Batchflow

Bug fixes and a lot of refactoring.

Batch
Components can be added dynamically during execution.
Parameters order is changed in `apply_transform` and `apply_transform_all`.


Named expressions:
- `B()` returns the batch itself.
- `F` takes args and kwargs.
- added `R` (random) and `L` (lambda).


Pipeline
Refactored models directory and variables directory.
Added `print`.
Removed `print_variable`.


Tensorflow

Layers
Added:
- 1d and 3d bilinear resize
- 3d depth to space
- separable transposed convolutions
- subpixel convolutions
- bilinear additive resize
- upsample
- alpha dropout
- universal pooling and global_pooling

Changed:
- `conv_block` support residuals (with sum and concat) and upsample layers.


TFModel:
- new methods: upsample, Pyramid Pooling module, Atrous Spatial Pyramid Pooling module
- model predictions can be an output of predefined operations (sigmoid, softmax, argmax, etc)


Model zoo
Added DenseNetFC, ResNetAttention, VNet, RefineNet, Faster-RCNN, Global Convolution Network, Encoder-decoder, Inception-ResNet v2, MobileNet v2.

* Changed model structure and configuration (with default_config() and build_config())

* Added ready to use TensorFlow models: VGG, Inception v1, v3, v4, ResNet, MobileNet, SqueezeNet, DenseNet, FCN32, FCN16, FCN8, UNet, LinkNet.

* Added new layers: fractional_max_pooling.

* Dimensionality for all layers is now inferred from the input tensor shape.

* Added fake njit decorator for environments without numba installed.

Class-based models