Add inplace matrix multiplication

doc/reference/ndarray.rst

@@ -249,7 +249,7 @@ Comparison operators:
    dpnp.ndarray.__eq__
    dpnp.ndarray.__ne__
 
-Truth value of an array (:func:`bool()`):
+Truth value of an array (:class:`bool() <bool>`):
 
 .. autosummary::
    :toctree: generated/
@@ -260,11 +260,11 @@ Truth value of an array (:func:`bool()`):
 
    Truth-value testing of an array invokes
    :meth:`dpnp.ndarray.__bool__`, which raises an error if the number of
-   elements in the array is larger than 1, because the truth value
+   elements in the array is not 1, because the truth value
    of such arrays is ambiguous. Use :meth:`.any() <dpnp.ndarray.any>` and
    :meth:`.all() <dpnp.ndarray.all>` instead to be clear about what is meant
-   in such cases. (If the number of elements is 0, the array evaluates
-   to ``False``.)
+   in such cases. (If you wish to check for whether an array is empty,
+   use for example ``.size > 0``.)
 
 
 Unary operations:
@@ -300,6 +300,26 @@ Arithmetic:
    dpnp.ndarray.__xor__
 
 
+Arithmetic, reflected:
+
+.. autosummary::
+   :toctree: generated/
+   :nosignatures:
+
+   dpnp.ndarray.__radd__
+   dpnp.ndarray.__rsub__
+   dpnp.ndarray.__rmul__
+   dpnp.ndarray.__rtruediv__
+   dpnp.ndarray.__rfloordiv__
+   dpnp.ndarray.__rmod__
+   dpnp.ndarray.__rpow__
+   dpnp.ndarray.__rlshift__
+   dpnp.ndarray.__rrshift__
+   dpnp.ndarray.__rand__
+   dpnp.ndarray.__ror__
+   dpnp.ndarray.__rxor__
+
+
 Arithmetic, in-place:
 
 .. autosummary::
@@ -326,6 +346,8 @@ Matrix Multiplication:
    :toctree: generated/
 
    dpnp.ndarray.__matmul__
+   dpnp.ndarray.__rmatmul__
+   dpnp.ndarray.__imatmul__
 
 
 Special methods

dpnp/dpnp_array.py

@@ -25,6 +25,7 @@
 # *****************************************************************************
 
 import dpctl.tensor as dpt
+from dpctl.tensor._numpy_helper import AxisError
 
 import dpnp
 
@@ -205,6 +206,7 @@ def __bool__(self):
         return self._array_obj.__bool__()
 
     # '__class__',
+    # `__class_getitem__`,
 
     def __complex__(self):
         return self._array_obj.__complex__()
@@ -335,6 +337,8 @@ def __getitem__(self, key):
         res._array_obj = item
         return res
 
+    # '__getstate__',
+
     def __gt__(self, other):
         """Return ``self>value``."""
         return dpnp.greater(self, other)
@@ -361,7 +365,31 @@ def __ilshift__(self, other):
         dpnp.left_shift(self, other, out=self)
         return self
 
-    # '__imatmul__',
+    def __imatmul__(self, other):
+        """Return ``self@=value``."""
+
+        """
+        Unlike `matmul(a, b, out=a)` we ensure that the result is not broadcast
+        if the result without `out` would have less dimensions than `a`.
+        Since the signature of matmul is '(n?,k),(k,m?)->(n?,m?)' this is the
+        case exactly when the second operand has both core dimensions.
+        We have to enforce this check by passing the correct `axes=`.
+        """
+        if self.ndim == 1:
+            axes = [(-1,), (-2, -1), (-1,)]
+        else:
+            axes = [(-2, -1), (-2, -1), (-2, -1)]
+
+        try:
+            dpnp.matmul(self, other, out=self, axes=axes)
+        except AxisError:
+            # AxisError should indicate that the axes argument didn't work out
+            # which should mean the second operand not being 2 dimensional.
+            raise ValueError(
+                "inplace matrix multiplication requires the first operand to "
+                "have at least one and the second at least two dimensions."
+            )
+        return self
 
     def __imod__(self, other):
         """Return ``self%=value``."""
@@ -469,9 +497,11 @@ def __pow__(self, other):
         return dpnp.power(self, other)
 
     def __radd__(self, other):
+        """Return ``value+self``."""
         return dpnp.add(other, self)
 
     def __rand__(self, other):
+        """Return ``value&self``."""
         return dpnp.bitwise_and(other, self)
 
     # '__rdivmod__',
@@ -483,40 +513,51 @@ def __repr__(self):
         return dpt.usm_ndarray_repr(self._array_obj, prefix="array")
 
     def __rfloordiv__(self, other):
+        """Return ``value//self``."""
         return dpnp.floor_divide(self, other)
 
     def __rlshift__(self, other):
+        """Return ``value<<self``."""
         return dpnp.left_shift(other, self)
 
     def __rmatmul__(self, other):
+        """Return ``value@self``."""
         return dpnp.matmul(other, self)
 
     def __rmod__(self, other):
+        """Return ``value%self``."""
         return dpnp.remainder(other, self)
 
     def __rmul__(self, other):
+        """Return ``value*self``."""
         return dpnp.multiply(other, self)
 
     def __ror__(self, other):
+        """Return ``value|self``."""
         return dpnp.bitwise_or(other, self)
 
     def __rpow__(self, other):
+        """Return ``value**self``."""
         return dpnp.power(other, self)
 
     def __rrshift__(self, other):
+        """Return ``value>>self``."""
         return dpnp.right_shift(other, self)
 
     def __rshift__(self, other):
         """Return ``self>>value``."""
         return dpnp.right_shift(self, other)
 
     def __rsub__(self, other):
+        """Return ``value-self``."""
         return dpnp.subtract(other, self)
 
     def __rtruediv__(self, other):
+        """Return ``value/self``."""
         return dpnp.true_divide(other, self)
 
     def __rxor__(self, other):
+        """Return ``value^self``."""
         return dpnp.bitwise_xor(other, self)
 
     # '__setattr__',

dpnp/dpnp_utils/dpnp_utils_linearalgebra.py

@@ -28,7 +28,7 @@
 import dpctl.tensor._tensor_impl as ti
 import dpctl.utils as dpu
 import numpy
-from dpctl.tensor._numpy_helper import normalize_axis_tuple
+from dpctl.tensor._numpy_helper import AxisError, normalize_axis_tuple
 from dpctl.utils import ExecutionPlacementError
 
 import dpnp
@@ -525,15 +525,15 @@ def _validate_internal(axes, i, ndim):
                 )
 
             if len(axes) != 1:
-                raise ValueError(
+                raise AxisError(
                     f"Axes item {i} should be a tuple with a single element, or an integer."
                 )
         else:
             iter = 2
             if not isinstance(axes, tuple):
                 raise TypeError(f"Axes item {i} should be a tuple.")
             if len(axes) != 2:
-                raise ValueError(
+                raise AxisError(
                     f"Axes item {i} should be a tuple with 2 elements."
                 )
 
@@ -563,7 +563,7 @@ def _validate_internal(axes, i, ndim):
 
     if x1_ndim == 1 and x2_ndim == 1:
         if axes[2] != ():
-            raise TypeError("Axes item 2 should be an empty tuple.")
+            raise AxisError("Axes item 2 should be an empty tuple.")
     elif x1_ndim == 1 or x2_ndim == 1:
         axes[2] = _validate_internal(axes[2], 2, 1)
     else: