allow using scalar when possible

Author: vtavana

dpnp/dpnp_iface_mathematical.py

@@ -145,7 +145,7 @@ def _append_to_diff_array(a, axis, combined, values):
 
     """
 
-    dpnp.check_supported_arrays_type(values, scalar_type=True)
+    dpnp.check_supported_arrays_type(values, scalar_type=True, all_scalars=True)
     if dpnp.isscalar(values):
         values = dpnp.asarray(
             values, sycl_queue=a.sycl_queue, usm_type=a.usm_type

dpnp/linalg/dpnp_iface_linalg.py

@@ -705,7 +705,9 @@ def matrix_rank(A, tol=None, hermitian=False):
 
     dpnp.check_supported_arrays_type(A)
     if tol is not None:
-        dpnp.check_supported_arrays_type(tol, scalar_type=True)
+        dpnp.check_supported_arrays_type(
+            tol, scalar_type=True, all_scalars=True
+        )
 
     return dpnp_matrix_rank(A, tol=tol, hermitian=hermitian)
 
@@ -819,7 +821,7 @@ def pinv(a, rcond=1e-15, hermitian=False):
     """
 
     dpnp.check_supported_arrays_type(a)
-    dpnp.check_supported_arrays_type(rcond, scalar_type=True)
+    dpnp.check_supported_arrays_type(rcond, scalar_type=True, all_scalars=True)
     check_stacked_2d(a)
 
     return dpnp_pinv(a, rcond=rcond, hermitian=hermitian)

tests/test_mathematical.py

@@ -2554,14 +2554,15 @@ def setup_method(self):
     def test_matmul(self, order_pair, shape_pair):
         order1, order2 = order_pair
         shape1, shape2 = shape_pair
-        a1 = numpy.arange(numpy.prod(shape1)).reshape(shape1)
-        a2 = numpy.arange(numpy.prod(shape2)).reshape(shape2)
+        dtype = dpnp.default_float_type()
+        a1 = numpy.arange(numpy.prod(shape1), dtype=dtype).reshape(shape1)
+        a2 = numpy.arange(numpy.prod(shape2), dtype=dtype).reshape(shape2)
         a1 = numpy.array(a1, order=order1)
         a2 = numpy.array(a2, order=order2)
 
         b1 = dpnp.asarray(a1)
         b2 = dpnp.asarray(a2)
-
+        print(a1.dtype)
         result = dpnp.matmul(b1, b2)
         expected = numpy.matmul(a1, a2)
         assert_dtype_allclose(result, expected)