Float16 support + Improved Context hyperparameter support + GNNs layer-wise inference

[janpfeifer]

• types.shapes package:
  • Added support for Float16 training -- tested with GNNs.
    • Up-precision metrics dtypes if they are Float16.
    • Allow arbitrary dtype for Adam optimizer -- it requires at least float32, even if the model runs on float16.
    • DType dependent epsilon values for Softmax and Adam -- current values would lead to NaN with float16.
    • Added DType.IsFloat16 to check for Float16 or BFloat16 (not yet well-supported).
  • Added support for Int8, Int16, Uint8 and Uint16.
  • Renamed UInt{X} to Uint{X} and added a deprecated alias to the old form (so it still compiles).
• Added logging of time to build and compile graph. Last version improved a lot the execution time, but slowed the compilation.
• Fixed Variable.SetValueGraph when the shape changes. Improved some documentation.
• Package optimizers:
  • Fixed optimizer constructor FromContext to allow further configuration of the optimizer by setting other hyperparameters into context.
  • Added hyperparameter clip_step_by_value, a clip by value applied to gradient updates.
  • Adam optimizer: "clip_step_by_value", "adam_epsilon", "adam_dtype" hyperparameters support.
  • MustOptimizerByName now takes also the context for the optimizer hyperparameters. -- this breaks the API.
• Package checkpoints:
  • Allow adding variables to exclude from saving after checkpoint is created -- for newly created variables.
• Added slices.CloseToEpsilon to easily customize tests.
• Fixed Variable.SetValuePreservingOld when shapes change.
• Scatter doesn't assume indices are sorted or unique.
• Plotly training plots: added WithCustomMetricFn for custom metrics and ScheduleEveryNSteps.
• Added OGBN_MAG GNN example:
  • Including Layer-Wise Inference.
• Package graph:
  • Added Shift, ShiftLeft, ShiftRight, ShiftWithScalar, ShiftWithValue.