Remove shape=None default in dpnp.reshape

CHANGELOG.md

@@ -36,6 +36,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
 * Refactored `dpnp.fft` and `dpnp.random` submodules by removing wildcard imports and defining explicit public exports [#2649](https://github.com/IntelPython/dpnp/pull/2649)
 * Added support for the `out` keyword to accept a tuple, bringing ufunc signatures into alignment with those in NumPy [#2664](https://github.com/IntelPython/dpnp/pull/2664)
 * Unified public API definitions in `dpnp.linalg` and `dpnp.scipy` submodules [#2663](https://github.com/IntelPython/dpnp/pull/2663)
+* Aligned the signature of `dpnp.reshape` function with Python array API by making `shape` a required argument [#2673](https://github.com/IntelPython/dpnp/pull/2673)
 
 ### Deprecated
 
@@ -46,6 +47,7 @@ Also, that release drops support for Python 3.9, making Python 3.10 the minimum
 
 * Dropped support for Python 3.9 [#2626](https://github.com/IntelPython/dpnp/pull/2626)
 * Removed the obsolete interface from DPNP to Numba JIT [#2647](https://github.com/IntelPython/dpnp/pull/2647)
+* Removed the `newshape` parameter from `dpnp.reshape`, which has been deprecated since dpnp 0.17.0. Pass it positionally or use `shape=` on newer versions [#2670](https://github.com/IntelPython/dpnp/pull/2670)
 
 ### Fixed
 

dpnp/dpnp_iface_manipulation.py

@@ -3013,7 +3013,7 @@ def require(a, dtype=None, requirements=None, *, like=None):
     return arr
 
 
-def reshape(a, /, shape=None, order="C", *, newshape=None, copy=None):
+def reshape(a, /, shape, order="C", *, copy=None):
     """
     Gives a new shape to an array without changing its data.
 
@@ -3028,8 +3028,6 @@ def reshape(a, /, shape=None, order="C", *, newshape=None, copy=None):
         an integer, then the result will be a 1-D array of that length.
         One shape dimension can be -1. In this case, the value is
         inferred from the length of the array and remaining dimensions.
-
-        Default: ``None``.
     order : {None, "C", "F", "A"}, optional
         Read the elements of `a` using this index order, and place the
         elements into the reshaped array using this index order. ``"C"``
@@ -3045,10 +3043,6 @@ def reshape(a, /, shape=None, order="C", *, newshape=None, copy=None):
         Fortran *contiguous* in memory, C-like order otherwise.
 
         Default: ``"C"``.
-    newshape : int or tuple of ints
-        Replaced by `shape` argument. Retained for backward compatibility.
-
-        Default: ``None``.
     copy : {None, bool}, optional
         If ``True``, then the array data is copied. If ``None``, a copy will
         only be made if it's required by ``order``. For ``False`` it raises
@@ -3117,27 +3111,6 @@ def reshape(a, /, shape=None, order="C", *, newshape=None, copy=None):
 
     """
 
-    if newshape is None and shape is None:
-        raise TypeError(
-            "reshape() missing 1 required positional argument: 'shape'"
-        )
-
-    if newshape is not None:
-        if shape is not None:
-            raise TypeError(
-                "You cannot specify 'newshape' and 'shape' arguments "
-                "at the same time."
-            )
-        # Deprecated in dpnp 0.17.0
-        warnings.warn(
-            "`newshape` keyword argument is deprecated, "
-            "use `shape=...` or pass shape positionally instead. "
-            "(deprecated in dpnp 0.17.0)",
-            DeprecationWarning,
-            stacklevel=2,
-        )
-        shape = newshape
-
     if order is None:
         order = "C"
     elif order in "aA":

dpnp/tests/test_manipulation.py

@@ -1124,21 +1124,6 @@ def test_copy(self):
 
 
 class TestReshape:
-    def test_error(self):
-        ia = dpnp.arange(10)
-        assert_raises(TypeError, dpnp.reshape, ia)
-        assert_raises(
-            TypeError, dpnp.reshape, ia, shape=(2, 5), newshape=(2, 5)
-        )
-
-    @pytest.mark.filterwarnings("ignore::DeprecationWarning")
-    def test_newshape(self):
-        a = numpy.arange(10)
-        ia = dpnp.array(a)
-        expected = numpy.reshape(a, (2, 5))
-        result = dpnp.reshape(ia, newshape=(2, 5))
-        assert_array_equal(result, expected)
-
     @pytest.mark.parametrize("order", [None, "C", "F", "A"])
     def test_order(self, order):
         a = numpy.arange(10)