code: def _slice(
      operand,
      start_indices,
      dynamic_slice_sizes,
      static_slice_sizes,
      fill_value=0,
  ):
      """Similar to lax.dynamic_slice, but handles arrays with dynamic sizes.
  
      Returns fill_value instead of clamping start_indices for those elements that
      would overflow the side of the array.
  
      Args:
        operand: the array to slice
        start_indices: the offset of the start of the slice
        dynamic_slice_sizes: the true (unpadded) size of the slice
        static_slice_sizes: the padded size of the slice, which must be known at
          compile time. The static size must be larger than the dynamic size.
        fill_value: value with which to replace masked-out elements.
      Returns:
        An array with static shape `static_slice_sizes`, padded from its true
        (dynamic) size `dynamic_slice_sizes`.
      """
      # We must pad the input array so the dynamic_slice is guaranteed to fall
      # entirely in bounds.
      padded = lax.pad(
          operand,
          jnp.array(0, operand.dtype),
          [(0, d, 0) for d in static_slice_sizes],
      )
      out = lax.dynamic_slice(
          padded,
          tuple(jnp.int32(i) for i in start_indices),
          static_slice_sizes,
      )
      return _mask(out, dynamic_slice_sizes, fill_value)
  
imports: from __future__ import annotations
  from functools import partial
  from typing import NamedTuple
  import jax
  import jax._src.numpy.lax_numpy
  import jax._src.numpy.linalg
  from jax._src.numpy import reductions
  from jax._src.numpy import ufuncs
  from jax import lax
  from jax._src.lax import qdwh
  from jax._src.lax import linalg
  from jax._src.lax.stack import Stack
label_desc: Use image node_id 3 for calling a global function with example usage: _slice(operand, start_indices, dynamic_slice_sizes, static_slice_sizes, fill_value) and returns: _mask