szha commented on a change in pull request #12512: [MXNET-938] Allow fusing
weight ahead of calling forward()
URL: https://github.com/apache/incubator-mxnet/pull/12512#discussion_r217132369
##########
File path: python/mxnet/gluon/rnn/rnn_layer.py
##########
@@ -183,6 +184,16 @@ def begin_state(self, batch_size=0, func=ndarray.zeros,
**kwargs):
states.append(func(name='%sh0_%d'%(self.prefix, i), **info))
return states
+ def fuse_weights(self, F):
+ if F is ndarray:
+ kwargs = {i: j.data() for i, j in self._reg_params.items()}
+ params = (kwargs['{}{}_{}_{}'.format(d, l, g, t)].reshape(-1)
+ for t in ['weight', 'bias']
+ for l in range(self._num_layers)
+ for d in ['l', 'r'][:self._dir]
+ for g in ['i2h', 'h2h'])
+ self.fused_params = F.concat(*params, dim=0)
Review comment:
The fused parameter wouldn't reflect updates in the parameters.
```
In [1]: import mxnet as mx
In [2]: a = mx.nd.arange(5)
In [3]: b = mx.nd.ones((3,))
In [4]: c = mx.nd.concat(a, b, dim=0)
In [5]: c
Out[5]:
[0. 1. 2. 3. 4. 1. 1. 1.]
<NDArray 8 @cpu(0)>
In [6]: a[0] = 5
In [7]: a
Out[7]:
[5. 1. 2. 3. 4.]
<NDArray 5 @cpu(0)>
In [8]: c
Out[8]:
[0. 1. 2. 3. 4. 1. 1. 1.]
<NDArray 8 @cpu(0)>
```
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