Use normalize_axis_tuple from numpy instead of _check_value_of_axes (#789)

Author: vlad-perevezentsev

dpctl/tensor/_manipulation_functions.py

@@ -15,23 +15,11 @@
 #  limitations under the License.
 
 
-import numpy as np
 from numpy.core.numeric import normalize_axis_tuple
 
 import dpctl.tensor as dpt
 
 
-def _check_value_of_axes(axes):
-    axes_len = len(axes)
-    check_array = np.zeros(axes_len)
-    for i in axes:
-        ii = i.__index__()
-        if ii < 0 or ii > axes_len or check_array[ii] != 0:
-            return False
-        check_array[ii] = 1
-    return True
-
-
 def permute_dims(X, axes):
     """
     permute_dims(X: usm_ndarray, axes: tuple or list) -> usm_ndarray
@@ -48,11 +36,7 @@ def permute_dims(X, axes):
             "The length of the passed axes does not match "
             "to the number of usm_ndarray dimensions."
         )
-    if not _check_value_of_axes(axes):
-        raise ValueError(
-            "The values of the axes must be in the range "
-            f"from 0 to {X.ndim} and have no duplicates."
-        )
+    axes = normalize_axis_tuple(axes, X.ndim, "axes")
     newstrides = tuple(X.strides[i] for i in axes)
     newshape = tuple(X.shape[i] for i in axes)
     return dpt.usm_ndarray(

dpctl/tests/test_usm_ndarray_manipulation.py

@@ -63,7 +63,7 @@ def test_permute_dims_0d_1d():
     assert_array_equal(dpt.asnumpy(Y_1d), dpt.asnumpy(X_1d))
 
     pytest.raises(ValueError, dpt.permute_dims, X_1d, ())
-    pytest.raises(IndexError, dpt.permute_dims, X_1d, (1))
+    pytest.raises(np.AxisError, dpt.permute_dims, X_1d, (1))
     pytest.raises(ValueError, dpt.permute_dims, X_1d, (1, 0))
     pytest.raises(
         ValueError, dpt.permute_dims, dpt.reshape(X_1d, (2, 3)), (1, 1)