From 7653448826a2f7fcad98d2521ace17fd473f31bf Mon Sep 17 00:00:00 2001
From: Natalia Polina <natalia.polina@intel.com>
Date: Mon, 28 Aug 2023 14:19:06 -0500
Subject: [PATCH 1/7] Implemented dpnp.hstack() and dpnp.atleast_1d()
 functions.

---
 dpnp/dpnp_iface_manipulation.py | 98 +++++++++++++++++++++++++++++++--
 tests/test_arraymanipulation.py | 13 +++--
 2 files changed, 100 insertions(+), 11 deletions(-)

diff --git a/dpnp/dpnp_iface_manipulation.py b/dpnp/dpnp_iface_manipulation.py
index a7ce7fb560e5..909c89b5d59d 100644
--- a/dpnp/dpnp_iface_manipulation.py
+++ b/dpnp/dpnp_iface_manipulation.py
@@ -112,13 +112,51 @@ def atleast_1d(*arys):
 
     For full documentation refer to :obj:`numpy.atleast_1d`.
 
-    Limitations
-    -----------
-    Input arrays is supported as :obj:`dpnp.ndarray`.
+    Parameters
+    ----------
+    arys1, arys2, ... : array_like
+        One or more input arrays.
+
+    Returns
+    -------
+    out : ndarray
+        An array, or list of arrays, each with ``a.ndim >= 1``.
+        Copies are made only if necessary.
+
+    See Also
+    --------
+    atleast_2d, atleast_3d
+
+    Examples
+    --------
+    >>> np.atleast_1d(1.0)
+    array([1.])
+
+    >>> x = np.arange(9.0).reshape(3,3)
+    >>> np.atleast_1d(x)
+    array([[0., 1., 2.],
+           [3., 4., 5.],
+           [6., 7., 8.]])
+    >>> np.atleast_1d(x) is x
+    True
+
+    >>> np.atleast_1d(1, [3, 4])
+    [array([1]), array([3, 4])]
 
     """
 
-    return call_origin(numpy.atleast_1d, *arys)
+    res = []
+    for ary in arys:
+        ary = dpnp.array(ary, copy=False)
+        if ary.ndim == 0:
+            result = ary.reshape(1)
+        else:
+            result = ary
+        res.append(result)
+    if len(res) == 1:
+        return res[0]
+    else:
+        return res
 
 
 def atleast_2d(*arys):
@@ -476,14 +514,62 @@ def expand_dims(a, axis):
     )
 
 
-def hstack(tup):
+def hstack(tup, *, dtype=None, casting="same_kind"):
     """
     Stack arrays in sequence horizontally (column wise).
 
     For full documentation refer to :obj:`numpy.hstack`.
 
+    Returns
+    -------
+    out : dpnp.ndarray
+        The stacked array which has one more dimension than the input arrays.
+
+    Limitations
+    -----------
+    Each array in `tup` is supported as either :class:`dpnp.ndarray`
+    or :class:`dpctl.tensor.usm_ndarray`. Otherwise ``TypeError`` exception
+    will be raised.
+    Parameters `dtype` and `casting` are supported with default value.
+    Otherwise the function will be executed sequentially on CPU.
+
+    See Also
+    --------
+    :obj:`dpnp.concatenate` : Join a sequence of arrays along an existing axis.
+    :obj:`dpnp.stack` : Join a sequence of arrays along a new axis.
+    :obj:`dpnp.block` : Assemble an nd-array from nested lists of blocks.
+    :obj:`dpnp.split` : Split array into a list of multiple sub-arrays of equal size.
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> a = np.array((1,2,3))
+    >>> b = np.array((4,5,6))
+    >>> np.hstack((a,b))
+    array([1, 2, 3, 4, 5, 6])
+    >>> a = np.array([[1],[2],[3]])
+    >>> b = np.array([[4],[5],[6]])
+    >>> np.hstack((a,b))
+    array([[1, 4],
+           [2, 5],
+           [3, 6]])
+
     """
 
+    if casting != "same_kind":
+        pass
+    elif dtype is not None:
+        pass
+    else:
+        arrs = dpnp.atleast_1d(*tup)
+        if not isinstance(arrs, list):
+            arrs = [arrs]
+        # As a special case, dimension 0 of 1-dimensional arrays is "horizontal"
+        if arrs and arrs[0].ndim == 1:
+            return dpnp.concatenate(arrs, axis=0)
+        else:
+            return dpnp.concatenate(arrs, axis=1)
+
     # TODO:
     # `call_origin` cannot convert sequence of array to sequence of
     # nparrays
@@ -884,7 +970,7 @@ def stack(arrays, /, *, axis=0, out=None, dtype=None, **kwargs):
     Each array in `arrays` is supported as either :class:`dpnp.ndarray`
     or :class:`dpctl.tensor.usm_ndarray`. Otherwise ``TypeError`` exception
     will be raised.
-    Parameters `out` and `dtype are supported with default value.
+    Parameters `out` and `dtype` are supported with default value.
     Keyword argument ``kwargs`` is currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
 
diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 94f54accbc78..2f87335b69ae 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -335,11 +335,9 @@ class TestHstack:
     def test_non_iterable(self):
         assert_raises(TypeError, dpnp.hstack, 1)
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_empty_input(self):
-        assert_raises(ValueError, dpnp.hstack, ())
+        assert_raises(TypeError, dpnp.hstack, ())
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_0D_array(self):
         b = dpnp.array(2)
         a = dpnp.array(1)
@@ -347,7 +345,6 @@ def test_0D_array(self):
         desired = dpnp.array([1, 2])
         assert_array_equal(res, desired)
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_1D_array(self):
         a = dpnp.array([1])
         b = dpnp.array([2])
@@ -355,7 +352,6 @@ def test_1D_array(self):
         desired = dpnp.array([1, 2])
         assert_array_equal(res, desired)
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     def test_2D_array(self):
         a = dpnp.array([[1], [2]])
         b = dpnp.array([[1], [2]])
@@ -605,3 +601,10 @@ def test_2D_array2(self):
     def test_generator(self):
         with assert_warns(FutureWarning):
             dpnp.vstack((numpy.arange(3) for _ in range(2)))
+
+
+@pytest.mark.parametrize("arys", [1.0, dpnp.arange(9.0).reshape(3, 3), [3, 4]])
+def test_atleast_1d(arys):
+    expected = numpy.atleast_1d(arys)
+    result = dpnp.atleast_1d(arys)
+    assert_array_equal(result, expected)

From 7423569ed9f2fc32fea684861744e8e90fb35303 Mon Sep 17 00:00:00 2001
From: Natalia Polina <natalia.polina@intel.com>
Date: Wed, 30 Aug 2023 10:08:27 -0500
Subject: [PATCH 2/7] Added tests for hstack and atleast_1d functions

---
 dpnp/dpnp_iface_manipulation.py               | 44 ++++++++-----------
 tests/test_arraymanipulation.py               | 41 ++++++++++++++---
 .../cupy/manipulation_tests/test_dims.py      |  2 -
 .../cupy/manipulation_tests/test_join.py      |  7 +--
 4 files changed, 56 insertions(+), 38 deletions(-)

diff --git a/dpnp/dpnp_iface_manipulation.py b/dpnp/dpnp_iface_manipulation.py
index 909c89b5d59d..590511517c1f 100644
--- a/dpnp/dpnp_iface_manipulation.py
+++ b/dpnp/dpnp_iface_manipulation.py
@@ -114,12 +114,12 @@ def atleast_1d(*arys):
 
     Parameters
     ----------
-    arys1, arys2, ... : array_like
+    arys : {dpnp_array, usm_ndarray}
         One or more input arrays.
 
     Returns
     -------
-    out : ndarray
+    out : dpnp.ndarray
         An array, or list of arrays, each with ``a.ndim >= 1``.
         Copies are made only if necessary.
 
@@ -129,6 +129,7 @@ def atleast_1d(*arys):
 
     Examples
     --------
+    >>> import dpnp as np
     >>> np.atleast_1d(1.0)
     array([1.])
 
@@ -147,7 +148,7 @@ def atleast_1d(*arys):
 
     res = []
     for ary in arys:
-        ary = dpnp.array(ary, copy=False)
+        ary = dpnp.asanyarray(ary)
         if ary.ndim == 0:
             result = ary.reshape(1)
         else:
@@ -275,7 +276,9 @@ def broadcast_to(array, /, shape, subok=False):
     return call_origin(numpy.broadcast_to, array, shape=shape, subok=subok)
 
 
-def concatenate(arrays, /, *, axis=0, out=None, dtype=None, **kwargs):
+def concatenate(
+    arrays, /, *, axis=0, out=None, dtype=None, casting="same_kind", **kwargs
+):
     """
     Join a sequence of arrays along an existing axis.
 
@@ -332,6 +335,8 @@ def concatenate(arrays, /, *, axis=0, out=None, dtype=None, **kwargs):
         pass
     elif dtype is not None:
         pass
+    elif casting != "same_kind":
+        pass
     else:
         usm_arrays = [dpnp.get_usm_ndarray(x) for x in arrays]
         usm_res = dpt.concat(usm_arrays, axis=axis)
@@ -537,6 +542,7 @@ def hstack(tup, *, dtype=None, casting="same_kind"):
     --------
     :obj:`dpnp.concatenate` : Join a sequence of arrays along an existing axis.
     :obj:`dpnp.stack` : Join a sequence of arrays along a new axis.
+    :obj:`dpnp.vstack` : Stack arrays in sequence vertically (row wise).
     :obj:`dpnp.block` : Assemble an nd-array from nested lists of blocks.
     :obj:`dpnp.split` : Split array into a list of multiple sub-arrays of equal size.
 
@@ -547,6 +553,7 @@ def hstack(tup, *, dtype=None, casting="same_kind"):
     >>> b = np.array((4,5,6))
     >>> np.hstack((a,b))
     array([1, 2, 3, 4, 5, 6])
+
     >>> a = np.array([[1],[2],[3]])
     >>> b = np.array([[4],[5],[6]])
     >>> np.hstack((a,b))
@@ -556,29 +563,14 @@ def hstack(tup, *, dtype=None, casting="same_kind"):
 
     """
 
-    if casting != "same_kind":
-        pass
-    elif dtype is not None:
-        pass
+    arrs = dpnp.atleast_1d(*tup)
+    if not isinstance(arrs, list):
+        arrs = [arrs]
+    # As a special case, dimension 0 of 1-dimensional arrays is "horizontal"
+    if arrs and arrs[0].ndim == 1:
+        return dpnp.concatenate(arrs, axis=0, dtype=dtype, casting=casting)
     else:
-        arrs = dpnp.atleast_1d(*tup)
-        if not isinstance(arrs, list):
-            arrs = [arrs]
-        # As a special case, dimension 0 of 1-dimensional arrays is "horizontal"
-        if arrs and arrs[0].ndim == 1:
-            return dpnp.concatenate(arrs, axis=0)
-        else:
-            return dpnp.concatenate(arrs, axis=1)
-
-    # TODO:
-    # `call_origin` cannot convert sequence of array to sequence of
-    # nparrays
-    tup_new = []
-    for tp in tup:
-        tpx = dpnp.asnumpy(tp) if not isinstance(tp, numpy.ndarray) else tp
-        tup_new.append(tpx)
-
-    return call_origin(numpy.hstack, tup_new)
+        return dpnp.concatenate(arrs, axis=1, dtype=dtype, casting=casting)
 
 
 def moveaxis(a, source, destination):
diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 2f87335b69ae..44cd5a6f0d40 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -603,8 +603,39 @@ def test_generator(self):
             dpnp.vstack((numpy.arange(3) for _ in range(2)))
 
 
-@pytest.mark.parametrize("arys", [1.0, dpnp.arange(9.0).reshape(3, 3), [3, 4]])
-def test_atleast_1d(arys):
-    expected = numpy.atleast_1d(arys)
-    result = dpnp.atleast_1d(arys)
-    assert_array_equal(result, expected)
+class TestAtleast1d:
+    def test_0D_array(self):
+        a = dpnp.array(1)
+        b = dpnp.array(2)
+        res = [dpnp.atleast_1d(a), dpnp.atleast_1d(b)]
+        desired = [dpnp.array([1]), dpnp.array([2])]
+        assert_array_equal(res, desired)
+
+    def test_1D_array(self):
+        a = dpnp.array([1, 2])
+        b = dpnp.array([2, 3])
+        res = [dpnp.atleast_1d(a), dpnp.atleast_1d(b)]
+        desired = [dpnp.array([1, 2]), dpnp.array([2, 3])]
+        assert_array_equal(res, desired)
+
+    def test_2D_array(self):
+        a = dpnp.array([[1, 2], [1, 2]])
+        b = dpnp.array([[2, 3], [2, 3]])
+        res = [dpnp.atleast_1d(a), dpnp.atleast_1d(b)]
+        desired = [a, b]
+        assert_array_equal(res, desired)
+
+    def test_3D_array(self):
+        a = dpnp.array([[1, 2], [1, 2]])
+        b = dpnp.array([[2, 3], [2, 3]])
+        a = dpnp.array([a, a])
+        b = dpnp.array([b, b])
+        res = [dpnp.atleast_1d(a), dpnp.atleast_1d(b)]
+        desired = [a, b]
+        assert_array_equal(res, desired)
+
+    def test_r1array(self):
+        assert dpnp.atleast_1d(3).shape == (1,)
+        assert dpnp.atleast_1d(3j).shape == (1,)
+        assert dpnp.atleast_1d(3.0).shape == (1,)
+        assert dpnp.atleast_1d([[2, 3], [4, 5]]).shape == (2, 2)
diff --git a/tests/third_party/cupy/manipulation_tests/test_dims.py b/tests/third_party/cupy/manipulation_tests/test_dims.py
index 6d59f0640512..461c0bb2ec2b 100644
--- a/tests/third_party/cupy/manipulation_tests/test_dims.py
+++ b/tests/third_party/cupy/manipulation_tests/test_dims.py
@@ -18,12 +18,10 @@ def check_atleast(self, func, xp):
         f = numpy.float32(1)
         return func(a, b, c, d, e, f)
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     @testing.numpy_cupy_array_equal()
     def test_atleast_1d1(self, xp):
         return self.check_atleast(xp.atleast_1d, xp)
 
-    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     @testing.numpy_cupy_array_equal()
     def test_atleast_1d2(self, xp):
         a = testing.shaped_arange((1, 3, 2), xp)
diff --git a/tests/third_party/cupy/manipulation_tests/test_join.py b/tests/third_party/cupy/manipulation_tests/test_join.py
index 054ada455aee..039471faab36 100644
--- a/tests/third_party/cupy/manipulation_tests/test_join.py
+++ b/tests/third_party/cupy/manipulation_tests/test_join.py
@@ -270,14 +270,12 @@ def test_dstack_single_element_3(self, xp):
         a = testing.shaped_arange((1,), xp)
         return xp.dstack((a,))
 
-    @pytest.mark.skip("dpnp.hstack() is not implemented yet")
     @testing.numpy_cupy_array_equal()
     def test_hstack_vectors(self, xp):
         a = xp.arange(3)
         b = xp.arange(2, -1, -1)
         return xp.hstack((a, b))
 
-    @pytest.mark.skip("dpnp.hstack() is not implemented yet")
     @testing.numpy_cupy_array_equal()
     def test_hstack_scalars(self, xp):
         a = testing.shaped_arange((), xp)
@@ -285,7 +283,6 @@ def test_hstack_scalars(self, xp):
         c = testing.shaped_arange((), xp)
         return xp.hstack((a, b, c))
 
-    @pytest.mark.skip("dpnp.hstack() is not implemented yet")
     @testing.numpy_cupy_array_equal()
     def test_hstack(self, xp):
         a = testing.shaped_arange((2, 1), xp)
@@ -293,7 +290,7 @@ def test_hstack(self, xp):
         c = testing.shaped_arange((2, 3), xp)
         return xp.hstack((a, b, c))
 
-    @pytest.mark.skip("dpnp.hstack() is not implemented yet")
+    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     @testing.with_requires("numpy>=1.24.0")
     @testing.for_all_dtypes_combination(names=["dtype1", "dtype2"])
     @testing.numpy_cupy_array_equal(accept_error=TypeError)
@@ -302,7 +299,7 @@ def test_hstack_dtype(self, xp, dtype1, dtype2):
         b = testing.shaped_arange((3, 4), xp, dtype1)
         return xp.hstack((a, b), dtype=dtype2)
 
-    @pytest.mark.skip("dpnp.hstack() is not implemented yet")
+    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     @testing.with_requires("numpy>=1.24.0")
     @pytest.mark.parametrize(
         "casting",

From de5d85748cf03a93344c83999f56b9fe6c407cce Mon Sep 17 00:00:00 2001
From: Natalia Polina <natalia.polina@intel.com>
Date: Thu, 31 Aug 2023 05:34:22 -0500
Subject: [PATCH 3/7] Fixed test for hstack.

---
 dpnp/dpnp_iface_manipulation.py                       |  5 +++++
 tests/skipped_tests.tbl                               |  1 -
 tests/skipped_tests_gpu.tbl                           |  1 -
 tests/test_arraymanipulation.py                       |  4 ++--
 .../third_party/cupy/manipulation_tests/test_join.py  | 11 +----------
 5 files changed, 8 insertions(+), 14 deletions(-)

diff --git a/dpnp/dpnp_iface_manipulation.py b/dpnp/dpnp_iface_manipulation.py
index 40d35365e6b7..246a601ad1c7 100644
--- a/dpnp/dpnp_iface_manipulation.py
+++ b/dpnp/dpnp_iface_manipulation.py
@@ -353,6 +353,7 @@ def concatenate(
         axis=axis,
         out=out,
         dtype=dtype,
+        casting=casting,
         **kwargs,
     )
 
@@ -746,6 +747,10 @@ def hstack(tup, *, dtype=None, casting="same_kind"):
 
     """
 
+    if not hasattr(tup, "__getitem__"):
+        raise TypeError(
+            "Arrays to stack must be passed as a sequence type such as list or tuple."
+        )
     arrs = dpnp.atleast_1d(*tup)
     if not isinstance(arrs, list):
         arrs = [arrs]
diff --git a/tests/skipped_tests.tbl b/tests/skipped_tests.tbl
index 9c5b855f3631..10f167653eab 100644
--- a/tests/skipped_tests.tbl
+++ b/tests/skipped_tests.tbl
@@ -34,7 +34,6 @@ tests/third_party/cupy/fft_tests/test_fft.py::TestFftn_param_23_{axes=None, norm
 
 tests/third_party/intel/test_zero_copy_test1.py::test_dpnp_interaction_with_dpctl_memory
 
-tests/test_arraymanipulation.py::TestHstack::test_generator
 tests/test_arraymanipulation.py::TestVstack::test_generator
 
 tests/test_linalg.py::test_cond[-1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
diff --git a/tests/skipped_tests_gpu.tbl b/tests/skipped_tests_gpu.tbl
index f82c6107a4c6..081f0b72350b 100644
--- a/tests/skipped_tests_gpu.tbl
+++ b/tests/skipped_tests_gpu.tbl
@@ -216,7 +216,6 @@ tests/third_party/cupy/random_tests/test_distributions.py::TestDistributionsMult
 tests/third_party/cupy/random_tests/test_distributions.py::TestDistributionsMultivariateNormal_param_3_{d=4, shape=(3, 2)}::test_normal
 
 tests/third_party/intel/test_zero_copy_test1.py::test_dpnp_interaction_with_dpctl_memory
-tests/test_arraymanipulation.py::TestHstack::test_generator
 tests/test_arraymanipulation.py::TestVstack::test_generator
 
 tests/test_linalg.py::test_cond[-1-[[1, 2, 3], [4, 5, 6], [7, 8, 9]]]
diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 7603879457d3..32b5e84ac38e 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -360,9 +360,9 @@ def test_2D_array(self):
         assert_array_equal(res, desired)
 
     def test_generator(self):
-        with assert_warns(FutureWarning):
+        with pytest.raises(TypeError):
             dpnp.hstack((numpy.arange(3) for _ in range(2)))
-        with assert_warns(FutureWarning):
+        with pytest.raises(TypeError):
             dpnp.hstack(map(lambda x: x, numpy.ones((3, 2))))
 
 
diff --git a/tests/third_party/cupy/manipulation_tests/test_join.py b/tests/third_party/cupy/manipulation_tests/test_join.py
index 039471faab36..8bffce98d875 100644
--- a/tests/third_party/cupy/manipulation_tests/test_join.py
+++ b/tests/third_party/cupy/manipulation_tests/test_join.py
@@ -301,16 +301,7 @@ def test_hstack_dtype(self, xp, dtype1, dtype2):
 
     @pytest.mark.usefixtures("allow_fall_back_on_numpy")
     @testing.with_requires("numpy>=1.24.0")
-    @pytest.mark.parametrize(
-        "casting",
-        [
-            "no",
-            "equiv",
-            "safe",
-            "same_kind",
-            "unsafe",
-        ],
-    )
+    @testing.for_castings()
     @testing.for_all_dtypes_combination(names=["dtype1", "dtype2"])
     @testing.numpy_cupy_array_equal(
         accept_error=(TypeError, numpy.ComplexWarning)

From a63746b3ab769eed557967664b991a5ecc450167 Mon Sep 17 00:00:00 2001
From: Anton <100830759+antonwolfy@users.noreply.github.com>
Date: Thu, 31 Aug 2023 13:02:08 +0200
Subject: [PATCH 4/7] Update tests/test_arraymanipulation.py

---
 tests/test_arraymanipulation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 32b5e84ac38e..7c77e3885346 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -361,7 +361,7 @@ def test_2D_array(self):
 
     def test_generator(self):
         with pytest.raises(TypeError):
-            dpnp.hstack((numpy.arange(3) for _ in range(2)))
+            dpnp.hstack((dpnp.arange(3) for _ in range(2)))
         with pytest.raises(TypeError):
             dpnp.hstack(map(lambda x: x, numpy.ones((3, 2))))
 

From a1f7fcf16d9fb04b3d8183ed3fcbf8f096f7d314 Mon Sep 17 00:00:00 2001
From: Anton <100830759+antonwolfy@users.noreply.github.com>
Date: Thu, 31 Aug 2023 13:02:17 +0200
Subject: [PATCH 5/7] Update tests/test_arraymanipulation.py

---
 tests/test_arraymanipulation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 7c77e3885346..048bbe1c709d 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -363,7 +363,7 @@ def test_generator(self):
         with pytest.raises(TypeError):
             dpnp.hstack((dpnp.arange(3) for _ in range(2)))
         with pytest.raises(TypeError):
-            dpnp.hstack(map(lambda x: x, numpy.ones((3, 2))))
+            dpnp.hstack(map(lambda x: x, dpnp.ones((3, 2))))
 
 
 class TestStack:

From 9066770008f86cf2186209ae291a1be5ae11d225 Mon Sep 17 00:00:00 2001
From: Natalia Polina <natalia.polina@intel.com>
Date: Thu, 31 Aug 2023 11:15:09 -0500
Subject: [PATCH 6/7] Fixed test coverage for concatenate and hstack functions.

---
 dpnp/dpnp_iface_manipulation.py |  7 ++-----
 tests/test_arraymanipulation.py | 22 ++++++++++++++++++++++
 2 files changed, 24 insertions(+), 5 deletions(-)

diff --git a/dpnp/dpnp_iface_manipulation.py b/dpnp/dpnp_iface_manipulation.py
index 246a601ad1c7..59bae9b30fec 100644
--- a/dpnp/dpnp_iface_manipulation.py
+++ b/dpnp/dpnp_iface_manipulation.py
@@ -282,7 +282,7 @@ def broadcast_to(array, /, shape, subok=False):
 
 
 def concatenate(
-    arrays, /, *, axis=0, out=None, dtype=None, casting="same_kind", **kwargs
+    arrays, /, *, axis=0, out=None, dtype=None, casting="same_kind"
 ):
     """
     Join a sequence of arrays along an existing axis.
@@ -334,9 +334,7 @@ def concatenate(
 
     """
 
-    if kwargs:
-        pass
-    elif out is not None:
+    if out is not None:
         pass
     elif dtype is not None:
         pass
@@ -354,7 +352,6 @@ def concatenate(
         out=out,
         dtype=dtype,
         casting=casting,
-        **kwargs,
     )
 
 
diff --git a/tests/test_arraymanipulation.py b/tests/test_arraymanipulation.py
index 048bbe1c709d..3dcfeac72a0f 100644
--- a/tests/test_arraymanipulation.py
+++ b/tests/test_arraymanipulation.py
@@ -330,6 +330,23 @@ def test_concatenate_out(self, dtype):
         assert_array_equal(dp_out.asnumpy(), np_out)
         assert_array_equal(dp_res.asnumpy(), np_res)
 
+    @pytest.mark.usefixtures("allow_fall_back_on_numpy")
+    @pytest.mark.parametrize(
+        "dtype", get_all_dtypes(no_bool=True, no_none=True)
+    )
+    @pytest.mark.parametrize(
+        "casting", ["no", "equiv", "safe", "same_kind", "unsafe"]
+    )
+    def test_concatenate_casting(self, dtype, casting):
+        np_a = numpy.arange(2 * 3 * 7, dtype=dtype).reshape((2, 3, 7))
+
+        dp_a = dpnp.arange(2 * 3 * 7, dtype=dtype).reshape((2, 3, 7))
+
+        np_res = numpy.concatenate((np_a, np_a), axis=2, casting=casting)
+        dp_res = dpnp.concatenate((dp_a, dp_a), axis=2, casting=casting)
+
+        assert_array_equal(dp_res.asnumpy(), np_res)
+
 
 class TestHstack:
     def test_non_iterable(self):
@@ -365,6 +382,11 @@ def test_generator(self):
         with pytest.raises(TypeError):
             dpnp.hstack(map(lambda x: x, dpnp.ones((3, 2))))
 
+    def test_one_element(self):
+        a = dpnp.array([1])
+        res = dpnp.hstack(a)
+        assert_array_equal(res, a)
+
 
 class TestStack:
     def test_non_iterable_input(self):

From 2429a6f2210fec0ec055bd30f54025865aa86a34 Mon Sep 17 00:00:00 2001
From: Natalia Polina <natalia.polina@intel.com>
Date: Wed, 6 Sep 2023 00:30:17 -0700
Subject: [PATCH 7/7] Fixed limitation description for concatenate function

---
 dpnp/dpnp_iface_manipulation.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/dpnp/dpnp_iface_manipulation.py b/dpnp/dpnp_iface_manipulation.py
index 59bae9b30fec..207d51636eb5 100644
--- a/dpnp/dpnp_iface_manipulation.py
+++ b/dpnp/dpnp_iface_manipulation.py
@@ -300,7 +300,6 @@ def concatenate(
     or :class:`dpctl.tensor.usm_ndarray`. Otherwise ``TypeError`` exception
     will be raised.
     Parameters `out` and `dtype are supported with default value.
-    Keyword argument ``kwargs`` is currently unsupported.
     Otherwise the function will be executed sequentially on CPU.
 
     See Also