[BUGFIX] fix unknown parameter shapes when np_shape is turned on.

[zheng-da]

Description

When np_shape is turned on, the unknown parameter shapes should be -1 instead of 0. So when a parameter is created but isn't initialized, the dimension of unknown size is -1 when np_shape is turned on, and is 0, otherwise.

Checklist

Essentials

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• To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

[reminisce]

I think the following two places checking whether the shape is known should be modified too.
https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/parameter.py#L272
https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/gluon/parameter.py#L383

[reminisce]

I'm worried about this line
https://github.com/apache/incubator-mxnet/blob/5fc4fc53df74f276aafa51208142e657e9cfe42d/python/mxnet/gluon/parameter.py#L168

Users may notice that we started to use -1 to represent unknown dim size in np shape semantics and some of them in practice may use shapes like (-1, 10) to create parameters for deferred initialization, instead of (0, 10). In those cases, we need to support that unknown dim size can be either 0 or -1, so this line should become

all(j in (-1, 0, i) for i, j in zip(new_shape, self._shape))

when is_np_shape = True.

@szha What do you think?

[abhinavs95]

@mxnet-label-bot add [Gluon]

[szha]

@reminisce I had similar concern though I thought the API doc should do the job. another option is to expose an internal interface for infer_shape to use, instead of piggybacking on the .shape attribute

[roywei]

@reminisce @szha @zheng-da what's the next step here? There is nothing to prevent users from using -1 as unknown dim. so maybe state clearly in comment or API doc and note experimental?

[reminisce]

I think it would be safer to note np_shape as experimental and still under development.

[zheng-da]

where should we document -1 is unknown dim and is experimental?

[roywei]

I believe for NP shape APIs, it's already documented as experimental, so just add some comments in this PR about -1 and refer to the np documentation here https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/util.py#L84