implement dpnp.einsum

.github/workflows/conda-package.yml

@@ -40,6 +40,7 @@ env:
       third_party/cupy/linalg_tests/test_norms.py
       third_party/cupy/linalg_tests/test_product.py
       third_party/cupy/linalg_tests/test_solve.py
+      third_party/cupy/linalg_tests/test_einsum.py
       third_party/cupy/logic_tests/test_comparison.py
       third_party/cupy/logic_tests/test_truth.py
       third_party/cupy/manipulation_tests/test_basic.py

doc/known_words.txt

@@ -5,7 +5,9 @@ broadcastable
 broadcasted
 byteorder
 Cholesky
+combinatorially
 conda
+cubically
 Decompositions
 dimensionality
 docstring
@@ -22,6 +24,7 @@ finfo
 finiteness
 Fortran
 Frobenius
+Hadamard
 Hypergeometric
 iinfo
 Infs

dpnp/dpnp_array.py

@@ -580,14 +580,14 @@ def astype(self, dtype, order="K", casting="unsafe", subok=True, copy=True):
             If it is False and no cast happens, then this method returns the array itself.
             Otherwise, a copy is returned.
         casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
-            Controls what kind of data casting may occur. Defaults to 'unsafe' for backwards compatibility.
-
+            Controls what kind of data casting may occur.
+            Defaults to ``'unsafe'`` for backwards compatibility.
             - 'no' means the data types should not be cast at all.
             - 'equiv' means only byte-order changes are allowed.
             - 'safe' means only casts which can preserve values are allowed.
-            - 'same_kind' means only safe casts or casts within a kind, like float64 to float32, are allowed.
+            - 'same_kind' means only safe casts or casts within a kind, like
+              float64 to float32, are allowed.
             - 'unsafe' means any data conversions may be done.
-
         copy : bool, optional
             By default, ``astype`` always returns a newly allocated array. If
             this is set to ``False``, and the `dtype`, `order`, and `subok`

dpnp/dpnp_iface.py

@@ -331,7 +331,7 @@ def check_supported_arrays_type(*arrays, scalar_type=False, all_scalars=False):
             f"An array must be any of supported type, but got {type(a)}"
         )
 
-    if len(arrays) > 1 and not (all_scalars or any_is_array):
+    if len(arrays) > 0 and not (all_scalars or any_is_array):
         raise TypeError(
             "At least one input must be of supported array type, "
             "but got all scalars."