Add UML diagrams

.gitignore

@@ -3,6 +3,6 @@
 *.mod
 *.smod
 *.dat
-*.h5
-/build
-/doc
+build
+doc/html
+*.h5

doc/README.md

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+# Developer documentation
+
+## UML Diagrams
+
+Use a PlantUML previewer to generate Unified Modeling Language (UML) diagrams
+from the PlantUML scripts (`*.puml`) in this subdirectory.
+The generated versions below were created by the renderer on the
+[PlantUML landing page](https://plantuml.com)
+
+### Class Hierarchy
+
+This diagram provides a high-level picture of the neural-fortran classes and
+their interrelationships:
+![class-hierarchy](https://user-images.githubusercontent.com/13108868/168928394-9fbf7880-0b11-4eb5-9106-baeb3ae3482d.png)
+
+### Developer API
+
+This diagram enhances the above class hierarchy depiction to include a richer
+summation of the public interface of each class, including the public derived
+types, type-bound procedures, and user-defined structure constructors:
+
+![developer-api](https://user-images.githubusercontent.com/13108868/168961635-1f43641f-8144-4c4c-aa61-9f7140650e42.png)
+
+For a depiction of the derived type components (but without the richness of
+information on interrelationships), generate the HTML documentation using
+[FORD](https://github.com/modern-fortran/neural-fortran#api-documentation).
+
+### User API
+
+This diagram depicts the functionality intended to be accessed directly by
+neural-fortran users:
+
+TBD

doc/class-hierarchy.puml

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+@startuml
+
+title Class Hierarchy
+
+hide empty members 
+
+class sgd
+
+abstract class base_layer
+
+network *-left- layer 
+
+base_layer <|-- maxpool2d_layer
+base_layer <|-- input3d_layer
+base_layer <|-- dense_layer
+base_layer <|-- conv2d_layer
+base_layer <|-- input1d_layer
+
+@enduml

doc/developer-api.puml

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+@startuml
+
+title Developer API: Public Classes, Type-Bound Procedures, and Constructors
+hide empty members 
+
+class sgd
+
+abstract class base_layer {
+  {abstract} init_interface(input_shape : integer)
+  set_activation(activation : character(len=*))
+}
+
+class maxpool2d_layer{
+  maxpool2d_layer(pool_size: integer, stride : integer) : maxpool2d_layer
+  init(input_shape : integer)
+  forward(input : real[][][])
+  backward(input : real[][][], gradient : real[][][])
+}
+
+class input3d_layer{
+  input3d_layer(output_shape : real[]) : input3d_layer
+  init(input_shape : real[])
+  set(values : real[][][])
+}
+
+class dense_layer{
+  dense_layer(output_size : integer, activation : character(len=*)) : dense_layer
+  backward(input : rea[], gradient : real[])
+  forward(input : real[])
+}
+
+class conv2d_layer{
+  conv2d_layer(filters : integer, kernel_size : integer, activation : character(len=*))
+  init(input_shape : integer[])
+  forward(input : real[][][])
+  backward(input : real[][][], gradient : real[][][])
+}
+
+class input1d_layer{
+  input1d_layer(output_size : integer)
+  init(input_shape:integer)
+  set(values : real[])
+}
+
+
+class network {
+  network(layers[] : layer) : network
+  backward(output : real[])
+  output(input : real[]) : real[]
+  print_info()
+  train(input_data:real[][], output_data:real[][], batch_size:integer, epochs:integer, optimizer:sgd)
+  update(learning_rate:real)
+  forward(input : real[])
+  forward(input : real[][][])
+}
+
+class layer{
+  backward(previous : layer, gradient : real[])
+  forward(input : layer)
+  init(input : layer)
+  print_info()
+  update(learning_rate : real)
+  get_output(output : real[])
+  get_output(output : real[][][])
+}
+
+network *-left- layer 
+
+base_layer <|-- maxpool2d_layer
+base_layer <|-- input3d_layer
+base_layer <|-- dense_layer
+base_layer <|-- conv2d_layer
+base_layer <|-- input1d_layer
+
+@enduml