def string_split_2(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context._get_precompiled_function("StringSplitImpl")
func = module.get_or_insert_function(precomp_func.type.pointee,
precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s, sep] = args
maxsplit = context.get_constant_struct(builder, IntVal, -1)
cs = _conv_numba_struct_to_clang(builder, s, func.args[1].type)
csep = _conv_numba_struct_to_clang(builder, sep, func.args[2].type)
cmaxsplit = _conv_numba_struct_to_clang(builder, maxsplit,
func.args[3].type)
# result is StringVal with an array of StringVals in the buffer
array_as_lowered_struct = builder.call(func,
[cfnctx_arg, cs, csep, cmaxsplit])
array_as_struct = raise_return_type(context, builder, StringVal,
array_as_lowered_struct)
array_as_StringVal = StringValStruct(context,
builder,
value=array_as_struct)
array_as_numba = context.make_array(sig.return_type)(context, builder)
data_ptr = builder.bitcast(array_as_StringVal.ptr,
array_as_numba.data.type)
array_as_numba.data = data_ptr
return array_as_numba._getvalue()
def string_split_2(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context._get_precompiled_function("StringSplitImpl")
func = module.get_or_insert_function(
precomp_func.type.pointee, precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s, sep] = args
maxsplit = context.get_constant_struct(builder, IntVal, -1)
cs = _conv_numba_struct_to_clang(builder, s, func.args[1].type)
csep = _conv_numba_struct_to_clang(builder, sep, func.args[2].type)
cmaxsplit = _conv_numba_struct_to_clang(
builder, maxsplit, func.args[3].type)
# result is StringVal with an array of StringVals in the buffer
array_as_lowered_struct = builder.call(
func, [cfnctx_arg, cs, csep, cmaxsplit])
array_as_struct = raise_return_type(
context, builder, StringVal, array_as_lowered_struct)
array_as_StringVal = StringValStruct(
context, builder, value=array_as_struct)
array_as_numba = context.make_array(sig.return_type)(context, builder)
data_ptr = builder.bitcast(
array_as_StringVal.ptr, array_as_numba.data.type)
array_as_numba.data = data_ptr
return array_as_numba._getvalue()
def return_value(self, builder, retval):
fn = cgutils.get_function(builder)
retptr = self._get_return_argument(fn)
assert retval.type == retptr.type.pointee, \
(str(retval.type), str(retptr.type.pointee))
builder.store(retval, retptr)
self._return_errcode_raw(builder, RETCODE_OK)
def return_value(self, builder, retval):
fn = cgutils.get_function(builder)
retptr = self._get_return_argument(fn)
assert retval.type == retptr.type.pointee, \
(str(retval.type), str(retptr.type.pointee))
builder.store(retval, retptr)
self._return_errcode_raw(builder, RETCODE_OK)
def return_value(self, builder, retval):
fn = cgutils.get_function(builder)
retptr = fn.args[0]
assert retval.type == retptr.type.pointee, \
(str(retval.type), str(retptr.type.pointee))
builder.store(retval, retptr)
builder.ret(RETCODE_OK)
def string_capitalize(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context._get_precompiled_function("StringCapitalizeImpl")
func = module.get_or_insert_function(precomp_func.type.pointee, precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s] = args
cs = _conv_numba_struct_to_clang(builder, s, func.args[1].type)
result = builder.call(func, [cfnctx_arg, cs])
return raise_return_type(context, builder, StringVal, result)
def return_user_exc(self, builder, exc, exc_args=None):
assert (exc is None or issubclass(exc, BaseException)), exc
assert (exc_args is None or isinstance(exc_args, tuple)), exc_args
fn = cgutils.get_function(builder)
pyapi = self.context.get_python_api(builder)
# Build excinfo struct
if exc_args is not None:
exc = (exc, exc_args)
struct_gv = pyapi.serialize_object(exc)
builder.store(struct_gv, self._get_excinfo_argument(fn))
self._return_errcode_raw(builder, RETCODE_USEREXC)
def string_capitalize(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context._get_precompiled_function("StringCapitalizeImpl")
func = module.get_or_insert_function(precomp_func.type.pointee,
precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s] = args
cs = _conv_numba_struct_to_clang(builder, s, func.args[1].type)
result = builder.call(func, [cfnctx_arg, cs])
return raise_return_type(context, builder, StringVal, result)
def add_stringval(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context._get_precompiled_function("AddStringValImpl")
func = module.get_or_insert_function(precomp_func.type.pointee, precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s1, s2] = args
cs1 = _conv_numba_struct_to_clang(builder, s1, func.args[1].type)
cs2 = _conv_numba_struct_to_clang(builder, s2, func.args[2].type)
result = builder.call(func, [cfnctx_arg, cs1, cs2])
return raise_return_type(context, builder, StringVal, result)
def return_user_exc(self, builder, exc, exc_args=None):
assert (exc is None or issubclass(exc, BaseException)), exc
assert (exc_args is None or isinstance(exc_args, tuple)), exc_args
fn = cgutils.get_function(builder)
pyapi = self.context.get_python_api(builder)
# Build excinfo struct
if exc_args is not None:
exc = (exc, exc_args)
struct_gv = pyapi.serialize_object(exc)
builder.store(struct_gv, self._get_excinfo_argument(fn))
self._return_errcode_raw(builder, RETCODE_USEREXC)
def add_stringval(context, builder, sig, args):
module = cgutils.get_module(builder)
precomp_func = context.precompiled_fns["AddStringValImpl"]
func = module.get_or_insert_function(precomp_func.type.pointee,
precomp_func.name)
fnctx_arg = context.get_arguments(cgutils.get_function(builder))[0]
cfnctx_arg = builder.bitcast(fnctx_arg, func.args[0].type)
[s1, s2] = args
cs1 = _conv_numba_struct_to_clang(builder, s1, func.args[1].type)
cs2 = _conv_numba_struct_to_clang(builder, s2, func.args[2].type)
result = builder.call(func, [cfnctx_arg, cs1, cs2])
return _raise_return_type(context, builder, StringVal, result)
def build(self):
module = self.func.module
byte_t = Type.int(8)
byte_ptr_t = Type.pointer(byte_t)
byte_ptr_ptr_t = Type.pointer(byte_ptr_t)
intp_t = self.context.get_value_type(types.intp)
intp_ptr_t = Type.pointer(intp_t)
fnty = Type.function(Type.void(), [byte_ptr_ptr_t, intp_ptr_t,
intp_ptr_t, byte_ptr_t])
wrapper = module.add_function(fnty, "__gufunc__." + self.func.name)
arg_args, arg_dims, arg_steps, arg_data = wrapper.args
arg_args.name = "args"
arg_dims.name = "dims"
arg_steps.name = "steps"
arg_data.name = "data"
builder = Builder.new(wrapper.append_basic_block("entry"))
loopcount = builder.load(arg_dims, name="loopcount")
# Unpack shapes
unique_syms = set()
for grp in (self.sin, self.sout):
for syms in grp:
unique_syms |= set(syms)
sym_map = {}
for syms in self.sin:
for s in syms:
if s not in sym_map:
sym_map[s] = len(sym_map)
sym_dim = {}
for s, i in sym_map.items():
sym_dim[s] = builder.load(builder.gep(arg_dims,
[self.context.get_constant(
types.intp,
i + 1)]))
# Prepare inputs
arrays = []
step_offset = len(self.sin) + len(self.sout)
for i, (typ, sym) in enumerate(zip(self.signature.args,
self.sin + self.sout)):
ary = GUArrayArg(self.context, builder, arg_args, arg_dims,
arg_steps, i, step_offset, typ, sym, sym_dim)
if not ary.as_scalar:
step_offset += ary.ndim
arrays.append(ary)
bbreturn = cgutils.get_function(builder).append_basic_block('.return')
# Prologue
self.gen_prologue(builder)
# Loop
with cgutils.for_range(builder, loopcount, intp=intp_t) as ind:
args = [a.array_value for a in arrays]
innercall, error = self.gen_loop_body(builder, args)
# If error, escape
cgutils.cbranch_or_continue(builder, error, bbreturn)
for a in arrays:
a.next(ind)
builder.branch(bbreturn)
builder.position_at_end(bbreturn)
# Epilogue
self.gen_epilogue(builder)
builder.ret_void()
module.verify()
# Set core function to internal so that it is not generated
self.func.linkage = LINKAGE_INTERNAL
# Force inline of code function
inline_function(innercall)
# Run optimizer
self.context.optimize(module)
if config.DUMP_OPTIMIZED:
print(module)
wrapper.verify()
return wrapper, self.env
def _prepare_call_to_object_mode(context, builder, func, signature, args, env):
mod = cgutils.get_module(builder)
thisfunc = cgutils.get_function(builder)
bb_core_return = thisfunc.append_basic_block('ufunc.core.return')
pyapi = context.get_python_api(builder)
# Call to
# PyObject* ndarray_new(int nd,
# npy_intp *dims, /* shape */
# npy_intp *strides,
# void* data,
# int type_num,
# int itemsize)
ll_int = context.get_value_type(types.int32)
ll_intp = context.get_value_type(types.intp)
ll_intp_ptr = Type.pointer(ll_intp)
ll_voidptr = context.get_value_type(types.voidptr)
ll_pyobj = context.get_value_type(types.pyobject)
fnty = Type.function(
ll_pyobj,
[ll_int, ll_intp_ptr, ll_intp_ptr, ll_voidptr, ll_int, ll_int])
fn_array_new = mod.get_or_insert_function(fnty, name="numba_ndarray_new")
# Convert each llarray into pyobject
error_pointer = cgutils.alloca_once(builder, Type.int(1), name='error')
builder.store(cgutils.true_bit, error_pointer)
ndarray_pointers = []
ndarray_objects = []
for i, (arr, arrtype) in enumerate(zip(args, signature.args)):
ptr = cgutils.alloca_once(builder, ll_pyobj)
ndarray_pointers.append(ptr)
builder.store(Constant.null(ll_pyobj), ptr) # initialize to NULL
arycls = context.make_array(arrtype)
array = arycls(context, builder, ref=arr)
zero = Constant.int(ll_int, 0)
# Extract members of the llarray
nd = Constant.int(ll_int, arrtype.ndim)
dims = builder.gep(array._get_ptr_by_name('shape'), [zero, zero])
strides = builder.gep(array._get_ptr_by_name('strides'), [zero, zero])
data = builder.bitcast(array.data, ll_voidptr)
dtype = np.dtype(str(arrtype.dtype))
# Prepare other info for reconstruction of the PyArray
type_num = Constant.int(ll_int, dtype.num)
itemsize = Constant.int(ll_int, dtype.itemsize)
# Call helper to reconstruct PyArray objects
obj = builder.call(fn_array_new,
[nd, dims, strides, data, type_num, itemsize])
builder.store(obj, ptr)
ndarray_objects.append(obj)
obj_is_null = cgutils.is_null(builder, obj)
builder.store(obj_is_null, error_pointer)
cgutils.cbranch_or_continue(builder, obj_is_null, bb_core_return)
# Call ufunc core function
object_sig = [types.pyobject] * len(ndarray_objects)
status, retval = context.call_conv.call_function(builder,
func,
ll_pyobj,
object_sig,
ndarray_objects,
env=env)
builder.store(status.is_error, error_pointer)
# Release returned object
pyapi.decref(retval)
builder.branch(bb_core_return)
# At return block
builder.position_at_end(bb_core_return)
# Release argument object
for ndary_ptr in ndarray_pointers:
pyapi.decref(builder.load(ndary_ptr))
innercall = status.code
return innercall, builder.load(error_pointer)
def return_status_propagate(self, builder, status):
fn = cgutils.get_function(builder)
builder.store(status.excinfoptr, self._get_excinfo_argument(fn))
self._return_errcode_raw(builder, status.code)
def _prepare_call_to_object_mode(context, builder, func, signature, args,
env):
mod = cgutils.get_module(builder)
thisfunc = cgutils.get_function(builder)
bb_core_return = thisfunc.append_basic_block('ufunc.core.return')
pyapi = context.get_python_api(builder)
# Call to
# PyObject* ndarray_new(int nd,
# npy_intp *dims, /* shape */
# npy_intp *strides,
# void* data,
# int type_num,
# int itemsize)
ll_int = context.get_value_type(types.int32)
ll_intp = context.get_value_type(types.intp)
ll_intp_ptr = Type.pointer(ll_intp)
ll_voidptr = context.get_value_type(types.voidptr)
ll_pyobj = context.get_value_type(types.pyobject)
fnty = Type.function(ll_pyobj, [ll_int, ll_intp_ptr,
ll_intp_ptr, ll_voidptr,
ll_int, ll_int])
fn_array_new = mod.get_or_insert_function(fnty, name="numba_ndarray_new")
# Convert each llarray into pyobject
error_pointer = cgutils.alloca_once(builder, Type.int(1), name='error')
builder.store(cgutils.true_bit, error_pointer)
ndarray_pointers = []
ndarray_objects = []
for i, (arr, arrtype) in enumerate(zip(args, signature.args)):
ptr = cgutils.alloca_once(builder, ll_pyobj)
ndarray_pointers.append(ptr)
builder.store(Constant.null(ll_pyobj), ptr) # initialize to NULL
arycls = context.make_array(arrtype)
array = arycls(context, builder, ref=arr)
zero = Constant.int(ll_int, 0)
# Extract members of the llarray
nd = Constant.int(ll_int, arrtype.ndim)
dims = builder.gep(array._get_ptr_by_name('shape'), [zero, zero])
strides = builder.gep(array._get_ptr_by_name('strides'), [zero, zero])
data = builder.bitcast(array.data, ll_voidptr)
dtype = np.dtype(str(arrtype.dtype))
# Prepare other info for reconstruction of the PyArray
type_num = Constant.int(ll_int, dtype.num)
itemsize = Constant.int(ll_int, dtype.itemsize)
# Call helper to reconstruct PyArray objects
obj = builder.call(fn_array_new, [nd, dims, strides, data,
type_num, itemsize])
builder.store(obj, ptr)
ndarray_objects.append(obj)
obj_is_null = cgutils.is_null(builder, obj)
builder.store(obj_is_null, error_pointer)
cgutils.cbranch_or_continue(builder, obj_is_null, bb_core_return)
# Call ufunc core function
object_sig = [types.pyobject] * len(ndarray_objects)
status, retval = context.call_function(builder, func, ll_pyobj, object_sig,
ndarray_objects, env=env)
builder.store(status.err, error_pointer)
# Release returned object
pyapi.decref(retval)
builder.branch(bb_core_return)
# At return block
builder.position_at_end(bb_core_return)
# Release argument object
for ndary_ptr in ndarray_pointers:
pyapi.decref(builder.load(ndary_ptr))
innercall = status.code
return innercall, builder.load(error_pointer)
def return_status_propagate(self, builder, status):
fn = cgutils.get_function(builder)
builder.store(status.excinfoptr, self._get_excinfo_argument(fn))
self._return_errcode_raw(builder, status.code)
def build(self):
byte_t = Type.int(8)
byte_ptr_t = Type.pointer(byte_t)
byte_ptr_ptr_t = Type.pointer(byte_ptr_t)
intp_t = self.context.get_value_type(types.intp)
intp_ptr_t = Type.pointer(intp_t)
fnty = Type.function(
Type.void(), [byte_ptr_ptr_t, intp_ptr_t, intp_ptr_t, byte_ptr_t])
wrapper_module = self.library.create_ir_module('')
func_type = self.call_conv.get_function_type(self.fndesc.restype,
self.fndesc.argtypes)
func = wrapper_module.add_function(func_type, name=self.func.name)
func.attributes.add("alwaysinline")
wrapper = wrapper_module.add_function(fnty,
"__gufunc__." + self.func.name)
arg_args, arg_dims, arg_steps, arg_data = wrapper.args
arg_args.name = "args"
arg_dims.name = "dims"
arg_steps.name = "steps"
arg_data.name = "data"
builder = Builder.new(wrapper.append_basic_block("entry"))
loopcount = builder.load(arg_dims, name="loopcount")
# Unpack shapes
unique_syms = set()
for grp in (self.sin, self.sout):
for syms in grp:
unique_syms |= set(syms)
sym_map = {}
for syms in self.sin:
for s in syms:
if s not in sym_map:
sym_map[s] = len(sym_map)
sym_dim = {}
for s, i in sym_map.items():
sym_dim[s] = builder.load(
builder.gep(arg_dims,
[self.context.get_constant(types.intp, i + 1)]))
# Prepare inputs
arrays = []
step_offset = len(self.sin) + len(self.sout)
for i, (typ, sym) in enumerate(
zip(self.signature.args, self.sin + self.sout)):
ary = GUArrayArg(self.context, builder, arg_args, arg_dims,
arg_steps, i, step_offset, typ, sym, sym_dim)
if not ary.as_scalar:
step_offset += ary.ndim
arrays.append(ary)
bbreturn = cgutils.get_function(builder).append_basic_block('.return')
# Prologue
self.gen_prologue(builder)
# Loop
with cgutils.for_range(builder, loopcount, intp=intp_t) as ind:
args = [a.array_value for a in arrays]
innercall, error = self.gen_loop_body(builder, func, args)
# If error, escape
cgutils.cbranch_or_continue(builder, error, bbreturn)
for a in arrays:
a.next(ind)
builder.branch(bbreturn)
builder.position_at_end(bbreturn)
# Epilogue
self.gen_epilogue(builder)
builder.ret_void()
self.library.add_ir_module(wrapper_module)
wrapper = self.library.get_function(wrapper.name)
# Set core function to internal so that it is not generated
self.func.linkage = LINKAGE_INTERNAL
return wrapper, self.env