Use nn.softmax in keras.activations.softmax

[szutenberg]

There are two issues with tf.keras.activations.softmax :

First:
it implements softmax for 3D+ tensors in not optimal way due to old workarounds:

• Keras: Support for 3D+ tensors was added on Nov 29, 2015 keras-team/keras@8f2d6d2
• TF: In that time tensorflow did not support multiple dimensions: issue was reported on Jun 29, 2016 (Softmax for multiple dimensions) Softmax for multiple dimensions #3101
• TF: Support for multiple dimensions was added on Aug 29, 2016 aeac274
• TF: Improved kernel accepting shapes with higher ranks was added on Aug 6, 2018 f3aa5d4

For 3D tensor, the softmax gradient is getting really complicated which seriously hurts performance. example:

Second:
It returns wrong results for 2D tensors, axis=0. I also prepared unit test for this scenario.

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[szutenberg]

@googlebot I signed it!

[fchollet]

LGTM, thanks