&x); out != &v || !isReduced(out.Bytes()) { return false } // Test aliasing the first argument and the receiver. v1 = x if out := f(&v1, &v1, &x); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing the second argument and the receiver. v1 = x if out := f(&v1, &x, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing both arguments and the receiver. v1 = x if out := f(&v1, &v1, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return...

&x); out != &v || !isReduced(out.Bytes()) { return false } // Test aliasing the first argument and the receiver. v1 = x if out := f(&v1, &v1, &x); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing the second argument and the receiver. v1 = x if out := f(&v1, &x, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return false } // Test aliasing both arguments and the receiver. v1 = x if out := f(&v1, &v1, &v1); out != &v1 || v1 != v || !isReduced(out.Bytes()) { return...

        and `tf.data.Dataset.with_options()` respectively.
    *   New `tf.data.Dataset.reduce()` API allows users to reduce a finite
        dataset to a single element using a user-provided reduce function.
    *   New `tf.data.Dataset.window()` API allows users to create finite windows
        of input dataset; when combined with the `tf.data.Dataset.reduce()` API,
        this allows users to implement customized batching.