Elektronn2

- Add new augmentation methods:
* random image region blurring (`BatchCreatorImage.blurry_blobs_probability`)
* random erasing
- with noise: `BatchCreatorImage.noisy_random_erasing_probability`)
- with constant values (`BatchCreatorImage.uniform_random_erasing_probability`)
- Remove broken `--gpu=auto` option from `elektronn2-train`
- Add `zxy` flag to `BatchCreatorImage`, making loading data in xyz axis order possible
- Improve version strings with versioneer (git revision and uncommitted modifications are now reflected in `elektronn3.__version__`, making identification of the current version easy)
- Various small improvements and bug fixes

This is the last planned release of ELEKTRONN2. We are focusing on [elektronn3](https://github.com/ELEKTRONN/elektronn3) now.

- Fix `model.modelload()` when using the new `Conv` constructor with optional `pool_shape`. Loading models from .mdl files was broken in 0.5.0 (13, c2a7b8a)
- Better progressbar for `model.predict_dense()` (thanks mahsabh, 6ee6d18)
- Extend maximum runtime and iterations of example networks to make sure they can be fully trained (970bfa4, 86fea4c)

- The new, more flexible `AutoMerge` operation replaces `UpConvMerge` (`UpConvMerge` is still available as an alias to `AutoMerge` for backwards compatibility) (da5b648, 45c507e, e45082c, 660c945).
* New `merge_mode` argument, which specifies the Node type to perform the merging (`'concat'` or `'add'`. This simplifies usage of the new `Add` node (using `merge_mode='add'`).
* Automatic uponvolutions can now be disabled (`disable_upconv=True`), making it a mere autocrop-merge wrapper.
* Better log output that tells how the parents are merged and what operations are automatically performed for merging. If an `UpConv` is inserted, it is explicitly logged.
* `kwargs` for the possible UpConv call are now bundled to `upconv_kwargs` to clean up the signature (potentially breaking change).
* Renamed some parameters (breaking, see new signature of `AutoMerge`)
* If used for two differently-sized input nodes, the larger one doesn't need to be the first one any more. Sizes are detected automatically now.
* The concept of high-res and low-res inputs is now explicitly optional (this still needs some refactoring to be more clear).
- Better exception handling by the trainer (71914ce). Errors messages are now displayed correctly when preview predictions fail.
- Reduce annoying malis import warning to "debug" log level (de8f414). Note: Fixing malis support is not on my short-term TODO-list and malis is not properly built in or documented, so these warnings were just distracting. Related to 3. (If there is any real demand for malis support, please tell me, then I will try to fix it soon)
- (WIP) Support SAME-mode convolutions (`border_mode='same'`) via Theano's `'half'` mode (3dd35df). There is an issue with the `fov` calculation of `Conv` nodes that use `border_mode='same'`. The `invalidate_fov=True` hack (0691711) can be used as a temporary fix until the `fov` calculation works as intended.
- (WIP) Experimental new `Pad` node for value-padding along spatial a image tensors (1d27a87).
- More nodes print their `__repr__` upon initialisation, making logs more clear.
- Support (path, key) tuples as hdf5 data path for preview predictions (81483b7).
- Fix preview predictions of unet3d example by using validation data for previews (preview data of neuro_data_zxy was too small). (05adabe)
- Fix sphinx CSS issue. (c7ba3ae)

- `(1,1,1)`-maxpoolings are now implied in `Conv` Node constructors → less redundant code in network models that don't use conv-pool layer stacks (917bdea, c81294e)
- New `Add` Node type for merging two network branches (cd87b78)
- Use the short form `nm` for the `elektronn2.neuromancer` module throughout examples and docs (8a412d0)

- Support ELU and SELU activation functions for Self-Normalizing Networks (12, e27276a)
- Log everything to stdout instead of stderr to make terminal output recording less confusing (5214e30)
- Fix file system permission problems on multi-user systems by changing output file names (8a436ef, 7661fe7)
- Documentation fixes, tables are now displayed correctly

- New `elektronn2-profile` command for profiling and finding optimal input sizes of already trained neural networks
- Default save directory of examples is now `~/elektronn2_training`
- Disable initial debug plots on `elektronn2-train` startup (3eec2c9)
- Many improvements to U-Net-based config examples (8866e1b, 25cd87c)
- Move examples that are yet not ready to use to `examples/wip`
- Many documentation updates (New section on predictions, new detailed installation instructions, better index page, improvements to some docstrings)
- Correct many typos in code and docs
- Minor bug fixes