Faster RCNN, Sequence to Sequence, Reshape layer, updated pip requirements

• Faster RCNN model
• Sequence to Sequence container and char_rae recurrent autoencoder model
• Reshape Layer that reshapes the input [#221]
• Pip requirements in requirements.txt updated to latest versions [#289]
• Remove deprecated data loaders and update docs
• Use NEON_DATA_CACHE_DIR envvar as archive dir to store DataLoader ingested data
• Eliminate type conversion for FP16 for CUDA compute capability >= 5.2
• Use GEMV kernels for batch size 1
• Alter delta buffers for nesting of merge-broadcast layers
• Support for ncloud real-time logging
• Add fast_style Makefile target
• Fix Python 3 builds on Ubuntu 16.04
• Run setup.py for sysinstall to generate version.py [#282]
• Fix broken link in mnist docs
• Fix conv/deconv tests for CPU execution and fix i32 data type
• Fix for average pooling with batch size 1
• Change default scale_min to allow random cropping if omitted
• Fix yaml loading
• Fix bug with image resize during injest
• Update references to the ModelZoo and neon examples to their new locations