GitLab

* Sync SyntaxNet with TensorFlow r1.0

* Fix typo back

* Fix Dockerfile to match TensorFlow 1.0

Fixes #657

For English News Corpus,
[Ling et al. (2015)](http://www.cs.cmu.edu/~lingwang/papers/emnlp2015.pdf)'s score is 
97.78 -> 97.44 (lower than SyntaxNet and Parsey Mcparseface)
according to [Andor et al. (2016)](http://arxiv.org/abs/1603.06042).

Updates to syntaxnet, including update tensorflow sub-module, bazel requirement and fix trainer crash (#479)

* syntaxnet: Cosmetic fixes recommended by python lint.

* syntaxnet: Fix crash in parser_trainer due to inconsistency between LexiconBuilder::Compute()
	   and context.pbtxt definition ('char-map' input declaration was missing).

* syntaxnet: reduce flakiness in GraphBuilderTest.

* syntaxnet: Update tensorflow submodule to version > 0.10.

* syntaxnet: Update to latest stable bazel (0.3.1).

This update comes partially to allow Tensorflow submodule to build
succesffuly. In this commit, I also update and simplify the WORKSPACE,
to avoid declaring dependencies already present in tensorflow.

* syntaxnet: Update bazel version check to require version 0.3.0

* syntaxnet: Document pip requirement, along with python mock module.

* Update README.md

Added alternative way to install bazel. Because people have been facing problem and by mistake they are downloading the latest version.

* Update README.md

Fixed conll2tree.py; handling correctly a sentence that has multiple elements with identical representation (#292)

* Adding scripts for tokenization and parsing in new languages.

* Adding:
  - offset feature locator,
  - last word feature function,
  - untokenized text format.

* Adding references to @calberti and @andorardo to syntaxnet readme.

* Morpher and segmenter transition systems and new features (quotes, punctuation, capitalization, character ngrams, morphology attributes).

Cleanup changes for syntaxnet.

* TF defines the same external repositories but with different commit and BUILD

* Fix a bunch of bazel namespace issues

@tf changed to @org_tensorflow
Tensorflow stopped using protobuf as submodule, now it's external, so use @protobuf

* Sync to master of tensorflow submodule:
  - local version of is_cuda in syntaxnet.bzl,
  - using unique_ptr in file api.

As Docker builds are layer by layer, removing cached package files in different layers do not reduce image size. To reduce image size, cached packages have to removed in the same layer i.e., `RUN` command as the packages have been installed.
Signed-off-by: Riyad Parvez <social.riyad@gmail.com>

* Updating TF submodule to latest and adding a Dockerfile example.

* Extra \n in ./configure.

* Updating Dockerfile to use bazel 0.2.2b.

* Replacing a mention of treebank_union with PMP in the README.

* doc: Add instructions on installing numpy

* fix typo