我正在尝试构建自定义池层(对于ndarray和Symbol)和我需要知道运行时的输入形状。根据文档,HybridBlock具有“infer_shape”功能,但我无法使其工作。任何关于我做错的指示?
1.0.0,从conda,python3构建。
例如:
import mxnet as mx
import mxnet.ndarray as nd
from mxnet.gluon import HybridBlock
class runtime_shape(HybridBlock):
def __init__(self, **kwards):
HybridBlock.__init__(self,**kwards)
def hybrid_forward(self,F,_input):
print (self.infer_shape(_input))
return _input
xx = nd.random_uniform(shape=[5,5,16,16])
mynet = runtime_shape()
mynet.hybrid_forward(nd,xx)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-41-3f539a940958> in <module>()
----> 1 mynet.hybrid_forward(nd,xx)
<ipython-input-38-afc9785b716d> in hybrid_forward(self, F, _input)
17 def hybrid_forward(self,F,_input):
18
---> 19 print (self.infer_shape(_input))
20
21 return _input
/home/dia021/anaconda2/lib/python2.7/site-packages/mxnet/gluon/block.pyc in infer_shape(self, *args)
460 def infer_shape(self, *args):
461 """Infers shape of Parameters from inputs."""
--> 462 self._infer_attrs('infer_shape', 'shape', *args)
463
464 def infer_type(self, *args):
/home/dia021/anaconda2/lib/python2.7/site-packages/mxnet/gluon/block.pyc in _infer_attrs(self, infer_fn, attr, *args)
448 def _infer_attrs(self, infer_fn, attr, *args):
449 """Generic infer attributes."""
--> 450 inputs, out = self._get_graph(*args)
451 args, _ = _flatten(args)
452 arg_attrs, _, aux_attrs = getattr(out, infer_fn)(
/home/dia021/anaconda2/lib/python2.7/site-packages/mxnet/gluon/block.pyc in _get_graph(self, *args)
369 params = {i: j.var() for i, j in self._reg_params.items()}
370 with self.name_scope():
--> 371 out = self.hybrid_forward(symbol, *grouped_inputs, **params) # pylint: disable=no-value-for-parameter
372 out, self._out_format = _flatten(out)
373
/home/dia021/anaconda2/lib/python2.7/site-packages/mxnet/gluon/block.pyc in __exit__(self, ptype, value, trace)
78 if self._block._empty_prefix:
79 return
---> 80 self._name_scope.__exit__(ptype, value, trace)
81 self._name_scope = None
82 _BlockScope._current = self._old_scope
AttributeError: 'NoneType' object has no attribute '__exit__'
答案 0 :(得分:3)
HybridBlock的想法是在命令式世界中轻松调试,您可以简单地设置断点或print
语句,并查看网络中正在传输的数据。当您确信网络正在按照您的意愿行事时,您可以致电.hybridize()
并享受速度提升。
在开发网络和使用命令式模式的同时,您只需打印:
print('shape',_input.shape)
并在使用网络的混合版本时删除此行,因为这仅适用于NDArrays。
如果这不能回答您的问题,您是否可以通过获取输入数据的形状来确定您要实现的目标是什么?