update params failed when params and grads are empty

[roywei]

This PR #13346 has changed the logic for updating parameters here

However it broke a unit test in downstream project Keras-MXNet. I was able to reproduce using pure MXNet:

Steps to reproduce

import mxnet as mx
from mxnet.io import  DataBatch
from mxnet import nd
data = mx.sym.Variable('data')
out  = mx.sym.Dropout(data, 0.5)
mod = mx.mod.Module(out)
mod.bind(data_shapes=[('data',(1,10))])
mod.init_params()
mod.init_optimizer()
data_batch = DataBatch([nd.random.uniform(0,1,(10,10))])
mod.forward(data_batch)
mod.backward()
mod.update()

will have the following error msg:

/Users/lawei/anaconda3/bin/python /Users/lawei/Documents/Workspace/roywei/incubator-mxnet/example/test.py
/Users/lawei/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters
/Users/lawei/Documents/Workspace/roywei/incubator-mxnet/python/mxnet/module/base_module.py:55: UserWarning: You created Module with Module(..., label_names=['softmax_label']) but input with name 'softmax_label' is not found in symbol.list_arguments(). Did you mean one of:
	data
  warnings.warn(msg)
/Users/lawei/Documents/Workspace/roywei/incubator-mxnet/python/mxnet/module/base_module.py:67: UserWarning: Data provided by label_shapes don't match names specified by label_names ([] vs. ['softmax_label'])
  warnings.warn(msg)
Traceback (most recent call last):
  File "/Users/lawei/Documents/Workspace/roywei/incubator-mxnet/example/test.py", line 13, in <module>
    mod.update()
  File "/Users/lawei/Documents/Workspace/roywei/incubator-mxnet/python/mxnet/module/module.py", line 671, in update
    param_names=self._exec_group.param_names)
  File "/Users/lawei/Documents/Workspace/roywei/incubator-mxnet/python/mxnet/model.py", line 184, in _update_params
    i, w, g = zip(*dev_updates)
ValueError: not enough values to unpack (expected 3, got 0)

Root cause

when you do update on a operator that does not require params/grads, it will crash due to the updates became a list of empy list [[]] here

Originally when we do param update, if paras and grads are both [], we would just skip it and don't do update.

Although this is not a common usage in MXNet to call module udpate on layers withou params. but I would like to keep the original logic as Keras-MXNet depends on it.

What have you tried to solve it?

Will create a PR to check empy list

[mxnet-label-bot]

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