* Add op::Sigmoid to nvgpu.

* Bring rnn fusion and concat passes over into GPU from IA. This is a temporary move until generalization and gpu specification can occur.

* Add LSTM fusion and cudnn inference kernel. Next need recurrent fusion and layer fusion.

* Formatting

* Removed unecessary extra output from LSTM op (rnn with seq. length = 1, so y = hy).

* Add RNN fusion of LSTM cells within a recurrent layer.

* Formatting.

* Add fusion across RNN layers.

* Formatting.

* Add algebraic simplification.

* Added rnn fusion tests.

* Updated conditional on LSTM fusion to better distinguish bound nodes as ht vs xt.

* Formatting.

* Removed print statements.

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* Committing missing file.

* Remove concat inputs pass and mkldnn references.

* fix cmake paths

* conflict resolution with merge from master.

* remove explicit lstm op support. bare LSTM ops are converted to RNN ops for emission.

* Formatting.

* Use NGRAPH_ASSERT. Formatting of intel copyright.

* Add check on the feature size (shape) of the recurrent (hidden) input and cell state, to ensure they are the same size.

* fix wrong rnn header

* Formatting.

* Add back lstm op to dispatch table.

* Added RNN test which shows cudnn rnn kernel is not producing correct results.

* With update to AlgSimpl. to simplify concat-reshape-slice, the check modifed in this commit needed to be relaxed.

* Bug fix in parameter tensor packing.

* Alias third output element of RNN for cell state (bug fix).

* Resolve numerical correctness issue with negative values in RNN (bug fix).
Add minimal test to evaluate LSTM and compare with values calculated by hand.

* Add tensor parameter sizes to kernel hash as
they are kernel-specific.

* Add 2 layer lstm fusion test against by-hand solution.

* Export param concatenation to graph for cudnn kernel at both the single rnn layer and multi-layer.

* Formatting.

* Finishing touches after merge: add support for macro expansed dispatch via op_tbl.

* Simplify macro support for gpu ops.

* Add CUDNN_VERSION >= 7200 defguards for RNN fusion.
Need to decide how to notify user of increased performance with >= 7200.

* Revert lstm_analytic test to explicitly copy data to tensor params.

* Removed namespace arg from NGRAPH_GPU_OP.

* Refactored macros to different header so op_tbl only contains op list.

* Defguard on cudnn_descriptor<cudnnRNNDataDescriptor_t>.

* doubles -> floats

* Reorg. pass asserts, prepare to replace with non-throwing pass failures.

* Remove Lstm op and replace it with Rnn.

* Format

* Utilize RETURN_IF_FALSE in rnn pass to avoid any RT asserts.
Note that falling back to raw (no passes) graph for 2rnn_3lstm json from mxnet models
results in a double free inside of the memory layout pass. Appears to be a bug
in Reshape pass through.

* Removed print statements. Add check on input data and recurrent data.

* Don't reuse memory for non-destructive ops.

* Add back Rnn test.

* Formatting.

* Clean up comments.

* Update test per review comments.