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core: WIP - fabs, sqrt and rint works now

David Mak 2024-04-30 16:16:19 +08:00
parent ffcae46bd8
commit 11a0bcc443
3 changed files with 136 additions and 37 deletions
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122
nac3core/src/codegen/builtin_fns.rs
View File

@ -1217,46 +1217,124 @@ pub fn call_numpy_log2<'ctx, G: CodeGenerator + ?Sized>(
})
}
/// Invokes the `np_sqrt` builtin function.
pub fn call_numpy_fabs<'ctx>(
/// Invokes the `np_fabs` builtin function.
pub fn call_numpy_fabs<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x: (Type, FloatValue<'ctx>),
) -> FloatValue<'ctx> {
x: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_fabs";
let llvm_usize = generator.get_size_type(ctx.ctx);
let (x_ty, x) = x;
if !ctx.unifier.unioned(x_ty, ctx.primitives.float) {
unsupported_type(ctx, "np_fabs", &[x_ty])
}
Ok(match x.get_type() {
BasicTypeEnum::FloatType(_) => {
debug_assert!(ctx.unifier.unioned(x_ty, ctx.primitives.float));
llvm_intrinsics::call_float_fabs(ctx, x, None)
llvm_intrinsics::call_float_fabs(ctx, x.into_float_value(), None).into()
}
BasicTypeEnum::PointerType(_) if x_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray) => {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
elem_ty,
None,
NDArrayValue::from_ptr_val(x.into_pointer_value(), llvm_usize, None),
|generator, ctx, val| {
call_numpy_fabs(generator, ctx, (elem_ty, val))
},
)?;
ndarray.as_ptr_value().into()
}
_ => unsupported_type(ctx, FN_NAME, &[x_ty])
})
}
/// Invokes the `np_sqrt` builtin function.
pub fn call_numpy_sqrt<'ctx>(
pub fn call_numpy_sqrt<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x: (Type, FloatValue<'ctx>),
) -> FloatValue<'ctx> {
x: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_sqrt";
let llvm_usize = generator.get_size_type(ctx.ctx);
let (x_ty, x) = x;
if !ctx.unifier.unioned(x_ty, ctx.primitives.float) {
unsupported_type(ctx, "np_sqrt", &[x_ty])
}
Ok(match x.get_type() {
BasicTypeEnum::FloatType(_) => {
debug_assert!(ctx.unifier.unioned(x_ty, ctx.primitives.float));
llvm_intrinsics::call_float_sqrt(ctx, x, None)
llvm_intrinsics::call_float_sqrt(ctx, x.into_float_value(), None).into()
}
BasicTypeEnum::PointerType(_) if x_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray) => {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
elem_ty,
None,
NDArrayValue::from_ptr_val(x.into_pointer_value(), llvm_usize, None),
|generator, ctx, val| {
call_numpy_sqrt(generator, ctx, (elem_ty, val))
},
)?;
ndarray.as_ptr_value().into()
}
_ => unsupported_type(ctx, FN_NAME, &[x_ty])
})
}
/// Invokes the `np_rint` builtin function.
pub fn call_numpy_rint<'ctx>(
pub fn call_numpy_rint<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x: (Type, FloatValue<'ctx>),
) -> FloatValue<'ctx> {
x: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_rint";
let llvm_usize = generator.get_size_type(ctx.ctx);
let (x_ty, x) = x;
if !ctx.unifier.unioned(x_ty, ctx.primitives.float) {
unsupported_type(ctx, "np_rint", &[x_ty])
}
Ok(match x.get_type() {
BasicTypeEnum::FloatType(_) => {
debug_assert!(ctx.unifier.unioned(x_ty, ctx.primitives.float));
llvm_intrinsics::call_float_roundeven(ctx, x, None)
llvm_intrinsics::call_float_roundeven(ctx, x.into_float_value(), None).into()
}
BasicTypeEnum::PointerType(_) if x_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray) => {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x_ty);
let ndarray = ndarray_elementwise_unaryop_impl(
generator,
ctx,
elem_ty,
None,
NDArrayValue::from_ptr_val(x.into_pointer_value(), llvm_usize, None),
|generator, ctx, val| {
call_numpy_rint(generator, ctx, (elem_ty, val))
},
)?;
ndarray.as_ptr_value().into()
}
_ => unsupported_type(ctx, FN_NAME, &[x_ty])
})
}
/// Invokes the `np_tan` builtin function.

27
nac3core/src/toplevel/builtins.rs
View File

@ -1514,45 +1514,42 @@ pub fn get_builtins(unifier: &mut Unifier, primitives: &PrimitiveStore) -> Built
unifier,
&var_map,
"np_fabs",
float,
&[(float, "x")],
float_or_ndarray_ty.0,
&[(float_or_ndarray_ty.0, "x")],
Box::new(|ctx, _, fun, args, generator| {
let x_ty = fun.0.args[0].ty;
let x_val = args[0].1.clone()
.to_basic_value_enum(ctx, generator, x_ty)?
.into_float_value();
.to_basic_value_enum(ctx, generator, x_ty)?;
Ok(Some(builtin_fns::call_numpy_fabs(ctx, (x_ty, x_val)).into()))
Ok(Some(builtin_fns::call_numpy_fabs(generator, ctx, (x_ty, x_val))?))
}),
),
create_fn_by_codegen(
unifier,
&var_map,
"np_sqrt",
float,
&[(float, "x")],
float_or_ndarray_ty.0,
&[(float_or_ndarray_ty.0, "x")],
Box::new(|ctx, _, fun, args, generator| {
let x_ty = fun.0.args[0].ty;
let x_val = args[0].1.clone()
.to_basic_value_enum(ctx, generator, x_ty)?
.into_float_value();
.to_basic_value_enum(ctx, generator, x_ty)?;
Ok(Some(builtin_fns::call_numpy_sqrt(ctx, (x_ty, x_val)).into()))
Ok(Some(builtin_fns::call_numpy_sqrt(generator, ctx, (x_ty, x_val))?))
}),
),
create_fn_by_codegen(
unifier,
&var_map,
"np_rint",
float,
&[(float, "x")],
float_or_ndarray_ty.0,
&[(float_or_ndarray_ty.0, "x")],
Box::new(|ctx, _, fun, args, generator| {
let x_ty = fun.0.args[0].ty;
let x_val = args[0].1.clone()
.to_basic_value_enum(ctx, generator, x_ty)?
.into_float_value();
.to_basic_value_enum(ctx, generator, x_ty)?;
Ok(Some(builtin_fns::call_numpy_rint(ctx, (x_ty, x_val)).into()))
Ok(Some(builtin_fns::call_numpy_rint(generator, ctx, (x_ty, x_val))?))
}),
),
create_fn_by_codegen(

24
nac3standalone/demo/src/ndarray.py
View File

@ -837,6 +837,27 @@ def test_ndarray_log2():
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_fabs():
x = -np_identity(2)
y = np_fabs(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_sqrt():
x = np_identity(2)
y = np_sqrt(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_rint():
x = np_identity(2)
y = np_rint(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def run() -> int32:
test_ndarray_ctor()
test_ndarray_empty()
@ -947,5 +968,8 @@ def run() -> int32:
test_ndarray_log()
test_ndarray_log10()
test_ndarray_log2()
test_ndarray_fabs()
test_ndarray_sqrt()
test_ndarray_rint()
return 0