## Bug Fixes and Other Changes

*   tf.data:
    *   tf.data users can now represent, get, and set options of TensorFlow
        input pipelines using `tf.data.Options()`, `tf.data.Dataset.options()`,
        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.

25A0..25EF    ; valid                  ;      ; NV8    # 1.1  BLACK SQUARE..LARGE CIRCLE
25F0..25F7    ; valid                  ;      ; NV8    # 3.0  WHITE SQUARE WITH UPPER LEFT QUADRANT..WHITE CIRCLE WITH UPPER RIGHT QUADRANT
25F8..25FF    ; valid                  ;      ; NV8    # 3.2  UPPER LEFT TRIANGLE..LOWER RIGHT TRIANGLE

A survey conducted in early 2019 by the working group (WG) Long Term Support (LTS) showed that a significant subset of Kubernetes end-users fail to upgrade within the previous 9-month support period. 
A yearly support period provides the cushion end-users appear to desire, and is more in harmony with familiar annual planning cycles.

## Known Issues

{\n  background-image: var(--bs-gradient) !important;\n}\n\n.user-select-all {\n  -webkit-user-select: all !important;\n  -moz-user-select: all !important;\n  user-select: all !important;\n}\n\n.user-select-auto {\n  -webkit-user-select: auto !important;\n  -moz-user-select: auto !important;\n  user-select: auto !important;\n}\n\n.user-select-none {\n  -webkit-user-select: none !important;\n  -moz-user-select: none !important;\n  user-select: none !important;\n}\n\n.pe-none {\n  pointer-events: none...

//go:norace func (out *Nat) Mod(x *Nat, m *Modulus) *Nat { out.resetFor(m) // Working our way from the most significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need to reduce every time we shift. i := len(x.limbs) - 1 // For the first N - 1 limbs we can skip...

```Python
def get_current_user(token: str):
    # authenticate user
    return User()


@app.get("/items/")
def read_items(user: User = Depends(get_current_user)):
    ...


@app.post("/items/")
def create_item(*, user: User = Depends(get_current_user), item: Item):
    ...


@app.get("/items/{item_id}")
def read_item(*, user: User = Depends(get_current_user), item_id: int):
    ...

//go:norace func (out *Nat) Mod(x *Nat, m *Modulus) *Nat { out.resetFor(m) // Working our way from the most significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need to reduce every time we shift. i := len(x.limbs) - 1 // For the first N - 1 limbs we can skip...