John Howard <******@****.***> 1704863403 -0800

    *   Add `tf.keras.layers.AbstractRNNCell` as the preferred implementation
        for RNN cells in TF v2. User can use it to implement RNN cells with
        custom behavior.
    *   Keras training and validation curves are shown on the same plot when
        using the TensorBoard callback.
    *   Switched Keras `fit/evaluate/predict` execution to use only a single
        unified path by default unless eager execution has been explicitly

		{"User", Func, 0},
		{"UserPassword", Func, 0},
		{"Userinfo", Type, 0},
		{"Values", Type, 0},
	},
	"os": {
		{"(*File).Chdir", Method, 0},
		{"(*File).Chmod", Method, 0},
		{"(*File).Chown", Method, 0},
		{"(*File).Close", Method, 0},
		{"(*File).Fd", Method, 0},
		{"(*File).Name", Method, 0},
		{"(*File).Read", Method, 0},
		{"(*File).ReadAt", Method, 0},
		{"(*File).ReadDir", Method, 16},

end and stride, while the new_axis_mask bit is set.

4. `...` grab the full ranges from as many dimensions as needed to
fully specify a slice for every dimension of the input shape.

5. `:-3:-1` shows the use of negative indices. A negative index `i` associated
with a dimension that has shape `s` is converted to a positive index
`s + i`. So `-1` becomes `s-1` (i.e. the last element). This conversion