More layers and models

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.

New models

• 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

Class-based models