Network.to_json should handle numpy.ndarray correctly.

[yanboliang]

Summary

Similar as #10727, when we serialize a Network by to_json, we should handle numpy.ndarray correctly if there is. For example:

model = Sequential()
model.add(Dense(2, input_shape=(3,), kernel_initializer=Constant(np.ones((3, 2)))))
model.add(Dense(3))
model.compile(loss='mse', optimizer='sgd', metrics=['acc'])
model.to_json()

It throws the following error:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "keras/engine/network.py", line 1205, in to_json
    return json.dumps(model_config, default=get_json_type, **kwargs)
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/__init__.py", line 250, in dumps
    sort_keys=sort_keys, **kw).encode(obj)
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/encoder.py", line 207, in encode
    chunks = self.iterencode(o, _one_shot=True)
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/json/encoder.py", line 270, in iterencode
    return _iterencode(o, 0)
  File "keras/engine/network.py", line 1196, in get_json_type
    return obj.item()
ValueError: can only convert an array of size 1 to a Python scalar

Note: tf.keras should have the same issue, will send a fix if this get approved.

Related Issues

PR Overview

• This PR requires new unit tests [y/n] (make sure tests are included)
• This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
• This PR is backwards compatible [y/n]
• This PR changes the current API [y/n] (all API changes need to be approved by fchollet)

[fchollet]

LGTM, thanks.

I believe tf.keras would have the same issue. Please consider creating a PR in the TensorFlow repository as well.