* Fixed bug where a shared module which was supposed to be skipped wasn't skipped on the second reference

* Added tests for new bug fix

* Bias handling:
  * Add 'bits_bias' parameter to explicitly specify # of bits for bias,
    similar to weights and activations.
  * BREAKING: Remove the now redundant 'quantize_bias' boolean parameter
* Custom overrides:
  * Expand the semantics of the overrides dict to allow overriding of
    other parameters in addition to bit-widths
  * Functions registered in the quantizer's 'replacement_factory' can
    define keyword arguments. Non bit-width entries in the overrides
    dict will be checked against the function signature and passed
  * BREAKING:
    * Changed the name of 'bits_overrides' to simply 'overrides'
    * Bit-width overrides must now be defined using the full parameter
      names - 'bits_activations/weights/bias' instead of the short-hands
      'acts' and 'wts' which were used so far.
  * Added/updated relevant tests
  * Modified all quantization YAMLs under 'examples' to reflect 
    these changes
  * Updated docs

Not backward compatible - re-installation is required

* Fixes for PyTorch==1.0.0
* Refactoring folder structure
* Update installation section in docs

Summary of changes:
(1) Post-train quantization based on pre-collected statistics
(2) Quantized concat, element-wise addition / multiplication and embeddings
(3) Move post-train quantization command line args out of sample code
(4) Configure post-train quantization from YAML for more fine-grained control

(See PR #136 for more detailed changes descriptions)

* Asymmetric post-training quantization (only symmetric supported so until now)
* Quantization aware training for range-based (min-max) symmetric and asymmetric quantization
* Per-channel quantization support in both training and post-training
* Added tests and examples
* Updated documentation

* Adding PACT quantization method
* Move logic modifying the optimizer due to changes the quantizer makes into the Quantizer itself
* Updated documentation and tests

* Add Quantizer unit tests
* Require 'bits_overrides' to be OrderedDict to support overlapping
  patterns in a predictable manner + update documentation to reflect this
* Quantizer class cleanup
  * Use "public" nn.Module APIs instead of protected attributes
  * Call the builtins set/get/delattr instead of the class special methods
    (__***__)
  * Fix issues reported in #24
* Bug in RangeLinearQuantParamLayerWrapper - add explicit override of
  pre_quantized_forward accpeting single input (#15)
* Add DoReFa test to full_flow_tests