[GitHub] TobiasSkovgaardJepsen opened a new issue #14177: Insufficient documentation for .hybridize()

[GitBox]

TobiasSkovgaardJepsen opened a new issue #14177: Insufficient documentation for 
.hybridize()
URL: https://github.com/apache/incubator-mxnet/issues/14177
 
 
   Hi
   
   I have been trying to optimize my models with hybridize and accidentally 
misspelled an argument to the method. I got the quite interesting message below 
(using a minimal example):
   ```
   >>> from mxnet.gluon.nn import Dense
   >>> from mxnet.ndarray import ones
   >>> model = Dense(10)
   >>> X =ones((1, 10))
   >>> model.initialize()
   >>> model.hybridize(unsupported_keyword_argument=True))
   >>> model(X)
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/gluon/block.py",
 line 542, in __call__
       out = self.forward(*args)
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/gluon/block.py",
 line 909, in forward
       return self._call_cached_op(x, *args)
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/gluon/block.py",
 line 799, in _call_cached_op
       self._build_cache(*args)
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/gluon/block.py",
 line 787, in _build_cache
       self._cached_op = ndarray.CachedOp(out, flags)
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/_ctypes/ndarray.py",
 line 116, in __init__
       ctypes.byref(self.handle)))
     File 
"/Users/tsj/.local/share/virtualenvs/rne-U4U7XVrs/lib/python3.6/site-packages/mxnet/base.py",
 line 251, in check_call
       raise MXNetError(py_str(_LIB.MXGetLastError()))
   mxnet.base.MXNetError: Cannot find argument 'erroneous_keyword_argument', 
Possible Arguments:
   
   ----------------
   static_alloc : boolean, optional, default=0
       Statically allocate memory to improve speed. Memory usage may increase.
   static_shape : boolean, optional, default=0
       Optimize for invariant input shapes between iterations. Must also set 
static_alloc to True. Change of input shapes is still allowed but slower.
   inline_limit : int (non-negative), optional, default=2
       Maximum number of operators that can be inlined.
   forward_bulk_size : int (non-negative), optional, default=15
       Segment size of bulk execution during forward pass.
   backward_bulk_size : int (non-negative), optional, default=15
       Segment size of bulk execution during backward pass.
   data_indices : tuple of <int (non-negative)>, optional, default=[]
       Position of argument variables.
   param_indices : tuple of <int (non-negative)>, optional, default=[]
       Position of parameters.
   ```
   
   Although I find this message quite useful, I also found it quite surprising 
since [the 
documentation](https://mxnet.incubator.apache.org/versions/master/api/python/gluon/gluon.html?highlight=hybrid#mxnet.gluon.Block.hybridize)
 only mentions `static_alloc` and `static_shape`.
   
   I am not sure what the effect of the other parameters are and when they are 
appropriate to change. I am hoping that someone could tell me and I suggest 
that the documentation be updated to describe the undocumented keyword 
arguments.

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