def handle_method_call(self, env, node, call_node):
"""
Resolve an extension method of a static (C++/Cython-like) vtable:
typedef {
double (*method1)(double);
...
} vtab_struct;
vtab_struct *vtab = *(vtab_struct **) (((char *) obj) + vtab_offset)
void *method = vtab[index]
"""
# Make the object we call the method on clone-able
node.value = nodes.CloneableNode(node.value)
ext_type = node.value.type
offset = ext_type.vtab_offset
vtable_struct = ext_type.vtab_type.to_struct()
vtable_struct_type = vtable_struct.ref()
vtab_struct_pointer_pointer = nodes.value_at_offset(
node.value, offset, vtable_struct_type.pointer())
vtab_struct_pointer = nodes.DereferenceNode(
vtab_struct_pointer_pointer)
vmethod = nodes.StructAttribute(vtab_struct_pointer, node.attr,
ast.Load(), vtable_struct_type)
# Insert first argument 'self' in args list
args = call_node.args
args.insert(0, nodes.CloneNode(node.value))
result = nodes.NativeFunctionCallNode(node.type, vmethod, args)
return result
def visit_ListComp(self, node):
"""
Rewrite list comprehensions to the equivalent for loops.
AST syntax:
ListComp(expr elt, comprehension* generators)
comprehension = (expr target, expr iter, expr* ifs)
'ifs' represent a chain of ANDs
"""
assert len(node.generators) > 0
# Create innermost body, i.e. list.append(expr)
# TODO: size hint for PyList_New
list_create = ast.List(elts=[], ctx=ast.Load())
list_create.type = typesystem.object_ # typesystem.list_()
list_create = nodes.CloneableNode(list_create)
list_value = nodes.CloneNode(list_create)
list_append = ast.Attribute(list_value, "append", ast.Load())
append_call = ast.Call(func=list_append,
args=[node.elt],
keywords=[],
starargs=None,
kwargs=None)
# Build up the loops from inwards to outwards
body = append_call
for comprehension in reversed(node.generators):
# Hanlde the 'if' clause
ifs = comprehension.ifs
if len(ifs) > 1:
make_boolop = lambda op1_op2: ast.BoolOp(op=ast.And(),
values=op1_op2)
if_test = reduce(make_boolop, ifs)
elif len(ifs) == 1:
if_test, = ifs
else:
if_test = None
if if_test is not None:
body = ast.If(test=if_test, body=[body], orelse=[])
# Wrap list.append() call or inner loops
body = ast.For(target=comprehension.target,
iter=comprehension.iter,
body=[body],
orelse=[])
expr = nodes.ExpressionNode(stmts=[list_create, body], expr=list_value)
return self.visit(expr)
def handle_method_call(self, env, node, call_node):
"""
Resolve an extension method of a dynamic hash-based vtable:
PyCustomSlots_Table ***vtab_slot = (((char *) obj) + vtab_offset)
lookup_virtual_method(*vtab_slot)
We may cache (*vtab_slot), but we may not cache (**vtab_slot), since
compilations may regenerate the table.
However, we could *preload* (**vtab_slot), where function calls
invalidate the preload, if we were so inclined.
"""
# Make the object we call the method on clone-able
node.value = nodes.CloneableNode(node.value)
ext_type = node.ext_type
func_signature = node.type #typesystem.extmethod_to_function(node.type)
offset = ext_type.vtab_offset
# __________________________________________________________________
# Retrieve vtab
vtab_ppp = nodes.value_at_offset(node.value, offset,
void.pointer().pointer())
vtab_struct_pp = nodes.DereferenceNode(vtab_ppp)
# __________________________________________________________________
# Calculate pre-hash
prehash = virtual.hash_signature(func_signature, func_signature.name)
prehash_node = nodes.ConstNode(prehash, uint64)
# __________________________________________________________________
# Retrieve method pointer
# A method is always present when it was given a static signature,
# e.g. @double(double)
always_present = node.attr in ext_type.vtab_type.methodnames
args = [vtab_struct_pp, prehash_node]
# lookup_impl = NumbaVirtualLookup()
lookup_impl = DebugVirtualLookup()
ptr = lookup_impl.lookup(env, always_present, node, args)
vmethod = ptr.coerce(func_signature.pointer())
vmethod = vmethod.cloneable
# __________________________________________________________________
# Call method pointer
# Insert first argument 'self' in args list
args = call_node.args
args.insert(0, nodes.CloneNode(node.value))
method_call = nodes.NativeFunctionCallNode(func_signature, vmethod,
args)
# __________________________________________________________________
# Generate fallback
# TODO: Subclassing!
# if not always_present:
# # TODO: Enable this path and generate a phi for the result
# # Generate object call
# obj_args = [nodes.CoercionNode(arg, object_) for arg in args]
# obj_args.append(nodes.NULL)
# object_call = function_util.external_call(
# env.context, env.crnt.llvm_module,
# 'PyObject_CallMethodObjArgs', obj_args)
#
# # if vmethod != NULL: vmethod(obj, ...)
# # else: obj.method(...)
# method_call = nodes.if_else(
# ast.NotEq(),
# vmethod.clone, nodes.NULL,
# lhs=method_call, rhs=object_call)
return method_call
def register_array_expression(self, node, lhs=None):
super(ArrayExpressionRewriteNative, self).register_array_expression(
node, lhs)
lhs_type = lhs.type if lhs else node.type
is_expr = lhs is None
if node.type.is_array and lhs_type.ndim < node.type.ndim:
# TODO: this is valid in NumPy if the leading dimensions of the
# TODO: RHS have extent 1
raise error.NumbaError(
node, "Right hand side must have a "
"dimensionality <= %d" % lhs_type.ndim)
# Create ufunc scalar kernel
ufunc_ast, signature, ufunc_builder = self.get_py_ufunc_ast(lhs, node)
signature.struct_by_reference = True
# Compile ufunc scalar kernel with numba
ast.fix_missing_locations(ufunc_ast)
func_env, (_, _, _) = pipeline.run_pipeline2(
self.env, None, ufunc_ast, signature,
function_globals={},
)
# Manual linking
lfunc = func_env.lfunc
# print lfunc
operands = ufunc_builder.operands
functions.keep_alive(self.func, lfunc)
operands = [nodes.CloneableNode(operand) for operand in operands]
if lhs is not None:
lhs = nodes.CloneableNode(lhs)
broadcast_operands = [lhs] + operands
lhs = lhs.clone
else:
broadcast_operands = operands[:]
shape = slicenodes.BroadcastNode(lhs_type, broadcast_operands)
operands = [op.clone for op in operands]
if lhs is None and self.nopython:
raise error.NumbaError(
node, "Cannot allocate new memory in nopython context")
elif lhs is None:
# TODO: determine best output order at runtime
shape = shape.cloneable
lhs = nodes.ArrayNewEmptyNode(lhs_type, shape.clone,
lhs_type.is_f_contig).cloneable
# Build minivect wrapper kernel
context = NumbaproStaticArgsContext()
context.llvm_module = self.env.llvm_context.module
# context.debug = True
context.optimize_broadcasting = False
b = context.astbuilder
variables = [b.variable(name_node.type, "op%d" % i)
for i, name_node in enumerate([lhs] + operands)]
miniargs = [b.funcarg(variable) for variable in variables]
body = miniutils.build_kernel_call(lfunc.name, signature, miniargs, b)
minikernel = b.function_from_numpy(
templating.temp_name("array_expression"), body, miniargs)
lminikernel, ctypes_kernel = context.run_simple(
minikernel, specializers.StridedSpecializer)
# Build call to minivect kernel
operands.insert(0, lhs)
args = [shape]
scalar_args = []
for operand in operands:
if operand.type.is_array:
data_p = self.array_attr(operand, 'data')
data_p = nodes.CoercionNode(data_p,
operand.type.dtype.pointer())
if not isinstance(operand, nodes.CloneNode):
operand = nodes.CloneNode(operand)
strides_p = self.array_attr(operand, 'strides')
args.extend((data_p, strides_p))
else:
scalar_args.append(operand)
args.extend(scalar_args)
result = nodes.NativeCallNode(minikernel.type, args, lminikernel)
# Use native slicing in array expressions
slicenodes.mark_nopython(ast.Suite(body=result.args))
if not is_expr:
# a[:] = b[:] * c[:]
return result
# b[:] * c[:], return new array as expression
return nodes.ExpressionNode(stmts=[result], expr=lhs.clone)
