = Net()
>>> net.initialize()
>>> print(net.collect_params())
{'hidden1_weight': Parameter hidden1_weight (shape=(3, -1), dtype=float32),
'hidden1_bias': Parameter hidden1_bias (shape=(3,), dtype=float32)}
>>> print(net(x))
[[ 0.09921001 0.04954842 0.12571132]
[-0.06151271 -0.17121975 -0.18948194]
[ 0.0051947 -0.08211827 0.02048509]
[ 0.10466634 -0.08711289 -0.18864125]
[ 0.26467288 -0.08746998 0.16121587]]
>>> net2=Net2()
>>> net2.initialize()
>>> print(net2.collect_params())
{'hidden2_weight': Parameter hidden2_weight (shape=(3, -1), dtype=float32),
'hidden2_bias': Parameter hidden2_bias (shape=(3,), dtype=float32)}
>>> net2.hidden2.share_parameters(net.hidden1.collect_params())
"""
equals to
net2.hidden2.weight=net.hidden1.weight
net2.hidden2.bias=net.hidden1.bias
"""
>>> print(net2.hidden2.weight is net.hidden1.weight)
True
>>> print(net2.hidden2.bias is net.hidden1.bias)
True
>>> net2.initialize()
/home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.py:410: UserWarning:
Parameter hidden1_weight has generated its symbol representation, which could
be used in some cached graph. Skip the operation that sets its name as
hidden2_weight.
self._set_prefix(recorded, prefix)
/home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.py:410: UserWarning:
Parameter hidden1_bias has generated its symbol representation, which could be
used in some cached graph. Skip the operation that sets its name as
hidden2_bias.
self._set_prefix(recorded, prefix)
/home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.py:694: UserWarning:
Parameter 'hidden1_weight' is already initialized, ignoring. Set
force_reinit=True to re-initialize.
v.initialize(None, ctx, init, force_reinit=force_reinit)
/home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.py:694: UserWarning:
Parameter 'hidden1_bias' is already initialized, ignoring. Set
force_reinit=True to re-initialize.
v.initialize(None, ctx, init, force_reinit=force_reinit)
>>> net2.hybridize()
>>> print(net2.collect_params())
{'hidden2_weight': Parameter hidden1_weight (shape=(3, 10), dtype=float32),
'hidden2_bias': Parameter hidden1_bias (shape=(3,), dtype=float32)}
>>> print(net2(x)) # should equal to relu(net1(x))
[[ 0.09921001 0.04954842 0.12571132]
[-0. -0. -0. ]
[ 0.0051947 -0. 0.02048509]
[ 0.10466634 -0. -0. ]
[ 0.26467288 -0. 0.16121587]]
```
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