Remove hacks for device scalars

pytential/symbolic/execution.py

@@ -100,44 +100,6 @@ def __init__(self, bound_expr, actx: PyOpenCLArrayContext, context=None,
 
         self.queue = actx.queue
 
-    # {{{ TODO: remove when device scalar broadcasting is fixed
-
-    # NOTE:
-    # * awaiting resolution of https://github.com/inducer/arraycontext/issues/49
-    # * these are only the operations required to pass tests
-
-    def _force_host_scalar(self, arg):
-        if isinstance(arg, cl.array.Array) and arg.shape == ():
-            return self.array_context.to_numpy(arg)[()]
-        elif isinstance(arg, np.ndarray) and arg.shape == ():
-            return arg[()]
-        else:
-            return arg
-
-    def _map_device_scalar_reduction(self, func, expr):
-        return func(
-                self._force_host_scalar(self.rec(child))
-                for child in expr.children)
-
-    def map_sum(self, expr):
-        return self._map_device_scalar_reduction(sum, expr)
-
-    def map_product(self, expr):
-        from pytools import product
-        return self._map_device_scalar_reduction(product, expr)
-
-    def _map_device_scalar_op(self, op, arg1, arg2):
-        return op(
-                self._force_host_scalar(self.rec(arg1)),
-                self._force_host_scalar(self.rec(arg2)))
-
-    def map_quotient(self, expr):
-        import operator
-        return self._map_device_scalar_op(
-                operator.truediv, expr.numerator, expr.denominator)
-
-    # }}}
-
     # {{{ map_XXX
 
     def _map_minmax(self, func, inherited_func, expr):
@@ -163,27 +125,21 @@ def map_min(self, expr):
 
     def map_node_sum(self, expr):
         actx = self.array_context
-        result = sum(actx.np.sum(grp_ary) for grp_ary in self.rec(expr.operand))
-        if not actx._force_device_scalars:
-            result = actx.to_numpy(result)[()]
-
-        return result
+        return sum(actx.np.sum(grp_ary) for grp_ary in self.rec(expr.operand))
 
     def map_node_max(self, expr):
+        from functools import reduce
         actx = self.array_context
-        result = max(actx.np.max(grp_ary) for grp_ary in self.rec(expr.operand))
-        if not actx._force_device_scalars:
-            result = actx.to_numpy(result)[()]
-
-        return result
+        return reduce(
+            actx.np.maximum,
+            (actx.np.max(grp_ary) for grp_ary in self.rec(expr.operand)))
 
     def map_node_min(self, expr):
+        from functools import reduce
         actx = self.array_context
-        result = min(actx.np.min(grp_ary) for grp_ary in self.rec(expr.operand))
-        if not actx._force_device_scalars:
-            result = actx.to_numpy(result)[()]
-
-        return result
+        return reduce(
+            actx.np.minimum,
+            (actx.np.min(grp_ary) for grp_ary in self.rec(expr.operand)))
 
     def _map_elementwise_reduction(self, reduction_name, expr):
         import loopy as lp
@@ -544,23 +500,19 @@ def matvec(self, x):
         #    => output is a flat PyOpenCL array
         # * structured arrays (object arrays/DOFArrays)
         #    => output has same structure as input
-        if isinstance(x, np.ndarray) and x.dtype.char != "O":
-            x = self.array_context.from_numpy(x)
-            flat = True
-            host = True
-            assert x.shape == (self.total_dofs,)
+        if isinstance(x, DOFArray):
+            flat, host = False, False
+        elif isinstance(x, np.ndarray) and x.dtype.char == "O":
+            flat, host = False, False
         elif isinstance(x, cl.array.Array):
-            flat = True
-            host = False
+            flat, host = True, False
+            assert x.shape == (self.total_dofs,)
+        elif isinstance(x, np.ndarray) and x.dtype.char != "O":
+            x = self.array_context.from_numpy(x)
+            flat, host = True, True
             assert x.shape == (self.total_dofs,)
-        elif isinstance(x, np.ndarray) and x.dtype.char == "O":
-            flat = False
-            host = False
-        elif isinstance(x, DOFArray):
-            flat = False
-            host = False
         else:
-            raise ValueError("unsupported input type")
+            raise ValueError(f"unsupported input type: {type(x).__name__}")
 
         args = self.extra_args.copy()
         args[self.arg_name] = self.unflatten(x) if flat else x

setup.py

@@ -119,7 +119,7 @@ def write_git_revision(package_name):
     install_requires=[
         "pytools>=2018.2",
         "modepy>=2013.3",
-        "pyopencl>=2013.1",
+        "pyopencl>=2021.2.6",
         "boxtree>=2019.1",
         "pymbolic>=2013.2",
         "loopy>=2020.2",