tile_docstring_added

jax/_src/numpy/lax_numpy.py

@@ -4483,8 +4483,38 @@ def unstack(x: ArrayLike, /, *, axis: int = 0) -> tuple[Array, ...]:
     )
   return tuple(moveaxis(x, axis, 0))
 
-@util.implements(np.tile)
 def tile(A: ArrayLike, reps: DimSize | Sequence[DimSize]) -> Array:
+  """Construct an array by repeating ``A`` along specified dimensions.
+
+  JAX implementation of :func:`numpy.tile`.
+
+  If ``A`` is an array of shape ``(d1, d2, ..., dn)`` and ``reps`` is a sequence of integers,
+  the resulting array will have a shape of ``(reps[0] * d1, reps[1] * d2, ..., reps[n] * dn)``,
+  with ``A`` tiled along each dimension.
+
+  Args:
+    A: input array to be repeated. Can be of any shape or dimension.
+    reps: specifies the number of repetitions along each axis.
+
+  Returns:
+    a new array where the input array has been repeated according to ``reps``.
+
+  See also:
+    - :func:`jax.numpy.repeat`: Construct an array from repeated elements.
+    - :func:`jax.numpy.broadcast_to`: Broadcast an array to a specified shape.
+
+  Examples:
+    >>> arr = jnp.array([1, 2])
+    >>> jnp.tile(arr, 2)
+    Array([1, 2, 1, 2], dtype=int32)
+    >>> arr = jnp.array([[1, 2],
+    ...                  [3, 4,]])
+    >>> jnp.tile(arr, (2, 1))
+    Array([[1, 2],
+           [3, 4],
+           [1, 2],
+           [3, 4]], dtype=int32)
+  """
   util.check_arraylike("tile", A)
   try:
     iter(reps)  # type: ignore[arg-type]