This is a major release with a lot of new features related to static types for tensors and ops. The graph construction API is now statically-typed, thus enabling much better type safety than before.

Tensors and outputs are now statically-typed and the types used are the Scala types that correspond to the tensors' TensorFlow data types. For example:

val t1 = Tensor(0.5, 1) // The inferred type is Tensor[Double].
val t2 = Tensor(1, 2)   // The inferred type is Tensor[Int].
val t3 = t1 + t2        // The inferred type is Tensor[Double].
val t4 = t3.isNaN       // The inferred type is Tensor[Boolean].
val t5 = t3.any()       // Fails at compile-time because `any()` is only
                        // supported for Tensor[Boolean].

A similar situation now applies to Outputs. Ops are also typed and so is the auto-differentiation implementation.

This resulted in major simplifications in the data pipeline and the high level learn API. Datasets and dataset iterators do not "carry" T, V, D, and S types with them now, but rather just the type of the elements they contain/produce.

A new type trait called is also introduced that denotes supported Scala types in TensorFlow (e.g., and ). Similarly, some more type traits are introduced to denote type constraints for various ops (e.g., , , , etc.). These type traits are powered by a general implementation of union types for Scala.