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Implement ndarray class, constructor and creation functions #371

Merged
sb10q merged 9 commits from enhance/issue-149-ndarray into master 2023-12-22 17:11:28 +08:00
Conversation 1 Commits 9 Files Changed 25
25 changed files with 2166 additions and 224 deletions
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11
nac3artiq/src/codegen.rs
View File

@ -400,6 +400,9 @@ fn gen_rpc_tag(
buffer.push(b'l');
gen_rpc_tag(ctx, *ty, buffer)?;
}
TNDArray { .. } => {
todo!()
}
_ => return Err(format!("Unsupported type: {:?}", ctx.unifier.stringify(ty))),
}
}
@ -673,6 +676,14 @@ pub fn attributes_writeback(
values.push((ty, inner_resolver.get_obj_value(py, val, ctx, generator, ty)?.unwrap()));
}
},
TypeEnum::TNDArray { ty: elem_ty, .. } => {
if gen_rpc_tag(ctx, *elem_ty, &mut scratch_buffer).is_ok() {
let pydict = PyDict::new(py);
pydict.set_item("obj", val)?;
host_attributes.append(pydict)?;
values.push((ty, inner_resolver.get_obj_value(py, val, ctx, generator, ty)?.unwrap()));
}
},
_ => {}
}
}

17
nac3artiq/src/lib.rs
View File

@ -63,6 +63,17 @@ enum Isa {
CortexA9,
}
impl Isa {
/// Returns the number of bits in `size_t` for the [`Isa`].
fn get_size_type(&self) -> u32 {
if self == &Isa::Host {
64u32
} else {
32u32
}
}
}
#[derive(Clone)]
pub struct PrimitivePythonId {
int: u64,
@ -74,6 +85,7 @@ pub struct PrimitivePythonId {
float64: u64,
bool: u64,
list: u64,
ndarray: u64,
tuple: u64,
typevar: u64,
const_generic_marker: u64,
@ -277,9 +289,11 @@ impl Nac3 {
py: Python,
link_fn: &dyn Fn(&Module) -> PyResult<T>,
) -> PyResult<T> {
let size_t = self.isa.get_size_type();
let (mut composer, mut builtins_def, mut builtins_ty) = TopLevelComposer::new(
self.builtins.clone(),
ComposerConfig { kernel_ann: Some("Kernel"), kernel_invariant_ann: "KernelInvariant" },
size_t,
);
let builtins = PyModule::import(py, "builtins")?;
@ -792,7 +806,7 @@ impl Nac3 {
Isa::RiscV32IMA => &timeline::NOW_PINNING_TIME_FNS,
Isa::CortexA9 | Isa::Host => &timeline::EXTERN_TIME_FNS,
};
let primitive: PrimitiveStore = TopLevelComposer::make_primitives().0;
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(isa.get_size_type()).0;
let builtins = vec![
(
"now_mu".into(),
@ -866,6 +880,7 @@ impl Nac3 {
float: get_attr_id(builtins_mod, "float"),
float64: get_attr_id(numpy_mod, "float64"),
list: get_attr_id(builtins_mod, "list"),
ndarray: get_attr_id(numpy_mod, "NDArray"),
tuple: get_attr_id(builtins_mod, "tuple"),
exception: get_attr_id(builtins_mod, "Exception"),
option: get_id(artiq_builtins.get_item("Option").ok().flatten().unwrap()),

44
nac3artiq/src/symbol_resolver.rs
View File

@ -302,6 +302,12 @@ impl InnerResolver {
let var = unifier.get_dummy_var().0;
let list = unifier.add_ty(TypeEnum::TList { ty: var });
Ok(Ok((list, false)))
} else if ty_id == self.primitive_ids.ndarray {
// do not handle type var param and concrete check here
let var = unifier.get_dummy_var().0;
let ndims = unifier.get_fresh_const_generic_var(primitives.usize(), None, None).0;
let ndarray = unifier.add_ty(TypeEnum::TNDArray { ty: var, ndims });
Ok(Ok((ndarray, false)))
} else if ty_id == self.primitive_ids.tuple {
// do not handle type var param and concrete check here
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![] }), false)))
@ -446,6 +452,16 @@ impl InnerResolver {
)));
}
}
TypeEnum::TNDArray { .. } => {
if args.len() != 2 {
return Ok(Err(format!(
"type list needs exactly 2 type parameters, found {}",
args.len()
)));
}
todo!()
}
TypeEnum::TTuple { .. } => {
let args = match args
.iter()
@ -607,7 +623,7 @@ impl InnerResolver {
Err(e) => return Ok(Err(e)),
};
match (&*unifier.get_ty(extracted_ty), inst_check) {
// do the instantiation for these three types
// do the instantiation for these four types
(TypeEnum::TList { ty }, false) => {
let len: usize = self.helper.len_fn.call1(py, (obj,))?.extract(py)?;
if len == 0 {
@ -632,6 +648,30 @@ impl InnerResolver {
}
}
}
(TypeEnum::TNDArray { ty, ndims }, false) => {
let len: usize = self.helper.len_fn.call1(py, (obj,))?.extract(py)?;
if len == 0 {
assert!(matches!(
&*unifier.get_ty(*ty),
TypeEnum::TVar { fields: None, range, .. }
if range.is_empty()
));
Ok(Ok(extracted_ty))
} else {
let actual_ty =
self.get_list_elem_type(py, obj, len, unifier, defs, primitives)?;
match actual_ty {
Ok(t) => match unifier.unify(*ty, t) {
Ok(_) => Ok(Ok(unifier.add_ty(TypeEnum::TNDArray { ty: *ty, ndims: *ndims }))),
Err(e) => Ok(Err(format!(
"type error ({}) for the ndarray",
e.to_display(unifier).to_string()
))),
},
Err(e) => Ok(Err(e)),
}
}
}
(TypeEnum::TTuple { .. }, false) => {
let elements: &PyTuple = obj.downcast()?;
let types: Result<Result<Vec<_>, _>, _> = elements
@ -898,6 +938,8 @@ impl InnerResolver {
global.set_initializer(&val);
Ok(Some(global.as_pointer_value().into()))
} else if ty_id == self.primitive_ids.ndarray {
todo!()
} else if ty_id == self.primitive_ids.tuple {
let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
let TypeEnum::TTuple { ty } = expected_ty_enum.as_ref() else {

1
nac3core/build.rs
View File

@ -17,6 +17,7 @@ fn main() {
const FLAG: &[&str] = &[
"--target=wasm32",
FILE,
"-fno-discard-value-names",
"-O3",
"-emit-llvm",
"-S",

14
nac3core/src/codegen/concrete_type.rs
View File

@ -47,6 +47,10 @@ pub enum ConcreteTypeEnum {
TList {
ty: ConcreteType,
},
TNDArray {
ty: ConcreteType,
ndims: ConcreteType,
},
TObj {
obj_id: DefinitionId,
fields: HashMap<StrRef, (ConcreteType, bool)>,
@ -167,6 +171,10 @@ impl ConcreteTypeStore {
TypeEnum::TList { ty } => ConcreteTypeEnum::TList {
ty: self.from_unifier_type(unifier, primitives, *ty, cache),
},
TypeEnum::TNDArray { ty, ndims } => ConcreteTypeEnum::TNDArray {
ty: self.from_unifier_type(unifier, primitives, *ty, cache),
ndims: self.from_unifier_type(unifier, primitives, *ndims, cache),
},
TypeEnum::TObj { obj_id, fields, params } => ConcreteTypeEnum::TObj {
obj_id: *obj_id,
fields: fields
@ -260,6 +268,12 @@ impl ConcreteTypeStore {
ConcreteTypeEnum::TList { ty } => {
TypeEnum::TList { ty: self.to_unifier_type(unifier, primitives, *ty, cache) }
}
ConcreteTypeEnum::TNDArray { ty, ndims } => {
TypeEnum::TNDArray {
ty: self.to_unifier_type(unifier, primitives, *ty, cache),
ndims: self.to_unifier_type(unifier, primitives, *ndims, cache),
}
}
ConcreteTypeEnum::TVirtual { ty } => {
TypeEnum::TVirtual { ty: self.to_unifier_type(unifier, primitives, *ty, cache) }
}

3
nac3core/src/codegen/expr.rs
View File

@ -1846,6 +1846,9 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
ctx.build_gep_and_load(arr_ptr, &[index], None).into()
}
}
TypeEnum::TNDArray { .. } => {
return Err(String::from("subscript operator for ndarray not implemented"))
}
TypeEnum::TTuple { .. } => {
let index: u32 =
if let ExprKind::Constant { value: Constant::Int(v), .. } = &slice.node {

12
nac3core/src/codegen/generator.rs
View File

@ -92,6 +92,18 @@ pub trait CodeGenerator {
gen_var(ctx, ty, name)
}
/// Allocate memory for a variable and return a pointer pointing to it.
/// The default implementation places the allocations at the start of the function.
fn gen_array_var_alloc<'ctx, 'a>(
&mut self,
ctx: &mut CodeGenContext<'ctx, 'a>,
ty: BasicTypeEnum<'ctx>,
size: IntValue<'ctx>,
name: Option<&str>,
) -> Result<PointerValue<'ctx>, String> {
gen_array_var(ctx, ty, size, name)
}
/// Return a pointer pointing to the target of the expression.
fn gen_store_target<'ctx>(
&mut self,

72
nac3core/src/codegen/irrt/irrt.c
View File

@ -196,4 +196,76 @@ double __nac3_j0(double x) {
}
return j0(x);
}
uint32_t __nac3_ndarray_calc_size(
const uint64_t *list_data,
uint32_t list_len
) {
uint32_t num_elems = 1;
for (uint32_t i = 0; i < list_len; ++i) {
uint64_t val = list_data[i];
__builtin_assume(val >= 0);
num_elems *= list_data[i];
}
return num_elems;
}
uint64_t __nac3_ndarray_calc_size64(
const uint64_t *list_data,
uint64_t list_len
) {
uint64_t num_elems = 1;
for (uint64_t i = 0; i < list_len; ++i) {
uint64_t val = list_data[i];
__builtin_assume(val >= 0);
num_elems *= list_data[i];
}
return num_elems;
}
void __nac3_ndarray_init_dims(
uint32_t *ndarray_dims,
const int32_t *shape_data,
uint32_t shape_len
) {
__builtin_memcpy(ndarray_dims, shape_data, shape_len * sizeof(int32_t));
}
void __nac3_ndarray_init_dims64(
uint64_t *ndarray_dims,
const int32_t *shape_data,
uint64_t shape_len
) {
for (uint64_t i = 0; i < shape_len; ++i) {
ndarray_dims[i] = (uint64_t) shape_data[i];
}
}
void __nac3_ndarray_calc_nd_indices(
uint32_t index,
const uint32_t* dims,
uint32_t num_dims,
uint32_t* idxs
) {
uint32_t stride = 1;
for (uint32_t dim = 0; dim < num_dims; dim++) {
uint32_t i = num_dims - dim - 1;
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
void __nac3_ndarray_calc_nd_indices64(
uint64_t index,
const uint64_t* dims,
uint64_t num_dims,
uint64_t* idxs
) {
uint64_t stride = 1;
for (uint64_t dim = 0; dim < num_dims; dim++) {
uint64_t i = num_dims - dim - 1;
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}

180
nac3core/src/codegen/irrt/mod.rs
View File

@ -1,6 +1,6 @@
use crate::typecheck::typedef::Type;
use super::{CodeGenContext, CodeGenerator};
use super::{assert_is_list, assert_is_ndarray, CodeGenContext, CodeGenerator};
use inkwell::{
attributes::{Attribute, AttributeLoc},
context::Context,
@ -546,3 +546,181 @@ pub fn call_j0<'ctx>(
.unwrap_left()
.into_float_value()
}
/// Generates a call to `__nac3_ndarray_calc_size`. Returns an [IntValue] representing the
/// calculated total size.
///
/// * `num_dims` - An [IntValue] containing the number of dimensions.
/// * `dims` - A [PointerValue] to an array containing the size of each dimensions.
pub fn call_ndarray_calc_size<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
num_dims: IntValue<'ctx>,
dims: PointerValue<'ctx>,
) -> IntValue<'ctx> {
let llvm_i64 = ctx.ctx.i64_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi64 = llvm_i64.ptr_type(AddressSpace::default());
let ndarray_calc_size_fn_name = match generator.get_size_type(ctx.ctx).get_bit_width() {
32 => "__nac3_ndarray_calc_size",
64 => "__nac3_ndarray_calc_size64",
bw => unreachable!("Unsupported size type bit width: {}", bw)
};
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
&[
llvm_pi64.into(),
llvm_usize.into(),
],
false,
);
let ndarray_calc_size_fn = ctx.module.get_function(ndarray_calc_size_fn_name)
.unwrap_or_else(|| {
ctx.module.add_function(ndarray_calc_size_fn_name, ndarray_calc_size_fn_t, None)
});
ctx.builder
.build_call(
ndarray_calc_size_fn,
&[
dims.into(),
num_dims.into(),
],
"",
)
.try_as_basic_value()
.unwrap_left()
.into_int_value()
}
/// Generates a call to `__nac3_ndarray_init_dims`.
///
/// * `ndarray` - LLVM pointer to the NDArray. This value must be the LLVM representation of an
/// `NDArray`.
/// * `shape` - LLVM pointer to the `shape` of the NDArray. This value must be the LLVM
/// representation of a `list`.
pub fn call_ndarray_init_dims<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
ndarray: PointerValue<'ctx>,
shape: PointerValue<'ctx>,
) {
assert_is_ndarray(ndarray);
assert_is_list(shape);
let llvm_void = ctx.ctx.void_type();
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi32 = llvm_i32.ptr_type(AddressSpace::default());
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_init_dims_fn_name = match generator.get_size_type(ctx.ctx).get_bit_width() {
32 => "__nac3_ndarray_init_dims",
64 => "__nac3_ndarray_init_dims64",
bw => unreachable!("Unsupported size type bit width: {}", bw)
};
let ndarray_init_dims_fn = ctx.module.get_function(ndarray_init_dims_fn_name).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[
llvm_pusize.into(),
llvm_pi32.into(),
llvm_usize.into(),
],
false,
);
ctx.module.add_function(ndarray_init_dims_fn_name, fn_type, None)
});
let ndarray_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
None,
);
let shape_data = ctx.build_gep_and_load(
shape,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None
);
let ndarray_num_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None,
).into_int_value();
ctx.builder.build_call(
ndarray_init_dims_fn,
&[
ndarray_dims.into(),
shape_data.into(),
ndarray_num_dims.into(),
],
"",
);
}
pub fn call_ndarray_calc_nd_indices<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
index: IntValue<'ctx>,
ndarray: PointerValue<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
assert_is_ndarray(ndarray);
let llvm_void = ctx.ctx.void_type();
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pusize = llvm_usize.ptr_type(AddressSpace::default());
let ndarray_calc_nd_indices_dn_name = match generator.get_size_type(ctx.ctx).get_bit_width() {
32 => "__nac3_ndarray_calc_nd_indices",
64 => "__nac3_ndarray_calc_nd_indices64",
bw => unreachable!("Unsupported size type bit width: {}", bw)
};
let ndarray_calc_nd_indices_fn = ctx.module.get_function(ndarray_calc_nd_indices_dn_name).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[
llvm_usize.into(),
llvm_pusize.into(),
llvm_usize.into(),
llvm_pusize.into(),
],
false,
);
ctx.module.add_function(ndarray_calc_nd_indices_dn_name, fn_type, None)
});
let ndarray_num_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None,
).into_int_value();
let ndarray_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
None,
).into_pointer_value();
let indices = ctx.builder.build_array_alloca(
llvm_usize,
ndarray_num_dims,
"",
);
ctx.builder.build_call(
ndarray_calc_nd_indices_fn,
&[
index.into(),
ndarray_dims.into(),
ndarray_num_dims.into(),
indices.into(),
],
"",
);
Ok(indices)
}

64
nac3core/src/codegen/mod.rs
View File

@ -34,6 +34,9 @@ use std::sync::{
};
use std::thread;
#[cfg(debug_assertions)]
use inkwell::types::AnyTypeEnum;
pub mod concrete_type;
pub mod expr;
mod generator;
@ -236,7 +239,7 @@ pub struct WorkerRegistry {
static_value_store: Arc<Mutex<StaticValueStore>>,
/// LLVM-related options for code generation.
llvm_options: CodeGenLLVMOptions,
pub llvm_options: CodeGenLLVMOptions,
}
impl WorkerRegistry {
@ -507,6 +510,24 @@ fn get_llvm_type<'ctx>(
];
ctx.struct_type(&fields, false).ptr_type(AddressSpace::default()).into()
}
TNDArray { ty, .. } => {
let llvm_usize = generator.get_size_type(ctx);
let element_type = get_llvm_type(
ctx, module, generator, unifier, top_level, type_cache, primitives, *ty,
);
// struct NDArray { num_dims: size_t, dims: size_t*, data: T* }
//
// * num_dims: Number of dimensions in the array
// * dims: Pointer to an array containing the size of each dimension
// * data: Pointer to an array containing the array data
let fields = [
llvm_usize.into(),
llvm_usize.ptr_type(AddressSpace::default()).into(),
element_type.ptr_type(AddressSpace::default()).into(),
];
ctx.struct_type(&fields, false).ptr_type(AddressSpace::default()).into()
}
TVirtual { .. } => unimplemented!(),
_ => unreachable!("{}", ty_enum.get_type_name()),
};
@ -614,6 +635,7 @@ pub fn gen_func_impl<'ctx, G: CodeGenerator, F: FnOnce(&mut G, &mut CodeGenConte
str: unifier.get_representative(primitives.str),
exception: unifier.get_representative(primitives.exception),
option: unifier.get_representative(primitives.option),
..primitives
};
let mut type_cache: HashMap<_, _> = [
@ -976,3 +998,43 @@ fn gen_in_range_check<'ctx>(
ctx.builder.build_int_compare(IntPredicate::SLT, lo, hi, "cmp")
}
/// Checks whether the pointer `value` refers to a `list` in LLVM.
fn assert_is_list(value: PointerValue) -> PointerValue {
#[cfg(debug_assertions)]
{
let llvm_shape_ty = value.get_type().get_element_type();
let AnyTypeEnum::StructType(llvm_shape_ty) = llvm_shape_ty else {
panic!("Expected struct type for `list` type, but got {llvm_shape_ty}")
};
assert_eq!(llvm_shape_ty.count_fields(), 2);
assert!(matches!(llvm_shape_ty.get_field_type_at_index(0), Some(BasicTypeEnum::PointerType(..))));
assert!(matches!(llvm_shape_ty.get_field_type_at_index(1), Some(BasicTypeEnum::IntType(..))));
}
value
}
/// Checks whether the pointer `value` refers to an `NDArray` in LLVM.
fn assert_is_ndarray(value: PointerValue) -> PointerValue {
#[cfg(debug_assertions)]
{
let llvm_ndarray_ty = value.get_type().get_element_type();
let AnyTypeEnum::StructType(llvm_ndarray_ty) = llvm_ndarray_ty else {
panic!("Expected struct type for `NDArray` type, but got {llvm_ndarray_ty}")
};
assert_eq!(llvm_ndarray_ty.count_fields(), 3);
assert!(matches!(llvm_ndarray_ty.get_field_type_at_index(0), Some(BasicTypeEnum::IntType(..))));
let Some(ndarray_dims) = llvm_ndarray_ty.get_field_type_at_index(1) else {
unreachable!()
};
let BasicTypeEnum::PointerType(dims) = ndarray_dims else {
panic!("Expected pointer type for `list.1`, but got {ndarray_dims}")
};
assert!(matches!(dims.get_element_type(), AnyTypeEnum::IntType(..)));
assert!(matches!(llvm_ndarray_ty.get_field_type_at_index(2), Some(BasicTypeEnum::PointerType(..))));
}
value
}

231
nac3core/src/codegen/stmt.rs
View File

@ -15,8 +15,8 @@ use crate::{
use inkwell::{
attributes::{Attribute, AttributeLoc},
basic_block::BasicBlock,
types::BasicTypeEnum,
values::{BasicValue, BasicValueEnum, FunctionValue, PointerValue},
types::{BasicType, BasicTypeEnum},
values::{BasicValue, BasicValueEnum, FunctionValue, IntValue, PointerValue},
IntPredicate,
};
use nac3parser::ast::{
@ -54,6 +54,37 @@ pub fn gen_var<'ctx>(
Ok(ptr)
}
/// See [CodeGenerator::gen_array_var_alloc].
pub fn gen_array_var<'ctx, 'a, T: BasicType<'ctx>>(
ctx: &mut CodeGenContext<'ctx, 'a>,
ty: T,
size: IntValue<'ctx>,
name: Option<&str>,
) -> Result<PointerValue<'ctx>, String> {
// Restore debug location
let di_loc = ctx.debug_info.0.create_debug_location(
ctx.ctx,
ctx.current_loc.row as u32,
ctx.current_loc.column as u32,
ctx.debug_info.2,
None,
);
// put the alloca in init block
let current = ctx.builder.get_insert_block().unwrap();
// position before the last branching instruction...
ctx.builder.position_before(&ctx.init_bb.get_last_instruction().unwrap());
ctx.builder.set_current_debug_location(di_loc);
let ptr = ctx.builder.build_array_alloca(ty, size, name.unwrap_or(""));
ctx.builder.position_at_end(current);
ctx.builder.set_current_debug_location(di_loc);
Ok(ptr)
}
/// See [`CodeGenerator::gen_store_target`].
pub fn gen_store_target<'ctx, G: CodeGenerator>(
generator: &mut G,
@ -99,63 +130,69 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
}
}
ExprKind::Subscript { value, slice, .. } => {
assert!(matches!(
ctx.unifier.get_ty_immutable(value.custom.unwrap()).as_ref(),
TypeEnum::TList { .. },
));
let i32_type = ctx.ctx.i32_type();
let zero = i32_type.const_zero();
let v = if let Some(v) = generator.gen_expr(ctx, value)? {
v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?.into_pointer_value()
} else {
return Ok(None)
};
let len = ctx
.build_gep_and_load(v, &[zero, i32_type.const_int(1, false)], Some("len"))
.into_int_value();
let raw_index = if let Some(v) = generator.gen_expr(ctx, slice)? {
v.to_basic_value_enum(ctx, generator, slice.custom.unwrap())?.into_int_value()
} else {
return Ok(None)
};
let raw_index = ctx.builder.build_int_s_extend(
raw_index,
generator.get_size_type(ctx.ctx),
"sext",
);
// handle negative index
let is_negative = ctx.builder.build_int_compare(
IntPredicate::SLT,
raw_index,
generator.get_size_type(ctx.ctx).const_zero(),
"is_neg",
);
let adjusted = ctx.builder.build_int_add(raw_index, len, "adjusted");
let index = ctx
.builder
.build_select(is_negative, adjusted, raw_index, "index")
.into_int_value();
// unsigned less than is enough, because negative index after adjustment is
// bigger than the length (for unsigned cmp)
let bound_check = ctx.builder.build_int_compare(
IntPredicate::ULT,
index,
len,
"inbound",
);
ctx.make_assert(
generator,
bound_check,
"0:IndexError",
"index {0} out of bounds 0:{1}",
[Some(raw_index), Some(len), None],
slice.location,
);
unsafe {
let arr_ptr = ctx
.build_gep_and_load(v, &[i32_type.const_zero(), i32_type.const_zero()], Some("arr.addr"))
.into_pointer_value();
ctx.builder.build_gep(arr_ptr, &[index], name.unwrap_or(""))
match ctx.unifier.get_ty_immutable(value.custom.unwrap()).as_ref() {
TypeEnum::TList { .. } => {
let i32_type = ctx.ctx.i32_type();
let zero = i32_type.const_zero();
let v = generator
.gen_expr(ctx, value)?
.unwrap()
.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
.into_pointer_value();
let len = ctx
.build_gep_and_load(v, &[zero, i32_type.const_int(1, false)], Some("len"))
.into_int_value();
let raw_index = generator
.gen_expr(ctx, slice)?
.unwrap()
.to_basic_value_enum(ctx, generator, slice.custom.unwrap())?
.into_int_value();
let raw_index = ctx.builder.build_int_s_extend(
raw_index,
generator.get_size_type(ctx.ctx),
"sext",
);
// handle negative index
let is_negative = ctx.builder.build_int_compare(
IntPredicate::SLT,
raw_index,
generator.get_size_type(ctx.ctx).const_zero(),
"is_neg",
);
let adjusted = ctx.builder.build_int_add(raw_index, len, "adjusted");
let index = ctx
.builder
.build_select(is_negative, adjusted, raw_index, "index")
.into_int_value();
// unsigned less than is enough, because negative index after adjustment is
// bigger than the length (for unsigned cmp)
let bound_check = ctx.builder.build_int_compare(
IntPredicate::ULT,
index,
len,
"inbound",
);
ctx.make_assert(
generator,
bound_check,
"0:IndexError",
"index {0} out of bounds 0:{1}",
[Some(raw_index), Some(len), None],
slice.location,
);
unsafe {
let arr_ptr = ctx
.build_gep_and_load(v, &[i32_type.const_zero(), i32_type.const_zero()], Some("arr.addr"))
.into_pointer_value();
ctx.builder.build_gep(arr_ptr, &[index], name.unwrap_or(""))
}
}
TypeEnum::TNDArray { .. } => {
todo!()
}
_ => unreachable!(),
}
}
_ => unreachable!(),
@ -203,7 +240,7 @@ pub fn gen_assign<'ctx, G: CodeGenerator>(
let value = value
.to_basic_value_enum(ctx, generator, target.custom.unwrap())?
.into_pointer_value();
let TypeEnum::TList { ty } = &*ctx.unifier.get_ty(target.custom.unwrap()) else {
let (TypeEnum::TList { ty } | TypeEnum::TNDArray { ty, .. }) = &*ctx.unifier.get_ty(target.custom.unwrap()) else {
unreachable!()
};
@ -399,6 +436,80 @@ pub fn gen_for<G: CodeGenerator>(
Ok(())
}
/// Generates a C-style `for` construct using lambdas, similar to the following C code:
///
/// ```c
/// for (x... = init(); cond(x...); update(x...)) {
/// body(x...);
/// }
/// ```
///
/// * `init` - A lambda containing IR statements declaring and initializing loop variables. The
/// return value is a [Clone] value which will be passed to the other lambdas.
/// * `cond` - A lambda containing IR statements checking whether the loop should continue
/// executing. The result value must be an `i1` indicating if the loop should continue.
/// * `body` - A lambda containing IR statements within the loop body.
/// * `update` - A lambda containing IR statements updating loop variables.
pub fn gen_for_callback<'ctx, 'a, I, InitFn, CondFn, BodyFn, UpdateFn>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
init: InitFn,
cond: CondFn,
body: BodyFn,
update: UpdateFn,
) -> Result<(), String>
where
I: Clone,
InitFn: FnOnce(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>) -> Result<I, String>,
CondFn: FnOnce(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>, I) -> Result<IntValue<'ctx>, String>,
BodyFn: FnOnce(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>, I) -> Result<(), String>,
UpdateFn: FnOnce(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>, I) -> Result<(), String>,
{
let current = ctx.builder.get_insert_block().and_then(|bb| bb.get_parent()).unwrap();
let init_bb = ctx.ctx.append_basic_block(current, "for.init");
// The BB containing the loop condition check
let cond_bb = ctx.ctx.append_basic_block(current, "for.cond");
let body_bb = ctx.ctx.append_basic_block(current, "for.body");
// The BB containing the increment expression
let update_bb = ctx.ctx.append_basic_block(current, "for.update");
let cont_bb = ctx.ctx.append_basic_block(current, "for.end");
// store loop bb information and restore it later
let loop_bb = ctx.loop_target.replace((update_bb, cont_bb));
ctx.builder.build_unconditional_branch(init_bb);
let loop_var = {
ctx.builder.position_at_end(init_bb);
let result = init(generator, ctx)?;
ctx.builder.build_unconditional_branch(cond_bb);
result
};
ctx.builder.position_at_end(cond_bb);
let cond = cond(generator, ctx, loop_var.clone())?;
assert_eq!(cond.get_type().get_bit_width(), ctx.ctx.bool_type().get_bit_width());
ctx.builder.build_conditional_branch(
cond,
body_bb,
cont_bb
);
ctx.builder.position_at_end(body_bb);
body(generator, ctx, loop_var.clone())?;
ctx.builder.build_unconditional_branch(update_bb);
ctx.builder.position_at_end(update_bb);
update(generator, ctx, loop_var)?;
ctx.builder.build_unconditional_branch(cond_bb);
ctx.builder.position_at_end(cont_bb);
ctx.loop_target = loop_bb;
Ok(())
}
/// See [`CodeGenerator::gen_while`].
pub fn gen_while<G: CodeGenerator>(
generator: &mut G,

29
nac3core/src/symbol_resolver.rs
View File

@ -354,13 +354,14 @@ pub trait SymbolResolver {
}
thread_local! {
static IDENTIFIER_ID: [StrRef; 11] = [
static IDENTIFIER_ID: [StrRef; 12] = [
"int32".into(),
"int64".into(),
"float".into(),
"bool".into(),
"virtual".into(),
"list".into(),
"ndarray".into(),
"tuple".into(),
"str".into(),
"Exception".into(),
@ -385,11 +386,12 @@ pub fn parse_type_annotation<T>(
let bool_id = ids[3];
let virtual_id = ids[4];
let list_id = ids[5];
let tuple_id = ids[6];
let str_id = ids[7];
let exn_id = ids[8];
let uint32_id = ids[9];
let uint64_id = ids[10];
let ndarray_id = ids[6];
let tuple_id = ids[7];
let str_id = ids[8];
let exn_id = ids[9];
let uint32_id = ids[10];
let uint64_id = ids[11];
let name_handling = |id: &StrRef, loc: Location, unifier: &mut Unifier| {
if *id == int32_id {
@ -460,6 +462,21 @@ pub fn parse_type_annotation<T>(
} else if *id == list_id {
let ty = parse_type_annotation(resolver, top_level_defs, unifier, primitives, slice)?;
Ok(unifier.add_ty(TypeEnum::TList { ty }))
} else if *id == ndarray_id {
let Tuple { elts, .. } = &slice.node else {
return Err(HashSet::from([
String::from("Expected 2 type arguments for ndarray"),
]))
};
if elts.len() < 2 {
return Err(HashSet::from([
String::from("Expected 2 type arguments for ndarray"),
]))
}
let ty = parse_type_annotation(resolver, top_level_defs, unifier, primitives, &elts[0])?;
let ndims = parse_type_annotation(resolver, top_level_defs, unifier, primitives, &elts[1])?;
Ok(unifier.add_ty(TypeEnum::TNDArray { ty, ndims }))
} else if *id == tuple_id {
if let Tuple { elts, .. } = &slice.node {
let ty = elts

218
nac3core/src/toplevel/builtins.rs
View File

@ -13,14 +13,22 @@ use crate::{
stmt::exn_constructor,
},
symbol_resolver::SymbolValue,
toplevel::numpy::{
gen_ndarray_empty,
gen_ndarray_eye,
gen_ndarray_full,
gen_ndarray_ones,
gen_ndarray_zeros,
},
};
use inkwell::{
attributes::{Attribute, AttributeLoc},
types::{BasicType, BasicMetadataTypeEnum},
values::BasicMetadataValueEnum,
values::{BasicValue, BasicMetadataValueEnum},
FloatPredicate,
IntPredicate
};
use crate::toplevel::numpy::gen_ndarray_identity;
type BuiltinInfo = Vec<(Arc<RwLock<TopLevelDef>>, Option<Stmt>)>;
@ -278,6 +286,31 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
let boolean = primitives.0.bool;
let range = primitives.0.range;
let string = primitives.0.str;
let ndarray = {
let ndarray_ty = TypeEnum::ndarray(&mut primitives.1, None, None, &primitives.0);
primitives.1.add_ty(ndarray_ty)
};
let ndarray_float = {
let ndarray_ty_enum = TypeEnum::ndarray(&mut primitives.1, Some(float), None, &primitives.0);
primitives.1.add_ty(ndarray_ty_enum)
};
let ndarray_float_2d = {
let value = match primitives.0.size_t {
64 => SymbolValue::U64(2u64),
32 => SymbolValue::U32(2u32),
_ => unreachable!(),
};
let ndims = primitives.1.add_ty(TypeEnum::TLiteral {
values: vec![value],
loc: None,
});
primitives.1.add_ty(TypeEnum::TNDArray {
ty: float,
ndims,
})
};
let list_int32 = primitives.1.add_ty(TypeEnum::TList { ty: int32 });
let num_ty = primitives.1.get_fresh_var_with_range(
&[int32, int64, float, boolean, uint32, uint64],
Some("N".into()),
@ -470,6 +503,22 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
)))),
loc: None,
})),
{
let tvar = primitives.1.get_fresh_var(Some("T".into()), None);
let ndims = primitives.1.get_fresh_const_generic_var(primitives.0.uint64, Some("N".into()), None);
Arc::new(RwLock::new(TopLevelDef::Class {
name: "ndarray".into(),
object_id: DefinitionId(14),
type_vars: vec![tvar.0, ndims.0],
fields: Vec::default(),
methods: Vec::default(),
ancestors: Vec::default(),
constructor: None,
resolver: None,
loc: None,
}))
},
Arc::new(RwLock::new(TopLevelDef::Function {
name: "int32".into(),
simple_name: "int32".into(),
@ -821,6 +870,115 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
)))),
loc: None,
})),
create_fn_by_codegen(
primitives,
&var_map,
"np_ndarray",
ndarray_float,
// We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
// type variable
&[(list_int32, "shape")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_empty(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
),
create_fn_by_codegen(
primitives,
&var_map,
"np_empty",
ndarray_float,
// We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
// type variable
&[(list_int32, "shape")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_empty(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
),
create_fn_by_codegen(
primitives,
&var_map,
"np_zeros",
ndarray_float,
// We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
// type variable
&[(list_int32, "shape")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_zeros(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
),
create_fn_by_codegen(
primitives,
&var_map,
"np_ones",
ndarray_float,
// We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
// type variable
&[(list_int32, "shape")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_ones(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
),
{
let tv = primitives.1.get_fresh_var(Some("T".into()), None).0;
create_fn_by_codegen(
primitives,
&var_map,
"np_full",
ndarray,
// We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
// type variable
&[(list_int32, "shape"), (tv, "fill_value")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_full(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
)
},
Arc::new(RwLock::new(TopLevelDef::Function {
name: "np_eye".into(),
simple_name: "np_eye".into(),
signature: primitives.1.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg { name: "N".into(), ty: int32, default_value: None },
// TODO(Derppening): Default values current do not work?
FuncArg {
name: "M".into(),
ty: int32,
default_value: Some(SymbolValue::OptionNone)
},
FuncArg { name: "k".into(), ty: int32, default_value: Some(SymbolValue::I32(0)) },
],
ret: ndarray_float_2d,
vars: var_map.clone(),
})),
var_id: Default::default(),
instance_to_symbol: Default::default(),
instance_to_stmt: Default::default(),
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
gen_ndarray_eye(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
},
)))),
loc: None,
})),
create_fn_by_codegen(
primitives,
&var_map,
"np_identity",
ndarray_float_2d,
&[(int32, "n")],
Box::new(|ctx, obj, fun, args, generator| {
gen_ndarray_identity(ctx, obj, fun, args, generator)
.map(|val| Some(val.as_basic_value_enum()))
}),
),
create_fn_by_codegen(
primitives,
&var_map,
@ -1265,10 +1423,13 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
}),
),
Arc::new(RwLock::new({
let list_var = primitives.1.get_fresh_var(Some("L".into()), None);
let list = primitives.1.add_ty(TypeEnum::TList { ty: list_var.0 });
let tvar = primitives.1.get_fresh_var(Some("L".into()), None);
let list = primitives.1.add_ty(TypeEnum::TList { ty: tvar.0 });
let ndims = primitives.1.get_fresh_const_generic_var(primitives.0.uint64, Some("N".into()), None);
let ndarray = primitives.1.add_ty(TypeEnum::TNDArray { ty: tvar.0, ndims: ndims.0 });
let arg_ty = primitives.1.get_fresh_var_with_range(
&[list, primitives.0.range],
&[list, ndarray, primitives.0.range],
Some("I".into()),
None,
);
@ -1278,7 +1439,7 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
signature: primitives.1.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg { name: "ls".into(), ty: arg_ty.0, default_value: None }],
ret: int32,
vars: vec![(list_var.1, list_var.0), (arg_ty.1, arg_ty.0)]
vars: vec![(tvar.1, tvar.0), (arg_ty.1, arg_ty.0)]
.into_iter()
.collect(),
})),
@ -1296,19 +1457,40 @@ pub fn get_builtins(primitives: &mut (PrimitiveStore, Unifier)) -> BuiltinInfo {
let (start, end, step) = destructure_range(ctx, arg);
Some(calculate_len_for_slice_range(generator, ctx, start, end, step).into())
} else {
let int32 = ctx.ctx.i32_type();
let zero = int32.const_zero();
let len = ctx
.build_gep_and_load(
arg.into_pointer_value(),
&[zero, int32.const_int(1, false)],
None,
)
.into_int_value();
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(ctx.builder.build_int_truncate(len, int32, "len2i32").into())
match &*ctx.unifier.get_ty_immutable(arg_ty) {
TypeEnum::TList { .. } => {
let int32 = ctx.ctx.i32_type();
let zero = int32.const_zero();
let len = ctx
.build_gep_and_load(
arg.into_pointer_value(),
&[zero, int32.const_int(1, false)],
None,
)
.into_int_value();
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(ctx.builder.build_int_truncate(len, int32, "len2i32").into())
}
}
TypeEnum::TNDArray { .. } => {
let llvm_i32 = ctx.ctx.i32_type();
let i32_zero = llvm_i32.const_zero();
let len = ctx.build_gep_and_load(
arg.into_pointer_value(),
&[i32_zero, i32_zero],
None,
).into_int_value();
if len.get_type().get_bit_width() != 32 {
Some(ctx.builder.build_int_truncate(len, llvm_i32, "len").into())
} else {
Some(len.into())
}
}
_ => unreachable!(),
}
})
},

12
nac3core/src/toplevel/composer.rs
View File

@ -37,12 +37,8 @@ pub struct TopLevelComposer {
// number of built-in function and classes in the definition list, later skip
pub builtin_num: usize,
pub core_config: ComposerConfig,
}
impl Default for TopLevelComposer {
fn default() -> Self {
Self::new(vec![], ComposerConfig::default()).0
}
/// The size of a native word on the target platform.
pub size_t: u32,
}
impl TopLevelComposer {
@ -52,8 +48,9 @@ impl TopLevelComposer {
pub fn new(
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
core_config: ComposerConfig,
size_t: u32,
) -> (Self, HashMap<StrRef, DefinitionId>, HashMap<StrRef, Type>) {
let mut primitives = Self::make_primitives();
let mut primitives = Self::make_primitives(size_t);
let mut definition_ast_list = builtins::get_builtins(&mut primitives);
let primitives_ty = primitives.0;
let mut unifier = primitives.1;
@ -146,6 +143,7 @@ impl TopLevelComposer {
defined_names,
method_class,
core_config,
size_t,
},
builtin_id,
builtin_ty,

3
nac3core/src/toplevel/helper.rs
View File

@ -44,7 +44,7 @@ impl TopLevelDef {
impl TopLevelComposer {
#[must_use]
pub fn make_primitives() -> (PrimitiveStore, Unifier) {
pub fn make_primitives(size_t: u32) -> (PrimitiveStore, Unifier) {
let mut unifier = Unifier::new();
let int32 = unifier.add_ty(TypeEnum::TObj {
obj_id: DefinitionId(0),
@ -144,6 +144,7 @@ impl TopLevelComposer {
str,
exception,
option,
size_t,
};
unifier.put_primitive_store(&primitives);
crate::typecheck::magic_methods::set_primitives_magic_methods(&primitives, &mut unifier);

1
nac3core/src/toplevel/mod.rs
View File

@ -25,6 +25,7 @@ pub struct DefinitionId(pub usize);
pub mod builtins;
pub mod composer;
pub mod helper;
pub mod numpy;
pub mod type_annotation;
use composer::*;
use type_annotation::*;

883
nac3core/src/toplevel/numpy.rs Normal file
View File

@ -0,0 +1,883 @@
use inkwell::{AddressSpace, IntPredicate, types::BasicType, values::{BasicValueEnum, PointerValue}};
use inkwell::values::{ArrayValue, IntValue};
use nac3parser::ast::StrRef;
use crate::{
codegen::{
CodeGenContext,
CodeGenerator,
irrt::{
call_ndarray_calc_nd_indices,
call_ndarray_calc_size,
call_ndarray_init_dims,
},
stmt::gen_for_callback
},
symbol_resolver::ValueEnum,
toplevel::DefinitionId,
typecheck::typedef::{FunSignature, Type, TypeEnum},
};
/// Creates an `NDArray` instance from a constant shape.
///
/// * `elem_ty` - The element type of the `NDArray`.
/// * `shape` - The shape of the `NDArray`, represented as an LLVM [ArrayValue].
fn create_ndarray_const_shape<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
shape: ArrayValue<'ctx>
) -> Result<PointerValue<'ctx>, String> {
let ndarray_ty_enum = TypeEnum::ndarray(&mut ctx.unifier, Some(elem_ty), None, &ctx.primitives);
let ndarray_ty = ctx.unifier.add_ty(ndarray_ty_enum);
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
let llvm_ndarray_data_t = ctx.get_llvm_type(generator, elem_ty).as_basic_type_enum();
assert!(llvm_ndarray_data_t.is_sized());
for i in 0..shape.get_type().len() {
let shape_dim = ctx.builder.build_extract_value(
shape,
i,
"",
).unwrap();
let shape_dim_gez = ctx.builder.build_int_compare(
IntPredicate::SGE,
shape_dim.into_int_value(),
llvm_usize.const_zero(),
""
);
ctx.make_assert(
generator,
shape_dim_gez,
"0:ValueError",
"negative dimensions not supported",
[None, None, None],
ctx.current_loc,
);
}
let ndarray = generator.gen_var_alloc(
ctx,
llvm_ndarray_t.into(),
None,
)?;
let num_dims = llvm_usize.const_int(shape.get_type().len() as u64, false);
let ndarray_num_dims = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
"",
)
};
ctx.builder.build_store(ndarray_num_dims, num_dims);
let ndarray_dims = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
"",
)
};
let ndarray_num_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None,
).into_int_value();
ctx.builder.build_store(
ndarray_dims,
ctx.builder.build_array_alloca(
llvm_usize,
ndarray_num_dims,
"",
),
);
for i in 0..shape.get_type().len() {
let ndarray_dim = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
None,
).into_pointer_value();
let ndarray_dim = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray_dim,
&[llvm_i32.const_int(i as u64, true)],
"",
)
};
let shape_dim = ctx.builder.build_extract_value(shape, i, "")
.map(|val| val.into_int_value())
.unwrap();
ctx.builder.build_store(ndarray_dim, shape_dim);
}
let (ndarray_num_dims, ndarray_dims) = unsafe {
(
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
""
),
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
""
),
)
};
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
ctx.builder.build_load(ndarray_num_dims, "").into_int_value(),
ctx.builder.build_load(ndarray_dims, "").into_pointer_value(),
);
let ndarray_data = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(2, true)],
"",
)
};
ctx.builder.build_store(
ndarray_data,
ctx.builder.build_array_alloca(
llvm_ndarray_data_t,
ndarray_num_elems,
""
),
);
Ok(ndarray)
}
fn ndarray_zero_value<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
) -> BasicValueEnum<'ctx> {
if [ctx.primitives.int32, ctx.primitives.uint32].iter().any(|ty| ctx.unifier.unioned(elem_ty, *ty)) {
ctx.ctx.i32_type().const_zero().into()
} else if [ctx.primitives.int64, ctx.primitives.uint64].iter().any(|ty| ctx.unifier.unioned(elem_ty, *ty)) {
ctx.ctx.i64_type().const_zero().into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.float) {
ctx.ctx.f64_type().const_zero().into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
ctx.ctx.bool_type().const_zero().into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
ctx.gen_string(generator, "").into()
} else {
unreachable!()
}
}
fn ndarray_one_value<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
) -> BasicValueEnum<'ctx> {
if [ctx.primitives.int32, ctx.primitives.uint32].iter().any(|ty| ctx.unifier.unioned(elem_ty, *ty)) {
let is_signed = ctx.unifier.unioned(elem_ty, ctx.primitives.int32);
ctx.ctx.i32_type().const_int(1, is_signed).into()
} else if [ctx.primitives.int64, ctx.primitives.uint64].iter().any(|ty| ctx.unifier.unioned(elem_ty, *ty)) {
let is_signed = ctx.unifier.unioned(elem_ty, ctx.primitives.int64);
ctx.ctx.i64_type().const_int(1, is_signed).into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.float) {
ctx.ctx.f64_type().const_float(1.0).into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
ctx.ctx.bool_type().const_int(1, false).into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
ctx.gen_string(generator, "1").into()
} else {
unreachable!()
}
}
/// LLVM-typed implementation for generating the implementation for constructing an `NDArray`.
///
/// * `elem_ty` - The element type of the NDArray.
/// * `shape` - The `shape` parameter used to construct the NDArray.
fn call_ndarray_empty_impl<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
shape: PointerValue<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
let ndarray_ty_enum = TypeEnum::ndarray(&mut ctx.unifier, Some(elem_ty), None, &ctx.primitives);
let ndarray_ty = ctx.unifier.add_ty(ndarray_ty_enum);
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
let llvm_ndarray_data_t = ctx.get_llvm_type(generator, elem_ty).as_basic_type_enum();
assert!(llvm_ndarray_data_t.is_sized());
// Assert that all dimensions are non-negative
gen_for_callback(
generator,
ctx,
|generator, ctx| {
let i = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
ctx.builder.build_store(i, llvm_usize.const_zero());
Ok(i)
},
|_, ctx, i_addr| {
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
let shape_len = ctx.build_gep_and_load(
shape,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
None,
).into_int_value();
Ok(ctx.builder.build_int_compare(IntPredicate::ULE, i, shape_len, ""))
},
|generator, ctx, i_addr| {
let shape_elems = ctx.build_gep_and_load(
shape,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None
).into_pointer_value();
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
let shape_dim = ctx.build_gep_and_load(
shape_elems,
&[i],
None
).into_int_value();
let shape_dim_gez = ctx.builder.build_int_compare(
IntPredicate::SGE,
shape_dim,
llvm_i32.const_zero(),
""
);
ctx.make_assert(
generator,
shape_dim_gez,
"0:ValueError",
"negative dimensions not supported",
[None, None, None],
ctx.current_loc,
);
Ok(())
},
|_, ctx, i_addr| {
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
let i = ctx.builder.build_int_add(i, llvm_usize.const_int(1, true), "");
ctx.builder.build_store(i_addr, i);
Ok(())
},
)?;
let ndarray = generator.gen_var_alloc(
ctx,
llvm_ndarray_t.into(),
None,
)?;
let num_dims = ctx.build_gep_and_load(
shape,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
None
).into_int_value();
let ndarray_num_dims = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
"",
)
};
ctx.builder.build_store(ndarray_num_dims, num_dims);
let ndarray_dims = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
"",
)
};
let ndarray_num_dims = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
None,
).into_int_value();
ctx.builder.build_store(
ndarray_dims,
ctx.builder.build_array_alloca(
llvm_usize,
ndarray_num_dims,
"",
),
);
call_ndarray_init_dims(generator, ctx, ndarray, shape);
let (ndarray_num_dims, ndarray_dims) = unsafe {
(
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
""
),
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
""
),
)
};
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
ctx.builder.build_load(ndarray_num_dims, "").into_int_value(),
ctx.builder.build_load(ndarray_dims, "").into_pointer_value(),
);
let ndarray_data = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(2, true)],
"",
)
};
ctx.builder.build_store(
ndarray_data,
ctx.builder.build_array_alloca(
llvm_ndarray_data_t,
ndarray_num_elems,
"",
),
);
Ok(ndarray)
}
/// Generates LLVM IR for populating the entire `NDArray` using a lambda with its flattened index as
/// its input.
///
/// Note that this differs from `ndarray.fill`, which instead replaces all first-dimension elements
/// with the given value (as opposed to all elements within the array).
fn ndarray_fill_flattened<'ctx, 'a, ValueFn>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
ndarray: PointerValue<'ctx>,
value_fn: ValueFn,
) -> Result<(), String>
where
ValueFn: Fn(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>, IntValue<'ctx>) -> Result<BasicValueEnum<'ctx>, String>,
{
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let (num_dims, dims) = unsafe {
(
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_zero()],
""
),
ctx.builder.build_in_bounds_gep(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(1, true)],
""
),
)
};
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
ctx.builder.build_load(num_dims, "").into_int_value(),
ctx.builder.build_load(dims, "").into_pointer_value(),
);
gen_for_callback(
generator,
ctx,
|generator, ctx| {
let i = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
ctx.builder.build_store(i, llvm_usize.const_zero());
Ok(i)
},
|_, ctx, i_addr| {
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
Ok(ctx.builder.build_int_compare(IntPredicate::ULT, i, ndarray_num_elems, ""))
},
|generator, ctx, i_addr| {
let ndarray_data = ctx.build_gep_and_load(
ndarray,
&[llvm_i32.const_zero(), llvm_i32.const_int(2, true)],
None
).into_pointer_value();
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
let elem = unsafe {
ctx.builder.build_in_bounds_gep(
ndarray_data,
&[i],
""
)
};
let value = value_fn(generator, ctx, i)?;
ctx.builder.build_store(elem, value);
Ok(())
},
|_, ctx, i_addr| {
let i = ctx.builder
.build_load(i_addr, "")
.into_int_value();
let i = ctx.builder.build_int_add(i, llvm_usize.const_int(1, true), "");
ctx.builder.build_store(i_addr, i);
Ok(())
},
)
}
/// Generates LLVM IR for populating the entire `NDArray` using a lambda with the dimension-indices
/// as its input
///
/// Note that this differs from `ndarray.fill`, which instead replaces all first-dimension elements
/// with the given value (as opposed to all elements within the array).
fn ndarray_fill_indexed<'ctx, 'a, ValueFn>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
ndarray: PointerValue<'ctx>,
value_fn: ValueFn,
) -> Result<(), String>
where
ValueFn: Fn(&mut dyn CodeGenerator, &mut CodeGenContext<'ctx, 'a>, PointerValue<'ctx>) -> Result<BasicValueEnum<'ctx>, String>,
{
ndarray_fill_flattened(
generator,
ctx,
ndarray,
|generator, ctx, idx| {
let indices = call_ndarray_calc_nd_indices(
generator,
ctx,
idx,
ndarray,
)?;
value_fn(generator, ctx, indices)
}
)
}
/// LLVM-typed implementation for generating the implementation for `ndarray.zeros`.
///
/// * `elem_ty` - The element type of the NDArray.
/// * `shape` - The `shape` parameter used to construct the NDArray.
fn call_ndarray_zeros_impl<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
shape: PointerValue<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
let supported_types = [
ctx.primitives.int32,
ctx.primitives.int64,
ctx.primitives.uint32,
ctx.primitives.uint64,
ctx.primitives.float,
ctx.primitives.bool,
ctx.primitives.str,
];
assert!(supported_types.iter().any(|supported_ty| ctx.unifier.unioned(*supported_ty, elem_ty)));
let ndarray = call_ndarray_empty_impl(generator, ctx, elem_ty, shape)?;
ndarray_fill_flattened(
generator,
ctx,
ndarray,
|generator, ctx, _| {
let value = ndarray_zero_value(generator, ctx, elem_ty);
Ok(value)
}
)?;
Ok(ndarray)
}
/// LLVM-typed implementation for generating the implementation for `ndarray.ones`.
///
/// * `elem_ty` - The element type of the NDArray.
/// * `shape` - The `shape` parameter used to construct the NDArray.
fn call_ndarray_ones_impl<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
shape: PointerValue<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
let supported_types = [
ctx.primitives.int32,
ctx.primitives.int64,
ctx.primitives.uint32,
ctx.primitives.uint64,
ctx.primitives.float,
ctx.primitives.bool,
ctx.primitives.str,
];
assert!(supported_types.iter().any(|supported_ty| ctx.unifier.unioned(*supported_ty, elem_ty)));
let ndarray = call_ndarray_empty_impl(generator, ctx, elem_ty, shape)?;
ndarray_fill_flattened(
generator,
ctx,
ndarray,
|generator, ctx, _| {
let value = ndarray_one_value(generator, ctx, elem_ty);
Ok(value)
}
)?;
Ok(ndarray)
}
/// LLVM-typed implementation for generating the implementation for `ndarray.ones`.
///
/// * `elem_ty` - The element type of the NDArray.
/// * `shape` - The `shape` parameter used to construct the NDArray.
fn call_ndarray_full_impl<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
shape: PointerValue<'ctx>,
fill_value: BasicValueEnum<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
let ndarray = call_ndarray_empty_impl(generator, ctx, elem_ty, shape)?;
ndarray_fill_flattened(
generator,
ctx,
ndarray,
|generator, ctx, _| {
let value = if fill_value.is_pointer_value() {
let llvm_void = ctx.ctx.void_type();
let llvm_i1 = ctx.ctx.bool_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
let copy = generator.gen_var_alloc(ctx, fill_value.get_type(), None)?;
let memcpy_fn_name = format!(
"llvm.memcpy.p0i8.p0i8.i{}",
generator.get_size_type(ctx.ctx).get_bit_width(),
);
let memcpy_fn = ctx.module.get_function(memcpy_fn_name.as_str()).unwrap_or_else(|| {
let fn_type = llvm_void.fn_type(
&[
llvm_pi8.into(),
llvm_pi8.into(),
llvm_usize.into(),
llvm_i1.into(),
],
false,
);
ctx.module.add_function(memcpy_fn_name.as_str(), fn_type, None)
});
ctx.builder.build_call(
memcpy_fn,
&[
copy.into(),
fill_value.into(),
fill_value.get_type().size_of().unwrap().into(),
llvm_i1.const_zero().into(),
],
"",
);
copy.into()
} else if fill_value.is_int_value() || fill_value.is_float_value() {
fill_value.into()
} else {
unreachable!()
};
Ok(value)
}
)?;
Ok(ndarray)
}
/// LLVM-typed implementation for generating the implementation for `ndarray.eye`.
///
/// * `elem_ty` - The element type of the NDArray.
fn call_ndarray_eye_impl<'ctx, 'a>(
generator: &mut dyn CodeGenerator,
ctx: &mut CodeGenContext<'ctx, 'a>,
elem_ty: Type,
nrows: IntValue<'ctx>,
ncols: IntValue<'ctx>,
offset: IntValue<'ctx>,
) -> Result<PointerValue<'ctx>, String> {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_usize_2 = llvm_usize.array_type(2);
let shape_addr = generator.gen_var_alloc(ctx, llvm_usize_2.into(), None)?;
let shape = ctx.builder.build_load(shape_addr, "")
.into_array_value();
let nrows = ctx.builder.build_int_z_extend_or_bit_cast(nrows, llvm_usize, "");
let shape = ctx.builder
.build_insert_value(shape, nrows, 0, "")
.map(|val| val.into_array_value())
.unwrap();
let ncols = ctx.builder.build_int_z_extend_or_bit_cast(ncols, llvm_usize, "");
let shape = ctx.builder
.build_insert_value(shape, ncols, 1, "")
.map(|val| val.into_array_value())
.unwrap();
let ndarray = create_ndarray_const_shape(generator, ctx, elem_ty, shape)?;
ndarray_fill_indexed(
generator,
ctx,
ndarray,
|generator, ctx, indices| {
let row = ctx.build_gep_and_load(
indices,
&[llvm_i32.const_zero()],
None,
).into_int_value();
let col = ctx.build_gep_and_load(
indices,
&[llvm_i32.const_int(1, true)],
None,
).into_int_value();
let col_with_offset = ctx.builder.build_int_add(
col,
ctx.builder.build_int_z_extend_or_bit_cast(offset, llvm_usize, ""),
""
);
let is_on_diag = ctx.builder.build_int_compare(
IntPredicate::EQ,
row,
col_with_offset,
""
);
let zero = ndarray_zero_value(generator, ctx, elem_ty);
let one = ndarray_one_value(generator, ctx, elem_ty);
let value = ctx.builder.build_select(is_on_diag, one, zero, "");
Ok(value)
},
)?;
Ok(ndarray)
}
/// Generates LLVM IR for `ndarray.empty`.
pub fn gen_ndarray_empty<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert_eq!(args.len(), 1);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, shape_ty)?;
call_ndarray_empty_impl(
generator,
context,
context.primitives.float,
shape_arg.into_pointer_value(),
)
}
/// Generates LLVM IR for `ndarray.zeros`.
pub fn gen_ndarray_zeros<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert_eq!(args.len(), 1);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, shape_ty)?;
call_ndarray_zeros_impl(
generator,
context,
context.primitives.float,
shape_arg.into_pointer_value(),
)
}
/// Generates LLVM IR for `ndarray.ones`.
pub fn gen_ndarray_ones<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert_eq!(args.len(), 1);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, shape_ty)?;
call_ndarray_ones_impl(
generator,
context,
context.primitives.float,
shape_arg.into_pointer_value(),
)
}
/// Generates LLVM IR for `ndarray.full`.
pub fn gen_ndarray_full<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert_eq!(args.len(), 2);
let shape_ty = fun.0.args[0].ty;
let shape_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, shape_ty)?;
let fill_value_ty = fun.0.args[1].ty;
let fill_value_arg = args[1].1.clone()
.to_basic_value_enum(context, generator, fill_value_ty)?;
call_ndarray_full_impl(
generator,
context,
fill_value_ty,
shape_arg.into_pointer_value(),
fill_value_arg,
)
}
/// Generates LLVM IR for `ndarray.eye`.
pub fn gen_ndarray_eye<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert!(matches!(args.len(), 1..=3));
let nrows_ty = fun.0.args[0].ty;
let nrows_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, nrows_ty)?;
let ncols_ty = fun.0.args[1].ty;
let ncols_arg = args.iter()
.find(|arg| arg.0.map(|name| name == fun.0.args[1].name).unwrap_or(false))
.map(|arg| arg.1.clone().to_basic_value_enum(context, generator, ncols_ty))
.unwrap_or_else(|| {
args[0].1.clone().to_basic_value_enum(context, generator, nrows_ty)
})?;
let offset_ty = fun.0.args[2].ty;
let offset_arg = args.iter()
.find(|arg| arg.0.map(|name| name == fun.0.args[2].name).unwrap_or(false))
.map(|arg| arg.1.clone().to_basic_value_enum(context, generator, offset_ty))
.unwrap_or_else(|| {
Ok(context.gen_symbol_val(
generator,
fun.0.args[2].default_value.as_ref().unwrap(),
offset_ty
))
})?;
call_ndarray_eye_impl(
generator,
context,
context.primitives.float,
nrows_arg.into_int_value(),
ncols_arg.into_int_value(),
offset_arg.into_int_value(),
)
}
/// Generates LLVM IR for `ndarray.identity`.
pub fn gen_ndarray_identity<'ctx, 'a>(
context: &mut CodeGenContext<'ctx, 'a>,
obj: Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: Vec<(Option<StrRef>, ValueEnum<'ctx>)>,
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert_eq!(args.len(), 1);
let llvm_usize = generator.get_size_type(context.ctx);
let n_ty = fun.0.args[0].ty;
let n_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, n_ty)?;
call_ndarray_eye_impl(
generator,
context,
context.primitives.float,
n_arg.into_int_value(),
n_arg.into_int_value(),
llvm_usize.const_zero(),
)
}

23
nac3core/src/toplevel/type_annotation.rs
View File

@ -491,11 +491,24 @@ pub fn get_type_from_type_annotation_kinds(
(*name, (subst_ty, *mutability))
}));
let need_subst = !subst.is_empty();
let ty = unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
});
let ty = if obj_id == &DefinitionId(14) {
assert_eq!(subst.len(), 2);
let tv_tys = subst.iter()
.sorted_by_key(|(k, _)| *k)
.map(|(_, v)| v)
.collect_vec();
unifier.add_ty(TypeEnum::TNDArray {
ty: *tv_tys[0],
ndims: *tv_tys[1],
})
} else {
unifier.add_ty(TypeEnum::TObj {
obj_id: *obj_id,
fields: tobj_fields,
params: subst,
})
};
if need_subst {
if let Some(wl) = subst_list.as_mut() {
wl.push(ty);

381
nac3core/src/typecheck/type_inferencer/mod.rs
View File

@ -5,12 +5,18 @@ use std::{cell::RefCell, sync::Arc};
use super::typedef::{Call, FunSignature, FuncArg, RecordField, Type, TypeEnum, Unifier};
use super::{magic_methods::*, typedef::CallId};
use crate::{symbol_resolver::SymbolResolver, toplevel::TopLevelContext};
use crate::{symbol_resolver::{SymbolResolver, SymbolValue}, toplevel::TopLevelContext};
use itertools::izip;
use nac3parser::ast::{
self,
fold::{self, Fold},
Arguments, Comprehension, ExprContext, ExprKind, Located, Location, StrRef,
Arguments,
Comprehension,
ExprContext,
ExprKind,
Located,
Location,
StrRef
};
#[cfg(test)]
@ -41,6 +47,18 @@ pub struct PrimitiveStore {
pub str: Type,
pub exception: Type,
pub option: Type,
pub size_t: u32,
}
impl PrimitiveStore {
/// Returns a [Type] representing `size_t`.
pub fn usize(&self) -> Type {
match self.size_t {
32 => self.uint32,
64 => self.uint64,
_ => unreachable!(),
}
}
}
pub struct FunctionData {
@ -205,8 +223,12 @@ impl<'a> Fold<()> for Inferencer<'a> {
if self.unifier.unioned(iter.custom.unwrap(), self.primitives.range) {
self.unify(self.primitives.int32, target.custom.unwrap(), &target.location)?;
} else {
let list = self.unifier.add_ty(TypeEnum::TList { ty: target.custom.unwrap() });
self.unify(list, iter.custom.unwrap(), &iter.location)?;
let list_like_ty = match &*self.unifier.get_ty(iter.custom.unwrap()) {
TypeEnum::TList { .. } => self.unifier.add_ty(TypeEnum::TList { ty: target.custom.unwrap() }),
TypeEnum::TNDArray { .. } => todo!(),
_ => unreachable!(),
};
self.unify(list_like_ty, iter.custom.unwrap(), &iter.location)?;
}
let body =
body.into_iter().map(|b| self.fold_stmt(b)).collect::<Result<Vec<_>, _>>()?;
@ -761,6 +783,228 @@ impl<'a> Inferencer<'a> {
})
}
/// Tries to fold a special call. Returns [`Some`] if the call expression `func` is a special call, otherwise
/// returns [`None`].
fn try_fold_special_call(
&mut self,
location: Location,
func: &ast::Expr<()>,
args: &mut Vec<ast::Expr<()>>,
keywords: &Vec<Located<ast::KeywordData>>,
) -> Result<Option<ast::Expr<Option<Type>>>, HashSet<String>> {
let Located { location: func_location, node: ExprKind::Name { id, ctx }, .. } = func else {
return Ok(None)
};
// handle special functions that cannot be typed in the usual way...
if id == &"virtual".into() {
if args.is_empty() || args.len() > 2 || !keywords.is_empty() {
return report_error(
"`virtual` can only accept 1/2 positional arguments",
*func_location,
)
}
let arg0 = self.fold_expr(args.remove(0))?;
let ty = if let Some(arg) = args.pop() {
let top_level_defs = self.top_level.definitions.read();
self.function_data.resolver.parse_type_annotation(
top_level_defs.as_slice(),
self.unifier,
self.primitives,
&arg,
)?
} else {
self.unifier.get_dummy_var().0
};
self.virtual_checks.push((arg0.custom.unwrap(), ty, *func_location));
let custom = Some(self.unifier.add_ty(TypeEnum::TVirtual { ty }));
return Ok(Some(Located {
location,
custom,
node: ExprKind::Call {
func: Box::new(Located {
custom: None,
location: func.location,
node: ExprKind::Name { id: *id, ctx: ctx.clone() },
}),
args: vec![arg0],
keywords: vec![],
},
}))
}
// int64 is special because its argument can be a constant larger than int32
if id == &"int64".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.int64);
let v: Result<i64, _> = (*val).try_into();
return if v.is_ok() {
Ok(Some(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
}))
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
if id == &"uint32".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.uint32);
let v: Result<u32, _> = (*val).try_into();
return if v.is_ok() {
Ok(Some(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
}))
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
if id == &"uint64".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.uint64);
let v: Result<u64, _> = (*val).try_into();
return if v.is_ok() {
Ok(Some(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
}))
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
// 1-argument ndarray n-dimensional creation functions
if [
"np_ndarray".into(),
"np_empty".into(),
"np_zeros".into(),
"np_ones".into(),
].contains(id) && args.len() == 1 {
let ExprKind::List { elts, .. } = &args[0].node else {
return report_error(
format!("Expected List literal for first argument of {id}, got {}", args[0].node.name()).as_str(),
args[0].location
)
};
let ndims = elts.len() as u64;
let arg0 = self.fold_expr(args.remove(0))?;
let ndims = self.unifier.get_fresh_literal(
vec![SymbolValue::U64(ndims)],
None,
);
let ret = self.unifier.add_ty(TypeEnum::TNDArray {
ty: self.primitives.float,
ndims
});
let custom = self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "shape".into(),
ty: arg0.custom.unwrap(),
default_value: None,
},
],
ret,
vars: HashMap::new(),
}));
return Ok(Some(Located {
location,
custom: Some(ret),
node: ExprKind::Call {
func: Box::new(Located {
custom: Some(custom),
location: func.location,
node: ExprKind::Name { id: *id, ctx: ctx.clone() },
}),
args: vec![arg0],
keywords: vec![],
},
}))
}
// 2-argument ndarray n-dimensional creation functions
if id == &"np_full".into() && args.len() == 2 {
let ExprKind::List { elts, .. } = &args[0].node else {
return report_error(
format!("Expected List literal for first argument of {id}, got {}", args[0].node.name()).as_str(),
args[0].location
)
};
let ndims = elts.len() as u64;
let arg0 = self.fold_expr(args.remove(0))?;
let arg1 = self.fold_expr(args.remove(0))?;
let ty = arg1.custom.unwrap();
let ndims = self.unifier.get_fresh_literal(
vec![SymbolValue::U64(ndims)],
None,
);
let ret = self.unifier.add_ty(TypeEnum::TNDArray {
ty,
ndims
});
let custom = self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "shape".into(),
ty: arg0.custom.unwrap(),
default_value: None,
},
FuncArg {
name: "fill_value".into(),
ty: arg1.custom.unwrap(),
default_value: None,
},
],
ret,
vars: HashMap::new(),
}));
return Ok(Some(Located {
location,
custom: Some(ret),
node: ExprKind::Call {
func: Box::new(Located {
custom: Some(custom),
location: func.location,
node: ExprKind::Name { id: *id, ctx: ctx.clone() },
}),
args: vec![arg0, arg1],
keywords: vec![],
},
}))
}
Ok(None)
}
fn fold_call(
&mut self,
location: Location,
@ -768,111 +1012,11 @@ impl<'a> Inferencer<'a> {
mut args: Vec<ast::Expr<()>>,
keywords: Vec<Located<ast::KeywordData>>,
) -> Result<ast::Expr<Option<Type>>, HashSet<String>> {
let func =
if let Located { location: func_location, custom, node: ExprKind::Name { id, ctx } } =
func
{
// handle special functions that cannot be typed in the usual way...
if id == "virtual".into() {
if args.is_empty() || args.len() > 2 || !keywords.is_empty() {
return report_error(
"`virtual` can only accept 1/2 positional arguments",
func_location,
);
}
let arg0 = self.fold_expr(args.remove(0))?;
let ty = if let Some(arg) = args.pop() {
let top_level_defs = self.top_level.definitions.read();
self.function_data.resolver.parse_type_annotation(
top_level_defs.as_slice(),
self.unifier,
self.primitives,
&arg,
)?
} else {
self.unifier.get_dummy_var().0
};
self.virtual_checks.push((arg0.custom.unwrap(), ty, func_location));
let custom = Some(self.unifier.add_ty(TypeEnum::TVirtual { ty }));
return Ok(Located {
location,
custom,
node: ExprKind::Call {
func: Box::new(Located {
custom: None,
location: func.location,
node: ExprKind::Name { id, ctx },
}),
args: vec![arg0],
keywords: vec![],
},
});
}
// int64 is special because its argument can be a constant larger than int32
if id == "int64".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.int64);
let v: Result<i64, _> = (*val).try_into();
return if v.is_ok() {
Ok(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
})
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
if id == "uint32".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.uint32);
let v: Result<u32, _> = (*val).try_into();
return if v.is_ok() {
Ok(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
})
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
if id == "uint64".into() && args.len() == 1 {
if let ExprKind::Constant { value: ast::Constant::Int(val), kind } =
&args[0].node
{
let custom = Some(self.primitives.uint64);
let v: Result<u64, _> = (*val).try_into();
return if v.is_ok() {
Ok(Located {
location: args[0].location,
custom,
node: ExprKind::Constant {
value: ast::Constant::Int(*val),
kind: kind.clone(),
},
})
} else {
report_error("Integer out of bound", args[0].location)
}
}
}
Located { location: func_location, custom, node: ExprKind::Name { id, ctx } }
} else {
func
};
let func = if let Some(spec_call_func) = self.try_fold_special_call(location, &func, &mut args, &keywords)? {
return Ok(spec_call_func)
} else {
func
};
let func = Box::new(self.fold_expr(func)?);
let args = args.into_iter().map(|v| self.fold_expr(v)).collect::<Result<Vec<_>, _>>()?;
let keywords = keywords
@ -1105,9 +1249,13 @@ impl<'a> Inferencer<'a> {
for v in [lower.as_ref(), upper.as_ref(), step.as_ref()].iter().flatten() {
self.constrain(v.custom.unwrap(), self.primitives.int32, &v.location)?;
}
let list = self.unifier.add_ty(TypeEnum::TList { ty });
self.constrain(value.custom.unwrap(), list, &value.location)?;
Ok(list)
let list_like_ty = match &*self.unifier.get_ty(value.custom.unwrap()) {
TypeEnum::TList { .. } => self.unifier.add_ty(TypeEnum::TList { ty }),
TypeEnum::TNDArray { ndims, .. } => self.unifier.add_ty(TypeEnum::TNDArray { ty, ndims: *ndims }),
_ => unreachable!()
};
self.constrain(value.custom.unwrap(), list_like_ty, &value.location)?;
Ok(list_like_ty)
}
ExprKind::Constant { value: ast::Constant::Int(val), .. } => {
// the index is a constant, so value can be a sequence.
@ -1127,10 +1275,15 @@ impl<'a> Inferencer<'a> {
{
return report_error("Tuple index must be a constant (KernelInvariant is also not supported)", slice.location)
}
// the index is not a constant, so value can only be a list
self.constrain(slice.custom.unwrap(), self.primitives.int32, &slice.location)?;
let list = self.unifier.add_ty(TypeEnum::TList { ty });
self.constrain(value.custom.unwrap(), list, &value.location)?;
let list_like_ty = match &*self.unifier.get_ty(value.custom.unwrap()) {
TypeEnum::TList { .. } => self.unifier.add_ty(TypeEnum::TList { ty }),
TypeEnum::TNDArray { .. } => todo!(),
_ => unreachable!(),
};
self.constrain(value.custom.unwrap(), list_like_ty, &value.location)?;
Ok(ty)
}
}

96
nac3core/src/typecheck/typedef/mod.rs
View File

@ -159,6 +159,11 @@ pub enum TypeEnum {
ty: Type,
},
TNDArray {
ty: Type,
ndims: Type,
},
/// An object type.
TObj {
/// The [DefintionId] of this object type.
@ -193,12 +198,34 @@ impl TypeEnum {
TypeEnum::TLiteral { .. } => "TConstant",
TypeEnum::TTuple { .. } => "TTuple",
TypeEnum::TList { .. } => "TList",
TypeEnum::TNDArray { .. } => "TNDArray",
TypeEnum::TObj { .. } => "TObj",
TypeEnum::TVirtual { .. } => "TVirtual",
TypeEnum::TCall { .. } => "TCall",
TypeEnum::TFunc { .. } => "TFunc",
}
}
/// Returns a [TypeEnum] representing a generic `ndarray` type.
///
/// * `dtype` - The datatype of the `ndarray`, or `None` if the datatype is generic.
/// * `ndims` - The number of dimensions of the `ndarray`, or `None` if the number of dimensions is generic.
#[must_use]
pub fn ndarray(
unifier: &mut Unifier,
dtype: Option<Type>,
ndims: Option<Type>,
primitives: &PrimitiveStore
) -> TypeEnum {
let dtype = dtype.unwrap_or_else(|| unifier.get_fresh_var(Some("T".into()), None).0);
let ndims = ndims
.unwrap_or_else(|| unifier.get_fresh_const_generic_var(primitives.usize(), Some("N".into()), None).0);
TypeEnum::TNDArray {
ty: dtype,
ndims,
}
}
}
pub type SharedUnifier = Arc<Mutex<(UnificationTable<TypeEnum>, u32, Vec<Call>)>>;
@ -418,6 +445,9 @@ impl Unifier {
TypeEnum::TList { ty } => self
.get_instantiations(*ty)
.map(|ty| ty.iter().map(|&ty| self.add_ty(TypeEnum::TList { ty })).collect_vec()),
TypeEnum::TNDArray { ty, ndims } => self
.get_instantiations(*ty)
.map(|ty| ty.iter().map(|&ty| self.add_ty(TypeEnum::TNDArray { ty, ndims: *ndims })).collect_vec()),
TypeEnum::TVirtual { ty } => self.get_instantiations(*ty).map(|ty| {
ty.iter().map(|&ty| self.add_ty(TypeEnum::TVirtual { ty })).collect_vec()
}),
@ -470,6 +500,7 @@ impl Unifier {
TVar { .. } => allowed_typevars.iter().any(|b| self.unification_table.unioned(a, *b)),
TCall { .. } => false,
TList { ty } | TVirtual { ty } => self.is_concrete(*ty, allowed_typevars),
TNDArray { ty, .. } => self.is_concrete(*ty, allowed_typevars),
TTuple { ty } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TObj { params: vars, .. } => {
vars.values().all(|ty| self.is_concrete(*ty, allowed_typevars))
@ -717,7 +748,8 @@ impl Unifier {
self.unify_impl(x, b, false)?;
self.set_a_to_b(a, x);
}
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TList { ty }) => {
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TList { ty }) |
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TNDArray { ty, .. }) => {
for (k, v) in fields {
match *k {
RecordKey::Int(_) => {
@ -789,7 +821,23 @@ impl Unifier {
(TLiteral { values: val1, .. }, TLiteral { values: val2, .. }) => {
for (v1, v2) in zip(val1, val2) {
if v1 != v2 {
return self.incompatible_types(a, b)
let symbol_value_to_int = |value: &SymbolValue| -> Option<i128> {
match value {
SymbolValue::I32(v) => Some(*v as i128),
SymbolValue::I64(v) => Some(*v as i128),
SymbolValue::U32(v) => Some(*v as i128),
SymbolValue::U64(v) => Some(*v as i128),
_ => None,
}
};
// Try performing integer promotion on literals
let v1i = symbol_value_to_int(v1);
let v2i = symbol_value_to_int(v2);
if v1i != v2i {
return self.incompatible_types(a, b)
}
}
}
@ -813,6 +861,15 @@ impl Unifier {
}
self.set_a_to_b(a, b);
}
(TNDArray { ty: ty1, ndims: ndims1 }, TNDArray { ty: ty2, ndims: ndims2 }) => {
if self.unify_impl(*ty1, *ty2, false).is_err() {
return self.incompatible_types(a, b)
}
if self.unify_impl(*ndims1, *ndims2, false).is_err() {
return self.incompatible_types(a, b)
}
self.set_a_to_b(a, b);
}
(TVar { fields: Some(map), range, .. }, TObj { fields, .. }) => {
for (k, field) in map {
match *k {
@ -1060,6 +1117,13 @@ impl Unifier {
TypeEnum::TList { ty } => {
format!("list[{}]", self.internal_stringify(*ty, obj_to_name, var_to_name, notes))
}
TypeEnum::TNDArray { ty, ndims } => {
format!(
"ndarray[{}, {}]",
self.internal_stringify(*ty, obj_to_name, var_to_name, notes),
self.internal_stringify(*ndims, obj_to_name, var_to_name, notes),
)
}
TypeEnum::TVirtual { ty } => {
format!(
"virtual[{}]",
@ -1179,7 +1243,7 @@ impl Unifier {
// variables, i.e. things like TRecord, TCall should not occur, and we
// should be safe to not implement the substitution for those variants.
match &*ty {
TypeEnum::TRigidVar { .. } => None,
TypeEnum::TRigidVar { .. } | TypeEnum::TLiteral { .. } => None,
TypeEnum::TVar { id, .. } => mapping.get(id).copied(),
TypeEnum::TTuple { ty } => {
let mut new_ty = Cow::from(ty);
@ -1197,6 +1261,19 @@ impl Unifier {
TypeEnum::TList { ty } => {
self.subst_impl(*ty, mapping, cache).map(|t| self.add_ty(TypeEnum::TList { ty: t }))
}
TypeEnum::TNDArray { ty, ndims } => {
let new_ty = self.subst_impl(*ty, mapping, cache);
let new_ndims = self.subst_impl(*ndims, mapping, cache);
if new_ty.is_some() || new_ndims.is_some() {
Some(self.add_ty(TypeEnum::TNDArray {
ty: new_ty.unwrap_or(*ty),
ndims: new_ndims.unwrap_or(*ndims)
}))
} else {
None
}
}
TypeEnum::TVirtual { ty } => self
.subst_impl(*ty, mapping, cache)
.map(|t| self.add_ty(TypeEnum::TVirtual { ty: t })),
@ -1367,6 +1444,19 @@ impl Unifier {
(TList { ty: ty1 }, TList { ty: ty2 }) => {
Ok(self.get_intersection(*ty1, *ty2)?.map(|ty| self.add_ty(TList { ty })))
}
(TNDArray { ty: ty1, ndims: ndims1 }, TNDArray { ty: ty2, ndims: ndims2 }) => {
let ty = self.get_intersection(*ty1, *ty2)?;
let ndims = self.get_intersection(*ndims1, *ndims2)?;
Ok(if ty.is_some() || ndims.is_some() {
Some(self.add_ty(TNDArray {
ty: ty.unwrap_or(*ty1),
ndims: ndims.unwrap_or(*ndims1),
}))
} else {
None
})
}
(TVirtual { ty: ty1 }, TVirtual { ty: ty2 }) => {
Ok(self.get_intersection(*ty1, *ty2)?.map(|ty| self.add_ty(TVirtual { ty })))
}

1
nac3core/src/typecheck/typedef/test.rs
View File

@ -33,6 +33,7 @@ impl Unifier {
&& ty1.iter().zip(ty2.iter()).all(|(t1, t2)| self.eq(*t1, *t2))
}
(TypeEnum::TList { ty: ty1 }, TypeEnum::TList { ty: ty2 })
| (TypeEnum::TNDArray { ty: ty1 }, TypeEnum::TNDArray { ty: ty2 })
| (TypeEnum::TVirtual { ty: ty1 }, TypeEnum::TVirtual { ty: ty2 }) => {
self.eq(*ty1, *ty2)
}

4
nac3standalone/demo/demo.c
View File

@ -94,13 +94,13 @@ uint64_t dbg_stack_address(__attribute__((unused)) struct cslice *slice) {
}
uint32_t __nac3_personality(uint32_t state, uint32_t exception_object, uint32_t context) {
printf("__nac3_personality(state: %u, exception_object: %u, context: %u\n", state, exception_object, context);
printf("__nac3_personality(state: %u, exception_object: %u, context: %u)\n", state, exception_object, context);
exit(101);
__builtin_unreachable();
}
uint32_t __nac3_raise(uint32_t state, uint32_t exception_object, uint32_t context) {
printf("__nac3_raise(state: %u, exception_object: %u, context: %u\n", state, exception_object, context);
printf("__nac3_raise(state: %u, exception_object: %u, context: %u)\n", state, exception_object, context);
exit(101);
__builtin_unreachable();
}

28
nac3standalone/demo/interpret_demo.py
View File

@ -5,11 +5,12 @@ import importlib.util
import importlib.machinery
import math
import numpy as np
import numpy.typing as npt
import pathlib
from numpy import int32, int64, uint32, uint64
from scipy import special
from typing import TypeVar, Generic, Literal
from typing import TypeVar, Generic, Literal, Union
T = TypeVar('T')
class Option(Generic[T]):
@ -50,6 +51,13 @@ class _ConstGenericMarker:
def ConstGeneric(name, constraint):
return TypeVar(name, _ConstGenericMarker, constraint)
N = TypeVar("N", bound=np.uint64)
class _NDArrayDummy(Generic[T, N]):
pass
# https://stackoverflow.com/questions/67803260/how-to-create-a-type-alias-with-a-throw-away-generic
NDArray = Union[npt.NDArray[T], _NDArrayDummy[T, N]]
def round_away_zero(x):
if x >= 0.0:
return math.floor(x + 0.5)
@ -124,6 +132,16 @@ def patch(module):
module.ceil64 = math.ceil
module.np_ceil = np.ceil
# NumPy ndarray functions
module.ndarray = NDArray
module.np_ndarray = np.ndarray
module.np_empty = np.empty
module.np_zeros = np.zeros
module.np_ones = np.ones
module.np_full = np.full
module.np_eye = np.eye
module.np_identity = np.identity
# NumPy Math functions
module.np_isnan = np.isnan
module.np_isinf = np.isinf
@ -166,6 +184,14 @@ def patch(module):
module.sp_spec_j0 = special.j0
module.sp_spec_j1 = special.j1
# NumPy NDArray Functions
module.np_ndarray = np.ndarray
module.np_empty = np.empty
module.np_zeros = np.zeros
module.np_ones = np.ones
module.np_full = np.full
module.np_eye = np.eye
module.np_identity = np.identity
def file_import(filename, prefix="file_import_"):
filename = pathlib.Path(filename)

55
nac3standalone/demo/src/ndarray.py Normal file
View File

@ -0,0 +1,55 @@
def consume_ndarray_1(n: ndarray[float, Literal[1]]):
pass
def consume_ndarray_i32_1(n: ndarray[int32, Literal[1]]):
pass
def consume_ndarray_2(n: ndarray[float, Literal[2]]):
pass
def consume_ndarray_i32_1(n: ndarray[int32, 1]):
pass
def consume_ndarray_2(n: ndarray[float, 2]):
pass
def test_ndarray_ctor():
n = np_ndarray([1])
consume_ndarray_1(n)
def test_ndarray_empty():
n = np_empty([1])
consume_ndarray_1(n)
def test_ndarray_zeros():
n = np_zeros([1])
consume_ndarray_1(n)
def test_ndarray_ones():
n = np_ones([1])
consume_ndarray_1(n)
def test_ndarray_full():
n_float = np_full([1], 2.0)
consume_ndarray_1(n_float)
n_i32 = np_full([1], 2)
consume_ndarray_i32_1(n_i32)
def test_ndarray_eye():
n = np_eye(2)
consume_ndarray_2(n)
def test_ndarray_identity():
n = np_identity(2)
consume_ndarray_2(n)
def run() -> int32:
test_ndarray_ctor()
test_ndarray_empty()
test_ndarray_zeros()
test_ndarray_ones()
test_ndarray_full()
test_ndarray_eye()
test_ndarray_identity()
return 0

7
nac3standalone/src/main.rs
View File

@ -286,6 +286,7 @@ fn main() {
// The default behavior for -O<n> where n>3 defaults to O3 for both Clang and GCC
_ => OptimizationLevel::Aggressive,
};
const SIZE_T: u32 = 64;
let program = match fs::read_to_string(file_name.clone()) {
Ok(program) => program,
@ -295,9 +296,9 @@ fn main() {
}
};
let primitive: PrimitiveStore = TopLevelComposer::make_primitives().0;
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(SIZE_T).0;
let (mut composer, builtins_def, builtins_ty) =
TopLevelComposer::new(vec![], ComposerConfig::default());
TopLevelComposer::new(vec![], ComposerConfig::default(), SIZE_T);
let internal_resolver: Arc<ResolverInternal> = ResolverInternal {
id_to_type: builtins_ty.into(),
@ -400,7 +401,7 @@ fn main() {
membuffer.lock().push(buffer);
})));
let threads = (0..threads)
.map(|i| Box::new(DefaultCodeGenerator::new(format!("module{i}"), 64)))
.map(|i| Box::new(DefaultCodeGenerator::new(format!("module{i}"), SIZE_T)))
.collect();
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
registry.add_task(task);