diff --git a/loopy/kernel/creation.py b/loopy/kernel/creation.py
index 5a642322021136de6f84325118311437761d98d5..343c850149df72f90c6860aa0b5db16fa1528718 100644
--- a/loopy/kernel/creation.py
+++ b/loopy/kernel/creation.py
@@ -1898,7 +1898,7 @@ class FunctionScoper(IdentityMapper):
from loopy.symbolic import Reduction
return Reduction(
- ScopedFunction(expr.operation.name),
+ ScopedFunction(expr.function.name),
tuple(new_inames),
self.rec(expr.expr),
allow_simultaneous=expr.allow_simultaneous)
@@ -1918,9 +1918,10 @@ class ScopedFunctionCollector(CombineMapper):
def map_reduction(self, expr):
from loopy.kernel.reduction_callable import CallableReduction
+ from loopy.kernel.function_interface import CallableOnScalar
from loopy.symbolic import Reduction
- callable_reduction = CallableReduction(expr.operation.name)
+ callable_reduction = CallableReduction(expr.function.name)
# sanity checks
@@ -1949,8 +1950,14 @@ class ScopedFunctionCollector(CombineMapper):
elif isinstance(expr, Reduction) and callable_reduction.is_tuple_typed:
raise LoopyError("got a tuple typed argument to a scalar reduction")
- return frozenset([(expr.operation.name,
- callable_reduction)])
+ hidden_function = callable_reduction.operation.hidden_function()
+ if hidden_function is not None:
+ return frozenset([(expr.function.name,
+ callable_reduction), (hidden_function,
+ CallableOnScalar(hidden_function))])
+ else:
+ return frozenset([(expr.function.name,
+ callable_reduction)])
def map_constant(self, expr):
return frozenset()
diff --git a/loopy/kernel/function_interface.py b/loopy/kernel/function_interface.py
index bc5d178b13bdd66f37f5f0b59238d6ba248512bd..fb80c5876a37110442d56234a2c20e9f78ab40b6 100644
--- a/loopy/kernel/function_interface.py
+++ b/loopy/kernel/function_interface.py
@@ -134,23 +134,17 @@ class InKernelCallable(ImmutableRecord):
"""
- fields = set(["name", "arg_id_to_dtype", "arg_id_to_descr"])
- init_arg_names = ("name", "arg_id_to_dtype", "arg_id_to_descr")
+ fields = set(["arg_id_to_dtype", "arg_id_to_descr"])
+ init_arg_names = ("arg_id_to_dtype", "arg_id_to_descr")
- def __init__(self, name, arg_id_to_dtype=None, arg_id_to_descr=None):
+ def __init__(self, arg_id_to_dtype=None, arg_id_to_descr=None):
- # sanity checks
-
- if not isinstance(name, str):
- raise LoopyError("name of an InKernelCallable should be a string")
-
- super(InKernelCallable, self).__init__(name=name,
+ super(InKernelCallable, self).__init__(
arg_id_to_dtype=arg_id_to_dtype,
arg_id_to_descr=arg_id_to_descr)
def __getinitargs__(self):
- return (self.name, self.arg_id_to_dtype, self.arg_id_to_descr,
- self.name_in_target)
+ return (self.arg_id_to_dtype, self.arg_id_to_descr)
def with_types(self, arg_id_to_dtype, target):
"""
@@ -245,10 +239,11 @@ class CallableOnScalar(InKernelCallable):
def __init__(self, name, arg_id_to_dtype=None,
arg_id_to_descr=None, name_in_target=None):
- super(InKernelCallable, self).__init__(name=name,
+ super(InKernelCallable, self).__init__(
arg_id_to_dtype=arg_id_to_dtype,
arg_id_to_descr=arg_id_to_descr)
+ self.name = name
self.name_in_target = name_in_target
def __getinitargs__(self):
@@ -265,7 +260,7 @@ class CallableOnScalar(InKernelCallable):
if self.arg_id_to_dtype[id] != arg_id_to_dtype[id]:
raise LoopyError("Overwriting a specialized"
" function is illegal--maybe start with new instance of"
- " CallableScalar?")
+ " CallableOnScalar?")
# {{{ attempt to specialize using scalar functions present in target
@@ -406,12 +401,13 @@ class CallableKernel(InKernelCallable):
def __init__(self, name, subkernel, arg_id_to_dtype=None,
arg_id_to_descr=None, name_in_target=None):
- super(InKernelCallable, self).__init__(name=name,
+ super(InKernelCallable, self).__init__(
arg_id_to_dtype=arg_id_to_dtype,
arg_id_to_descr=arg_id_to_descr)
if name_in_target is not None:
subkernel = subkernel.copy(name=name_in_target)
+ self.name = name
self.name_in_target = name_in_target
self.subkernel = subkernel
@@ -628,7 +624,7 @@ def register_pymbolic_calls_to_knl_callables(kernel,
unique_name = next_indexed_name(unique_name)
# book-keeping of the functions and names mappings for later use
- if in_knl_callable.subkernel is not None:
+ if isinstance(in_knl_callable, CallableKernel):
# for array calls the name in the target is the name of the
# scoped funciton
in_knl_callable = in_knl_callable.copy(
diff --git a/loopy/kernel/reduction_callable.py b/loopy/kernel/reduction_callable.py
index 1682f71608dc0e066cf6930cc2e6b07649bbc8d5..1ad2acd8db6891490f5b7e7fff68d9c3ffd9268b 100644
--- a/loopy/kernel/reduction_callable.py
+++ b/loopy/kernel/reduction_callable.py
@@ -28,7 +28,7 @@ class CallableReduction(InKernelCallable):
self.operation = operation
- super(InKernelCallable, self).__init__(name="",
+ super(InKernelCallable, self).__init__(
arg_id_to_dtype=arg_id_to_dtype,
arg_id_to_descr=arg_id_to_descr)
@@ -47,39 +47,32 @@ class CallableReduction(InKernelCallable):
for id, dtype in arg_id_to_dtype.items():
# only checking for the ones which have been provided
- if self.arg_id_to_dtype[id] != arg_id_to_dtype[id]:
+ if id in self.arg_id_to_dtype and (
+ self.arg_id_to_dtype[id] != arg_id_to_dtype[id]):
raise LoopyError("Overwriting a specialized"
" function is illegal--maybe start with new instance of"
- " CallableScalar?")
-
- if self.name in target.get_device_ast_builder().function_identifiers():
- new_in_knl_callable = target.get_device_ast_builder().with_types(
- self, arg_id_to_dtype)
- if new_in_knl_callable is None:
- new_in_knl_callable = self.copy()
- return new_in_knl_callable
-
- # did not find a scalar function and function prototype does not
- # even have subkernel registered => no match found
- raise LoopyError("Function %s not present within"
- " the %s namespace" % (self.name, target))
+ " CallableReduction?")
+ updated_arg_id_to_dtype = self.operation.with_types(arg_id_to_dtype,
+ target)
+ return self.copy(arg_id_to_dtype=updated_arg_id_to_dtype)
def with_descrs(self, arg_id_to_descr):
+ # not sure what would be the reson of having this over here
# This is a scalar call
# need to assert that the name is in funtion indentifiers
arg_id_to_descr[-1] = ValueArgDescriptor()
return self.copy(arg_id_to_descr=arg_id_to_descr)
- def with_iname_tag_usage(self, unusable, concurrent_shape):
-
- raise NotImplementedError()
+ def inline(self, kernel):
+ # Replaces the job of realize_reduction
+ raise NotImplementedError
def is_ready_for_code_gen(self):
return (self.arg_id_to_dtype is not None and
self.arg_id_to_descr is not None and
- self.name_in_target is not None)
+ self.operation is not None)
# vim: foldmethod=marker
diff --git a/loopy/library/reduction.py b/loopy/library/reduction.py
index 5daa1528a7d67c0dc35644dc40c6d179dc01527e..f4444c8864a44840f624c63ab282769e0f321a9a 100644
--- a/loopy/library/reduction.py
+++ b/loopy/library/reduction.py
@@ -36,7 +36,7 @@ class ReductionOperation(object):
equality-comparable.
"""
- def result_dtypes(self, target, *arg_dtypes):
+ def with_types(self, arg_id_to_dtype, target):
"""
:arg arg_dtypes: may be None if not known
:returns: None if not known, otherwise the returned type
@@ -51,6 +51,9 @@ class ReductionOperation(object):
def neutral_element(self, *dtypes):
raise NotImplementedError
+ def hidden_function(self):
+ return None
+
def __hash__(self):
# Force subclasses to override
raise NotImplementedError
@@ -95,15 +98,22 @@ class ScalarReductionOperation(ReductionOperation):
def arg_count(self):
return 1
- def result_dtypes(self, kernel, arg_dtype):
+ def with_types(self, arg_id_to_dtype, target):
+ if 0 not in arg_id_to_dtype or arg_id_to_dtype[0] is None:
+ # do not have enough info to figure out the type.
+ return arg_id_to_dtype.copy()
+
+ arg_dtype = arg_id_to_dtype[0]
+
+ updated_arg_id_to_dtype = arg_id_to_dtype.copy()
if self.forced_result_type is not None:
- return (self.parse_result_type(
- kernel.target, self.forced_result_type),)
+ updated_arg_id_to_dtype[-1] = (self.parse_result_type(
+ target, self.forced_result_type),)
+ return updated_arg_id_to_dtype
- if arg_dtype is None:
- return None
+ updated_arg_id_to_dtype[-1] = arg_dtype
- return (arg_dtype,)
+ return updated_arg_id_to_dtype
def __hash__(self):
return hash((type(self), self.forced_result_type))
@@ -180,7 +190,11 @@ class MaxReductionOperation(ScalarReductionOperation):
return get_ge_neutral(dtype)
def __call__(self, dtype, operand1, operand2):
- return var("max")(operand1, operand2)
+ from loopy.symbolic import ScopedFunction
+ return ScopedFunction("max")(operand1, operand2)
+
+ def hidden_function(self):
+ return "max"
class MinReductionOperation(ScalarReductionOperation):
@@ -188,7 +202,11 @@ class MinReductionOperation(ScalarReductionOperation):
return get_le_neutral(dtype)
def __call__(self, dtype, operand1, operand2):
- return var("min")(operand1, operand2)
+ from loopy.symbolic import ScopedFunction
+ return ScopedFunction("min")(operand1, operand2)
+
+ def hidden_function(self):
+ return "min"
# {{{ base class for symbolic reduction ops
@@ -233,9 +251,22 @@ class _SegmentedScalarReductionOperation(ReductionOperation):
return var("make_tuple")(scalar_neutral_element,
segment_flag_dtype.numpy_dtype.type(0))
- def result_dtypes(self, kernel, scalar_dtype, segment_flag_dtype):
- return (self.inner_reduction.result_dtypes(kernel, scalar_dtype)
- + (segment_flag_dtype,))
+ def with_types(self, arg_id_to_dtype, target):
+ for id in range(self.arg_count):
+ if id not in arg_id_to_dtype or arg_id_to_dtype[id] is None:
+ # types of arguemnts not known => result type cannot be
+ # determined.
+ return arg_id_to_dtype.copy()
+
+ scalar_dtype = arg_id_to_dtype[0]
+ segment_flag_dtype = arg_id_to_dtype[1]
+
+ updated_arg_id_to_dtype = arg_id_to_dtype.copy()
+ updated_arg_id_to_dtype[-1] = self.inner_reduction.with_types(
+ {0: scalar_dtype}, target)[-1]
+ updated_arg_id_to_dtype[-2] = segment_flag_dtype
+
+ return updated_arg_id_to_dtype
def __str__(self):
return "segmented(%s)" % self.which
@@ -299,8 +330,22 @@ class _ArgExtremumReductionOperation(ReductionOperation):
scalar_dtype.numpy_dtype.type.__name__,
index_dtype.numpy_dtype.type.__name__)
- def result_dtypes(self, kernel, scalar_dtype, index_dtype):
- return (scalar_dtype, index_dtype)
+ def with_types(self, arg_id_to_dtype, target):
+ for id in range(self.arg_count):
+ if id not in arg_id_to_dtype or arg_id_to_dtype[id] is None:
+ # types of arguemnts not known => result type cannot be
+ # determined.
+ return self.copy(arg_id_to_dtype=arg_id_to_dtype)
+
+ scalar_dtype = arg_id_to_dtype[0]
+ index_dtype = arg_id_to_dtype[1]
+
+ updated_arg_id_to_dtype = arg_id_to_dtype.copy()
+
+ updated_arg_id_to_dtype[-1] = scalar_dtype
+ updated_arg_id_to_dtype[-2] = index_dtype
+
+ return updated_arg_id_to_dtype
def neutral_element(self, scalar_dtype, index_dtype):
scalar_neutral_func = (
@@ -331,12 +376,18 @@ class ArgMaxReductionOperation(_ArgExtremumReductionOperation):
update_comparison = ">="
neutral_sign = -1
+ def hidden_function(self):
+ return "max"
+
class ArgMinReductionOperation(_ArgExtremumReductionOperation):
which = "min"
update_comparison = "<="
neutral_sign = +1
+ def hidden_function(self):
+ return "min"
+
def get_argext_preamble(kernel, func_id, arg_dtypes):
op = func_id.reduction_op
@@ -377,8 +428,8 @@ def get_argext_preamble(kernel, func_id, arg_dtypes):
_REDUCTION_OPS = {
"sum": SumReductionOperation,
"product": ProductReductionOperation,
- "max": MaxReductionOperation,
- "min": MinReductionOperation,
+ "maximum": MaxReductionOperation,
+ "minimum": MinReductionOperation,
"argmax": ArgMaxReductionOperation,
"argmin": ArgMinReductionOperation,
"segmented(sum)": SegmentedSumReductionOperation,
@@ -429,6 +480,12 @@ def reduction_function_identifiers():
return set(op for op in _REDUCTION_OPS)
+def reduction_function_mangler(kernel, func_id, arg_dtypes):
+ raise NotImplementedError("Reduction Function Mangler!")
+
+
+'''
+# KK -- we will replace this with the new interface
def reduction_function_mangler(kernel, func_id, arg_dtypes):
if isinstance(func_id, ArgExtOp):
from loopy.target.opencl import CTarget
@@ -475,6 +532,7 @@ def reduction_function_mangler(kernel, func_id, arg_dtypes):
)
return None
+'''
def reduction_preamble_generator(preamble_info):
diff --git a/loopy/preprocess.py b/loopy/preprocess.py
index 34fe6e830c3f3a3cf42d6b77a12fda54c727276f..51389f4f56669e1cebaf7e6b04e5f3e8d9cde0ae 100644
--- a/loopy/preprocess.py
+++ b/loopy/preprocess.py
@@ -39,7 +39,6 @@ from loopy.kernel.data import make_assignment
# for the benefit of loopy.statistics, for now
from loopy.type_inference import infer_unknown_types
from loopy.symbolic import ScopedFunction, CombineMapper
-from pymbolic.mapper import Collector
from loopy.kernel.instruction import (MultiAssignmentBase, CInstruction,
CallInstruction, _DataObliviousInstruction)
@@ -893,7 +892,6 @@ def _insert_subdomain_into_domain_tree(kernel, domains, subdomain):
# }}}
-
def realize_reduction(kernel, insn_id_filter=None, unknown_types_ok=True,
automagic_scans_ok=False, force_scan=False,
force_outer_iname_for_scan=None):
@@ -1041,13 +1039,16 @@ def realize_reduction(kernel, insn_id_filter=None, unknown_types_ok=True,
init_id = insn_id_gen(
"%s_%s_init" % (insn.id, "_".join(expr.inames)))
+ reduction_operation = kernel.scoped_functions[
+ expr.function.name].operation
+
init_insn = make_assignment(
id=init_id,
assignees=acc_vars,
within_inames=outer_insn_inames - frozenset(expr.inames),
within_inames_is_final=insn.within_inames_is_final,
depends_on=init_insn_depends_on,
- expression=expr.operation.neutral_element(*arg_dtypes),
+ expression=reduction_operation.neutral_element(*arg_dtypes),
predicates=insn.predicates,)
generated_insns.append(init_insn)
@@ -1082,10 +1083,12 @@ def realize_reduction(kernel, insn_id_filter=None, unknown_types_ok=True,
else:
reduction_expr = expr.expr
+ reduction_operation = kernel.scoped_functions[
+ expr.function.name].operation
reduction_insn = make_assignment(
id=update_id,
assignees=acc_vars,
- expression=expr.operation(
+ expression=reduction_operation(
arg_dtypes,
_strip_if_scalar(acc_vars, acc_vars),
reduction_expr),
@@ -1094,8 +1097,6 @@ def realize_reduction(kernel, insn_id_filter=None, unknown_types_ok=True,
within_inames_is_final=insn.within_inames_is_final,
predicates=insn.predicates,)
- reduction_insn = scope_function_in_insn(reduction_insn, kenrel)
-
generated_insns.append(reduction_insn)
new_insn_add_depends_on.add(reduction_insn.id)
@@ -1944,6 +1945,8 @@ def realize_reduction(kernel, insn_id_filter=None, unknown_types_ok=True,
kernel = lp.tag_inames(kernel, new_iname_tags)
+ # making changes to the scoped function that are arising
+
# TODO: remove unused inames...
kernel = (
@@ -2381,10 +2384,6 @@ def preprocess_kernel(kernel, device=None):
from loopy.kernel.creation import apply_single_writer_depencency_heuristic
kernel = apply_single_writer_depencency_heuristic(kernel)
- # inferring the shape and dim_tags of the arguments involved in a function
- # call.
- kernel = infer_arg_descr(kernel)
-
# Ordering restrictions:
#
# - realize_reduction must happen after type inference because it needs
@@ -2396,6 +2395,10 @@ def preprocess_kernel(kernel, device=None):
kernel = realize_reduction(kernel, unknown_types_ok=False)
+ # inferring the shape and dim_tags of the arguments involved in a function
+ # call.
+ kernel = infer_arg_descr(kernel)
+
# Ordering restriction:
# add_axes_to_temporaries_for_ilp because reduction accumulators
# need to be duplicated by this.
diff --git a/loopy/symbolic.py b/loopy/symbolic.py
index e8e39a24f35f0744046a420750f4768c02e5c0ca..32670c1cc26bef1dacc18c0a46f70c92a00d9405 100644
--- a/loopy/symbolic.py
+++ b/loopy/symbolic.py
@@ -96,7 +96,7 @@ class IdentityMapperMixin(object):
new_inames.append(new_sym_iname.name)
return Reduction(
- expr.operation, tuple(new_inames),
+ expr.function, tuple(new_inames),
self.rec(expr.expr, *args),
allow_simultaneous=expr.allow_simultaneous)
@@ -226,7 +226,7 @@ class StringifyMapper(StringifyMapperBase):
return "%sreduce(%s, [%s], %s)" % (
"simul_" if expr.allow_simultaneous else "",
- expr.operation, ", ".join(expr.inames),
+ expr.function, ", ".join(expr.inames),
self.rec(expr.expr, PREC_NONE))
def map_tagged_variable(self, expr, prec):
@@ -266,7 +266,7 @@ class UnidirectionalUnifier(UnidirectionalUnifierBase):
if not isinstance(other, type(expr)):
return self.treat_mismatch(expr, other, unis)
if (expr.inames != other.inames
- or type(expr.operation) != type(other.operation) # noqa
+ or type(expr.function) != type(other.function) # noqa
):
return []
@@ -537,7 +537,7 @@ class Reduction(p.Expression):
"""Represents a reduction operation on :attr:`exprs`
across :attr:`inames`.
- ..attribute:: operation
+ ..attribute:: function
an instance of :class:`pymbolic.primitives.Variable` which indicates
the reduction callable that the reduction would point to in the dict
@@ -562,10 +562,10 @@ class Reduction(p.Expression):
in precisely one reduction, to avoid mis-nesting errors.
"""
- init_arg_names = ("operation", "inames", "expr", "allow_simultaneous")
+ init_arg_names = ("function", "inames", "expr", "allow_simultaneous")
- def __init__(self, operation, inames, expr, allow_simultaneous=False):
- assert isinstance(operation, p.Variable)
+ def __init__(self, function, inames, expr, allow_simultaneous=False):
+ assert isinstance(function, p.Variable)
if isinstance(inames, str):
inames = tuple(iname.strip() for iname in inames.split(","))
@@ -610,20 +610,20 @@ class Reduction(p.Expression):
raise LoopyError("got a tuple typed argument to a scalar reduction")
"""
- self.operation = operation
+ self.function = function
self.inames = inames
self.expr = expr
self.allow_simultaneous = allow_simultaneous
def __getinitargs__(self):
- return (self.operation, self.inames, self.expr, self.allow_simultaneous)
+ return (self.funciton, self.inames, self.expr, self.allow_simultaneous)
def get_hash(self):
- return hash((self.__class__, self.operation, self.inames, self.expr))
+ return hash((self.__class__, self.function, self.inames, self.expr))
def is_equal(self, other):
return (other.__class__ == self.__class__
- and other.operation == self.operation
+ and other.function == self.function
and other.inames == self.inames
and other.expr == self.expr)
@@ -1146,10 +1146,10 @@ class FunctionToPrimitiveMapper(IdentityMapper):
turns those into the actual pymbolic primitives used for that.
"""
- def _parse_reduction(self, operation, inames, red_exprs,
+ def _parse_reduction(self, function, inames, red_exprs,
allow_simultaneous=False):
- assert isinstance(operation, str)
- operation = p.Variable(operation)
+ assert isinstance(function, str)
+ function = p.Variable(function)
if isinstance(inames, p.Variable):
inames = (inames,)
@@ -1168,7 +1168,7 @@ class FunctionToPrimitiveMapper(IdentityMapper):
if len(red_exprs) == 1:
red_exprs = red_exprs[0]
- return Reduction(operation, tuple(processed_inames), red_exprs,
+ return Reduction(function, tuple(processed_inames), red_exprs,
allow_simultaneous=allow_simultaneous)
def map_call(self, expr):
@@ -1194,10 +1194,10 @@ class FunctionToPrimitiveMapper(IdentityMapper):
elif name in set(["reduce, simul_reduce"]):
if len(expr.parameters) >= 3:
- operation, inames = expr.parameters[:2]
+ function, inames = expr.parameters[:2]
red_exprs = expr.parameters[2:]
- return self._parse_reduction(str(operation), inames,
+ return self._parse_reduction(str(function), inames,
tuple(self.rec(red_expr) for red_expr in red_exprs),
allow_simultaneous=(name == "simul_reduce"))
else:
diff --git a/loopy/target/opencl.py b/loopy/target/opencl.py
index 7aec34a22a4a4a6282ab6065abd412f16612bcdc..7ffd91309b9b82a86c17357abca9fe381a145e33 100644
--- a/loopy/target/opencl.py
+++ b/loopy/target/opencl.py
@@ -255,7 +255,7 @@ def opencl_with_types(in_knl_callable, arg_id_to_dtype):
dtype = np.find_common_type(
[], [dtype.numpy_dtype for id, dtype in
- arg_id_to_dtype.values() if id >= 0])
+ arg_id_to_dtype.items() if id >= 0])
if dtype.kind == "i":
dtype = NumpyType(dtype)
diff --git a/loopy/type_inference.py b/loopy/type_inference.py
index 11113538eeadb4fc103bdc15cacc54899bcb864d..8df9773a98dcafe809f81de88f068e4948ace410 100644
--- a/loopy/type_inference.py
+++ b/loopy/type_inference.py
@@ -396,7 +396,10 @@ class TypeInferenceMapper(CombineMapper):
from loopy.symbolic import Reduction
from pymbolic.primitives import Call
- if not return_tuple and expr.is_tuple_typed:
+ reduction_callable = self.scoped_functions[
+ expr.function.name]
+
+ if not return_tuple and reduction_callable.is_tuple_typed:
raise LoopyError("reductions with more or fewer than one "
"return value may only be used in direct "
"assignments")
@@ -416,12 +419,23 @@ class TypeInferenceMapper(CombineMapper):
else:
rec_results = self.rec(expr.expr)
- if return_tuple:
- return [expr.operation.result_dtypes(self.kernel, *rec_result)
- for rec_result in rec_results]
- else:
- return [expr.operation.result_dtypes(self.kernel, rec_result)[0]
- for rec_result in rec_results]
+ arg_id_to_dtype = dict(enumerate(rec_results))
+
+ in_knl_callable = (
+ self.scoped_functions[expr.function.name].with_types(
+ arg_id_to_dtype, self.kernel.target))
+
+ # storing the type specialized function so that it can be used for
+ # later use
+ self.specialized_functions[expr] = in_knl_callable
+
+ new_arg_id_to_dtype = in_knl_callable.arg_id_to_dtype
+
+ # collecting result dtypes in order of the assignees
+ if -1 in new_arg_id_to_dtype and new_arg_id_to_dtype[-1] is not None:
+ return [new_arg_id_to_dtype[-1]]
+
+ return []
def map_sub_array_ref(self, expr):
return self.rec(expr.get_begin_subscript())
@@ -691,8 +705,9 @@ def infer_arg_and_reduction_dtypes_for_reduction_expression(
kernel, expr, unknown_types_ok):
type_inf_mapper = TypeInferenceMapper(kernel)
import loopy as lp
+ callable_reduction = kernel.scoped_functions[expr.function.name]
- if expr.is_tuple_typed:
+ if callable_reduction.is_tuple_typed:
arg_dtypes_result = type_inf_mapper(
expr, return_tuple=True, return_dtype_set=True)
@@ -700,7 +715,7 @@ def infer_arg_and_reduction_dtypes_for_reduction_expression(
arg_dtypes = arg_dtypes_result[0]
else:
if unknown_types_ok:
- arg_dtypes = [lp.auto] * expr.operation.arg_count
+ arg_dtypes = [lp.auto] * callable_reduction.operation.arg_count
else:
raise LoopyError("failed to determine types of accumulators for "
"reduction '%s'" % expr)
@@ -714,13 +729,22 @@ def infer_arg_and_reduction_dtypes_for_reduction_expression(
raise LoopyError("failed to determine type of accumulator for "
"reduction '%s'" % expr)
- reduction_dtypes = expr.operation.result_dtypes(kernel, *arg_dtypes)
- reduction_dtypes = tuple(
- dt.with_target(kernel.target)
- if dt is not lp.auto else dt
- for dt in reduction_dtypes)
+ # TODODODODODODODODODO
+
+ new_arg_id_to_dtype = callable_reduction.with_types(
+ dict(enumerate(arg_dtypes)), kernel.target).arg_id_to_dtype
+
+ num_result = len([id for id in new_arg_id_to_dtype if id < 0])
+ reduction_dtypes = []
+
+ for id in range(num_result):
+ dt = new_arg_id_to_dtype[-id-1]
+ if dt is not lp.auto:
+ reduction_dtypes.append(dt.with_target(kernel.target))
+ else:
+ reduction_dtypes.append(dt)
- return tuple(arg_dtypes), reduction_dtypes
+ return tuple(arg_dtypes), tuple(reduction_dtypes)
# }}}