Deprecate newshape argument of jnp.reshape

CHANGELOG.md

@@ -11,6 +11,8 @@ Remember to align the itemized text with the first line of an item within a list
 * Deprecations & removals
   * The ``kind`` argument to {func}`jax.numpy.sort` and {func}`jax.numpy.argsort`
     is now removed. Use `stable=True` or `stable=False` instead.
+  * The ``newshape`` argument to {func}`jax.numpy.reshape`is being deprecated
+    and will soon be removed. Use `shape` instead.
 
 ## jaxlib 0.4.28
 

jax/_src/numpy/lax_numpy.py

@@ -893,15 +893,17 @@ def isrealobj(x: Any) -> bool:
   return not iscomplexobj(x)
 
 
-def reshape(a: ArrayLike, newshape: DimSize | Shape, order: str = "C") -> Array:
+def reshape(
+    a: ArrayLike, shape: DimSize | Shape | None = None, order: str = "C", *,
+    newshape: DimSize | Shape | DeprecatedArg = DeprecatedArg()) -> Array:
   """Return a reshaped copy of an array.
 
   JAX implementation of :func:`numpy.reshape`, implemented in terms of
   :func:`jax.lax.reshape`.
 
   Args:
     a: input array to reshape
-    newshape: integer or sequence of integers giving the new shape, which must match the
+    shape: integer or sequence of integers giving the new shape, which must match the
       size of the input array. If any single dimension is given size ``-1``, it will be
       replaced with a value such that the output has the correct size.
     order: ``'F'`` or ``'C'``, specifies whether the reshape should apply column-major
@@ -961,12 +963,31 @@ def reshape(a: ArrayLike, newshape: DimSize | Shape, order: str = "C") -> Array:
   """
   __tracebackhide__ = True
   util.check_arraylike("reshape", a)
+
+  # TODO(micky774): deprecated 2024-5-9, remove after deprecation expires.
+  if not isinstance(newshape, DeprecatedArg):
+    if shape is not None:
+      raise ValueError(
+        "jnp.reshape received both `shape` and `newshape` arguments. Note that "
+        "using `newshape` is deprecated, please only use `shape` instead."
+      )
+    warnings.warn(
+      "The newshape argument of jax.numpy.reshape is deprecated and setting it "
+      "will soon raise an error. To avoid an error in the future, and to "
+      "suppress this warning, please use the shape argument instead.",
+      DeprecationWarning, stacklevel=2)
+    shape = newshape
+    del newshape
+  elif shape is None:
+    raise TypeError(
+      "jnp.shape requires passing a `shape` argument, but none was given."
+    )
   try:
     # forward to method for ndarrays
-    return a.reshape(newshape, order=order)  # type: ignore[call-overload,union-attr]
+    return a.reshape(shape, order=order)  # type: ignore[call-overload,union-attr]
   except AttributeError:
     pass
-  return asarray(a).reshape(newshape, order=order)
+  return asarray(a).reshape(shape, order=order)
 
 
 @partial(jit, static_argnames=('order',), inline=True)

jax/experimental/array_api/_manipulation_functions.py

@@ -18,7 +18,7 @@
 from jax import Array
 
 
-# TODO(micky774): Deprecate newshape-->shape in for array API 2023.12
+# TODO(micky774): Implement copy
 def reshape(x: Array, /, shape: tuple[int, ...], *, copy: bool | None = None) -> Array:
   """Reshapes an array without changing its data."""
   del copy  # unused

jax/numpy/__init__.pyi

@@ -690,7 +690,8 @@ def remainder(x: ArrayLike, y: ArrayLike, /) -> Array: ...
 def repeat(a: ArrayLike, repeats: ArrayLike, axis: Optional[int] = ..., *,
            total_repeat_length: Optional[int] = ...) -> Array: ...
 def reshape(
-    a: ArrayLike, newshape: Union[DimSize, Shape], order: str = ...
+    a: ArrayLike, shape: Union[DimSize, Shape] = ...,
+    newshape: Union[DimSize, Shape] | None = ..., order: str = ...
 ) -> Array: ...
 
 def resize(a: ArrayLike, new_shape: Shape) -> Array: ...

tests/random_test.py

@@ -1221,9 +1221,9 @@ def test_reshape(self):
     key = random.key(123)
     keys = random.split(key, 4)
 
-    newshape = (2, 2)
-    key_func = partial(jnp.reshape, newshape=newshape)
-    arr_func = partial(jnp.reshape, newshape=(*newshape, *key._impl.key_shape))
+    shape = (2, 2)
+    key_func = partial(jnp.reshape, shape=shape)
+    arr_func = partial(jnp.reshape, shape=(*shape, *key._impl.key_shape))
 
     self.check_shape(key_func, keys)
     self.check_against_reference(key_func, arr_func, keys)
@@ -1291,7 +1291,7 @@ def test_ravel(self):
     keys = random.split(key, 4).reshape(2, 2)
 
     key_func = jnp.ravel
-    arr_func = partial(jnp.reshape, newshape=(4, *key._impl.key_shape))
+    arr_func = partial(jnp.reshape, shape=(4, *key._impl.key_shape))
 
     self.check_shape(key_func, keys)
     self.check_against_reference(key_func, arr_func, keys)