warp.tile\_assign
=================

.. currentmodule:: warp._src.lang

.. function:: tile_assign(dst: Tile[Any, tuple[int, ...]], src: Tile[Any, tuple[int, ...]], offset: tuple[int, ...] = ...) -> None

   .. wp-function-tags::
      :kernel: true
      :python: false
      :differentiable: true

   Copy a tile into a subrange of a destination tile.
   
   ``dst`` is modified in place and requires shared storage.
   
   When ``src`` and ``dst`` have different element types, each element is converted
   following C++ conversion rules. Overlapping source and destination regions assign
   like NumPy; ``t[1:] = t[:-1]`` shifts the tile.
   
   In a backward pass, gradients from the overwritten region of ``dst`` are accumulated
   into the adjoint of ``src``, then cleared from that region of ``dst``.
   
   :param dst: Destination tile, modified in place. Must have the same number of dimensions
               as ``src``.
   :param src: Source tile. Must fit inside ``dst`` at ``offset`` along every axis.
   :param offset: Coordinate in ``dst`` at which to write ``src``. If omitted, ``src`` is
                  written at the origin. Must have one entry per dimension of ``dst`` and may
                  contain runtime values.
   
   .. rubric:: Example
   
   .. testcode::
   
       @wp.kernel
       def insert_values(a: wp.array[float], out: wp.array[float]):
           dst = wp.tile_full(shape=6, value=-1.0, dtype=float)
           src = wp.tile_load(a, shape=3)
   
           wp.tile_assign(dst, src, offset=(2,))
   
           wp.tile_store(out, dst)
   
       a = wp.array([1.0, 2.0, 3.0], dtype=float)
       out = wp.zeros(6, dtype=float)
   
       wp.launch_tiled(insert_values, dim=1, inputs=[a], outputs=[out], block_dim=4)
   
       print(out.numpy())
   
   .. testoutput::
   
       [-1. -1.  1.  2.  3. -1.]