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core/numpy: Implement codegen for np_array

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This commit is contained in:
David Mak 2024-06-11 15:29:32 +08:00
parent 4730b595f3
commit 6153f94b05
2 changed files with 473 additions and 5 deletions
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471
nac3core/src/codegen/numpy.rs
View File

@ -1,12 +1,16 @@
use inkwell::{IntPredicate, OptimizationLevel, types::BasicType, values::{BasicValueEnum, IntValue, PointerValue}};
use inkwell::{AddressSpace, IntPredicate, OptimizationLevel, types::BasicType, values::{BasicValueEnum, IntValue, PointerValue}};
use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
use nac3parser::ast::{Operator, StrRef};
use crate::{
codegen::{
classes::{
ArrayLikeIndexer,
ArrayLikeValue,
ListType,
ListValue,
NDArrayType,
NDArrayValue,
ProxyType,
ProxyValue,
TypedArrayLikeAccessor,
TypedArrayLikeAdapter,
@ -31,9 +35,10 @@ use crate::{
symbol_resolver::ValueEnum,
toplevel::{
DefinitionId,
helper::PRIMITIVE_DEF_IDS,
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
},
typecheck::typedef::{FunSignature, Type},
typecheck::typedef::{FunSignature, Type, TypeEnum},
};
/// Creates an uninitialized `NDArray` instance.
@ -589,6 +594,405 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
Ok(ndarray)
}
/// Returns the number of dimensions for a multidimensional list as an [`IntValue`].
fn llvm_ndlist_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
ty: PointerType<'ctx>,
) -> IntValue<'ctx> {
let llvm_usize = generator.get_size_type(ctx.ctx);
let list_ty = ListType::from_type(ty, llvm_usize);
let list_elem_ty = list_ty.element_type();
let ndims = llvm_usize.const_int(1, false);
match list_elem_ty {
AnyTypeEnum::PointerType(ptr_ty) if ListType::is_type(ptr_ty, llvm_usize).is_ok() => {
ndims.const_add(llvm_ndlist_get_ndims(generator, ctx, ptr_ty))
}
AnyTypeEnum::PointerType(ptr_ty) if NDArrayType::is_type(ptr_ty, llvm_usize).is_ok() => {
todo!("Getting ndims for list[ndarray] not supported")
}
_ => ndims,
}
}
/// Returns the number of dimensions for an array-like object as an [`IntValue`].
fn llvm_arraylike_get_ndims<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
value: BasicValueEnum<'ctx>,
) -> IntValue<'ctx> {
let llvm_usize = generator.get_size_type(ctx.ctx);
match value {
BasicValueEnum::PointerValue(v) if NDArrayValue::is_instance(v, llvm_usize).is_ok() => {
NDArrayValue::from_ptr_val(v, llvm_usize, None).load_ndims(ctx)
}
BasicValueEnum::PointerValue(v) if ListValue::is_instance(v, llvm_usize).is_ok() => {
llvm_ndlist_get_ndims(generator, ctx, v.get_type())
}
_ => llvm_usize.const_zero(),
}
}
/// Flattens and copies the values from a multidimensional list into an [`NDArrayValue`].
fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
(dst_arr, dst_slice_ptr): (NDArrayValue<'ctx>, PointerValue<'ctx>),
src_lst: ListValue<'ctx>,
dim: u64,
) -> Result<(), String> {
let llvm_i1 = ctx.ctx.bool_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let list_elem_ty = src_lst.get_type().element_type();
match list_elem_ty {
AnyTypeEnum::PointerType(ptr_ty) if ListType::is_type(ptr_ty, llvm_usize).is_ok() => {
// The stride of elements in this dimension, i.e. the number of elements between arr[i]
// and arr[i + 1] in this dimension
let stride = call_ndarray_calc_size(
generator,
ctx,
&dst_arr.dim_sizes(),
(Some(llvm_usize.const_int(dim + 1, false)), None),
);
gen_for_range_callback(
generator,
ctx,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, ctx| Ok(src_lst.load_size(ctx, None)), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, i| {
let offset = ctx.builder.build_int_mul(
stride,
i,
"",
).unwrap();
let dst_ptr = unsafe {
ctx.builder.build_gep(dst_slice_ptr, &[offset], "").unwrap()
};
let nested_lst_elem = ListValue::from_ptr_val(
unsafe {
src_lst.data().get_unchecked(ctx, generator, &i, None)
}.into_pointer_value(),
llvm_usize,
None,
);
ndarray_from_ndlist_impl(
generator,
ctx,
elem_ty,
(dst_arr, dst_ptr),
nested_lst_elem,
dim + 1,
)?;
Ok(())
},
)?;
}
AnyTypeEnum::PointerType(ptr_ty) if NDArrayType::is_type(ptr_ty, llvm_usize).is_ok() => {
todo!("Not implemented for list[ndarray]")
}
_ => {
let lst_len = src_lst.load_size(ctx, None);
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let cpy_len = ctx.builder.build_int_mul(
ctx.builder.build_int_z_extend_or_bit_cast(lst_len, llvm_usize, "").unwrap(),
sizeof_elem,
""
).unwrap();
call_memcpy_generic(
ctx,
dst_slice_ptr,
src_lst.data().base_ptr(ctx, generator),
cpy_len,
llvm_i1.const_zero(),
);
}
}
Ok(())
}
/// LLVM-typed implementation for `ndarray.array`.
fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
object: BasicValueEnum<'ctx>,
copy: IntValue<'ctx>,
ndmin: IntValue<'ctx>,
) -> Result<NDArrayValue<'ctx>, String> {
let llvm_i1 = ctx.ctx.bool_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let ndmin = ctx.builder
.build_int_z_extend_or_bit_cast(ndmin, llvm_usize, "")
.unwrap();
// TODO(Derppening): Add assertions for sizes of different dimensions
// object is not a pointer - 0-dim NDArray
if !object.is_pointer_value() {
let ndarray = create_ndarray_const_shape(
generator,
ctx,
elem_ty,
&[],
)?;
unsafe {
ndarray.data()
.set_unchecked(ctx, generator, &llvm_usize.const_zero(), object);
}
return Ok(ndarray)
}
let object = object.into_pointer_value();
// object is an NDArray instance - copy object unless copy=0 && ndmin < object.ndims
if NDArrayValue::is_instance(object, llvm_usize).is_ok() {
let object = NDArrayValue::from_ptr_val(object, llvm_usize, None);
let ndarray = gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
let copy_nez = ctx.builder
.build_int_compare(IntPredicate::NE, copy, llvm_i1.const_zero(), "")
.unwrap();
let ndmin_gt_ndims = ctx.builder
.build_int_compare(IntPredicate::UGT, ndmin, object.load_ndims(ctx), "")
.unwrap();
Ok(ctx.builder
.build_and(copy_nez, ndmin_gt_ndims, "")
.unwrap())
},
|generator, ctx| {
let ndarray = create_ndarray_dyn_shape(
generator,
ctx,
elem_ty,
&object,
|_, ctx, object| {
let ndims = object.load_ndims(ctx);
let ndmin_gt_ndims = ctx.builder
.build_int_compare(IntPredicate::UGT, ndmin, object.load_ndims(ctx), "")
.unwrap();
Ok(ctx.builder
.build_select(ndmin_gt_ndims, ndmin, ndims, "")
.map(BasicValueEnum::into_int_value)
.unwrap())
},
|generator, ctx, object, idx| {
let ndims = object.load_ndims(ctx);
let ndmin = llvm_intrinsics::call_int_umax(ctx, ndims, ndmin, None);
// The number of dimensions to prepend 1's to
let offset = ctx.builder.build_int_sub(ndmin, ndims, "").unwrap();
Ok(gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx.builder
.build_int_compare(IntPredicate::UGE, idx, offset, "")
.unwrap())
},
|_, _| {
Ok(Some(llvm_usize.const_int(1, false)))
},
|_, ctx| {
Ok(Some(ctx.builder.build_int_sub(
idx,
offset,
""
).unwrap()))
},
)?.map(BasicValueEnum::into_int_value).unwrap())
},
)?;
ndarray_sliced_copyto_impl(
generator,
ctx,
elem_ty,
(ndarray, ndarray.data().base_ptr(ctx, generator)),
(object, object.data().base_ptr(ctx, generator)),
0,
&[],
)?;
Ok(Some(ndarray.as_base_value()))
},
|_, _| {
Ok(Some(object.as_base_value()))
},
)?;
return Ok(NDArrayValue::from_ptr_val(
ndarray.map(BasicValueEnum::into_pointer_value).unwrap(),
llvm_usize,
None,
))
}
// Remaining case: TList
assert!(ListValue::is_instance(object, llvm_usize).is_ok());
let object = ListValue::from_ptr_val(object, llvm_usize, None);
// The number of dimensions to prepend 1's to
let ndims = llvm_ndlist_get_ndims(generator, ctx, object.as_base_value().get_type());
let ndmin = llvm_intrinsics::call_int_umax(ctx, ndims, ndmin, None);
let offset = ctx.builder.build_int_sub(ndmin, ndims, "").unwrap();
let ndarray = create_ndarray_dyn_shape(
generator,
ctx,
elem_ty,
&object,
|generator, ctx, object| {
let ndims = llvm_ndlist_get_ndims(generator, ctx, object.as_base_value().get_type());
let ndmin_gt_ndims = ctx.builder
.build_int_compare(IntPredicate::UGT, ndmin, ndims, "")
.unwrap();
Ok(ctx.builder
.build_select(ndmin_gt_ndims, ndmin, ndims, "")
.map(BasicValueEnum::into_int_value)
.unwrap())
},
|generator, ctx, object, idx| {
Ok(gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx.builder
.build_int_compare(IntPredicate::ULT, idx, offset, "")
.unwrap())
},
|_, _| {
Ok(Some(llvm_usize.const_int(1, false)))
},
|generator, ctx| {
let make_llvm_list = |elem_ty: BasicTypeEnum<'ctx>| {
ctx.ctx.struct_type(
&[
elem_ty.ptr_type(AddressSpace::default()).into(),
llvm_usize.into(),
],
false,
)
};
let llvm_i8 = ctx.ctx.i8_type();
let llvm_list_i8 = make_llvm_list(llvm_i8.into());
let llvm_plist_i8 = llvm_list_i8.ptr_type(AddressSpace::default());
// Cast list to { i8*, usize } since we only care about the size
let lst = generator.gen_var_alloc(
ctx,
ListType::new(generator, ctx.ctx, llvm_i8.into()).as_base_type().into(),
None,
).unwrap();
ctx.builder.build_store(
lst,
ctx.builder.build_bitcast(
object.as_base_value(),
llvm_plist_i8,
"",
).unwrap(),
).unwrap();
let stop = ctx.builder.build_int_sub(idx, offset, "").unwrap();
gen_for_range_callback(
generator,
ctx,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, _| Ok(stop), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _| {
let plist_plist_i8 = make_llvm_list(llvm_plist_i8.into())
.ptr_type(AddressSpace::default());
let this_dim = ctx.builder
.build_load(lst, "")
.map(BasicValueEnum::into_pointer_value)
.map(|v| ctx.builder.build_bitcast(v, plist_plist_i8, "").unwrap())
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let this_dim = ListValue::from_ptr_val(
this_dim,
llvm_usize,
None,
);
// TODO: Assert this_dim.sz != 0
let next_dim = unsafe {
this_dim.data()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
}.into_pointer_value();
ctx.builder.build_store(
lst,
ctx.builder.build_bitcast(
next_dim,
llvm_plist_i8,
"",
).unwrap(),
).unwrap();
Ok(())
},
)?;
let lst = ListValue::from_ptr_val(
ctx.builder
.build_load(lst, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap(),
llvm_usize,
None,
);
Ok(Some(lst.load_size(ctx, None)))
},
)?.map(BasicValueEnum::into_int_value).unwrap())
},
)?;
ndarray_from_ndlist_impl(
generator,
ctx,
elem_ty,
(ndarray, ndarray.data().base_ptr(ctx, generator)),
object,
0,
)?;
Ok(ndarray)
}
/// LLVM-typed implementation for generating the implementation for `ndarray.eye`.
///
/// * `elem_ty` - The element type of the `NDArray`.
@ -1450,6 +1854,69 @@ pub fn gen_ndarray_full<'ctx>(
).map(NDArrayValue::into)
}
pub fn gen_ndarray_array<'ctx>(
context: &mut CodeGenContext<'ctx, '_>,
obj: &Option<(Type, ValueEnum<'ctx>)>,
fun: (&FunSignature, DefinitionId),
args: &[(Option<StrRef>, ValueEnum<'ctx>)],
generator: &mut dyn CodeGenerator,
) -> Result<PointerValue<'ctx>, String> {
assert!(obj.is_none());
assert!(matches!(args.len(), 1..=3));
let obj_ty = fun.0.args[0].ty;
let obj_elem_ty = match &*context.unifier.get_ty(obj_ty) {
TypeEnum::TObj { obj_id, .. } if *obj_id == PRIMITIVE_DEF_IDS.ndarray => {
unpack_ndarray_var_tys(&mut context.unifier, obj_ty).0
}
TypeEnum::TList { ty } => {
let mut ty = *ty;
while let TypeEnum::TList { ty: elem_ty } = &*context.unifier.get_ty_immutable(ty) {
ty = *elem_ty;
}
ty
},
_ => obj_ty,
};
let obj_arg = args[0].1.clone()
.to_basic_value_enum(context, generator, obj_ty)?;
let copy_arg = if let Some(arg) =
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[1].name)) {
let copy_ty = fun.0.args[1].ty;
arg.1.clone().to_basic_value_enum(context, generator, copy_ty)?
} else {
context.gen_symbol_val(
generator,
fun.0.args[1].default_value.as_ref().unwrap(),
fun.0.args[1].ty,
)
};
let ndmin_arg = if let Some(arg) =
args.iter().find(|arg| arg.0.is_some_and(|name| name == fun.0.args[2].name)) {
let ndmin_ty = fun.0.args[2].ty;
arg.1.clone().to_basic_value_enum(context, generator, ndmin_ty)?
} else {
context.gen_symbol_val(
generator,
fun.0.args[2].default_value.as_ref().unwrap(),
fun.0.args[2].ty,
)
};
call_ndarray_array_impl(
generator,
context,
obj_elem_ty,
obj_arg,
copy_arg.into_int_value(),
ndmin_arg.into_int_value(),
).map(NDArrayValue::into)
}
/// Generates LLVM IR for `ndarray.eye`.
pub fn gen_ndarray_eye<'ctx>(
context: &mut CodeGenContext<'ctx, '_>,

7
nac3core/src/toplevel/builtins.rs
View File

@ -809,15 +809,16 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
},
],
ret: ndarray,
vars: VarMap::default(),
vars: VarMap::from([(tv.1, tv.0)]),
})),
var_id: Vec::default(),
var_id: vec![tv.1],
instance_to_symbol: HashMap::default(),
instance_to_stmt: HashMap::default(),
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
|ctx, obj, fun, args, generator| {
todo!()
gen_ndarray_array(ctx, &obj, fun, &args, generator)
.map(|val| Some(val.as_basic_value_enum()))
},
)))),
loc: None,