abstract: TensorFlow is a machine learning system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture...

    *   In `map_vectorization` optimization, reduce the degree of parallelism in
        the vectorized map node.
    *   Add variant wrapper for `absl::string_view`.
    *   Add OpKernels for some stateless maps.
    *   DType is no longer convertible to an int. Use `dtype.as_datatype_enum`
        instead of `int(dtype)` to get the same result.
    *   Support both binary and -1/1 label input in v2 hinge and squared hinge