ndstrides: [9] Implement ndarray subscript assignment #519

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lyken wants to merge 2 commits from ndstrides-9-subassign into ndstrides-8-transpose
2 changed files with 130 additions and 2 deletions

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@ -18,7 +18,7 @@ use crate::{
CodeGenContext, CodeGenerator, CodeGenContext, CodeGenerator,
}, },
toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys}, toplevel::{helper::extract_ndims, numpy::unpack_ndarray_var_tys},
typecheck::typedef::Type, typecheck::typedef::{Type, TypeEnum},
}; };
pub mod array; pub mod array;
@ -483,6 +483,22 @@ impl<'ctx> NDArrayObject<'ctx> {
TupleObject::from_objects(generator, ctx, objects) TupleObject::from_objects(generator, ctx, objects)
} }
/// Create an unsized ndarray to contain `object`.
pub fn make_unsized<G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
object: AnyObject<'ctx>,
) -> NDArrayObject<'ctx> {
// We have to put the value on the stack to get a data pointer.
let data = ctx.builder.build_alloca(object.value.get_type(), "make_unsized").unwrap();
ctx.builder.build_store(data, object.value).unwrap();
let data = Ptr(Int(Byte)).pointer_cast(generator, ctx, data);
let ndarray = NDArrayObject::alloca(generator, ctx, object.ty, 0);
ndarray.instance.set(ctx, |f| f.data, data);
ndarray
}
} }
/// A convenience enum for implementing functions that acts on scalars or ndarrays or both. /// A convenience enum for implementing functions that acts on scalars or ndarrays or both.
@ -492,7 +508,50 @@ pub enum ScalarOrNDArray<'ctx> {
NDArray(NDArrayObject<'ctx>), NDArray(NDArrayObject<'ctx>),
} }
impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for AnyObject<'ctx> {
type Error = ();
fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
match value {
ScalarOrNDArray::Scalar(scalar) => Ok(*scalar),
ScalarOrNDArray::NDArray(_ndarray) => Err(()),
}
}
}
impl<'ctx> TryFrom<&ScalarOrNDArray<'ctx>> for NDArrayObject<'ctx> {
type Error = ();
fn try_from(value: &ScalarOrNDArray<'ctx>) -> Result<Self, Self::Error> {
match value {
ScalarOrNDArray::Scalar(_scalar) => Err(()),
ScalarOrNDArray::NDArray(ndarray) => Ok(*ndarray),
}
}
}
impl<'ctx> ScalarOrNDArray<'ctx> { impl<'ctx> ScalarOrNDArray<'ctx> {
/// Split on `object` either into a scalar or an ndarray.
///
/// If `object` is an ndarray, [`ScalarOrNDArray::NDArray`].
///
/// For everything else, it is wrapped with [`ScalarOrNDArray::Scalar`].
pub fn split_object<G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
object: AnyObject<'ctx>,
) -> ScalarOrNDArray<'ctx> {
match &*ctx.unifier.get_ty(object.ty) {
TypeEnum::TObj { obj_id, .. }
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
{
let ndarray = NDArrayObject::from_object(generator, ctx, object);
ScalarOrNDArray::NDArray(ndarray)
}
_ => ScalarOrNDArray::Scalar(object),
}
}
/// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`]. /// Get the underlying [`BasicValueEnum<'ctx>`] of this [`ScalarOrNDArray`].
#[must_use] #[must_use]
pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> { pub fn to_basic_value_enum(self) -> BasicValueEnum<'ctx> {
@ -501,4 +560,27 @@ impl<'ctx> ScalarOrNDArray<'ctx> {
ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(), ScalarOrNDArray::NDArray(ndarray) => ndarray.instance.value.as_basic_value_enum(),
} }
} }
/// Convert this [`ScalarOrNDArray`] to an ndarray - behaves like `np.asarray`.
/// - If this is an ndarray, the ndarray is returned.
/// - If this is a scalar, this function returns new ndarray created with [`NDArrayObject::make_unsized`].
pub fn to_ndarray<G: CodeGenerator + ?Sized>(
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
) -> NDArrayObject<'ctx> {
match self {
ScalarOrNDArray::NDArray(ndarray) => *ndarray,
ScalarOrNDArray::Scalar(scalar) => NDArrayObject::make_unsized(generator, ctx, *scalar),
}
}
/// Get the dtype of the ndarray created if this were called with [`ScalarOrNDArray::to_ndarray`].
#[must_use]
pub fn get_dtype(&self) -> Type {
match self {
ScalarOrNDArray::NDArray(ndarray) => ndarray.dtype,
ScalarOrNDArray::Scalar(scalar) => scalar.ty,
}
}
} }

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@ -17,6 +17,12 @@ use super::{
gen_in_range_check, gen_in_range_check,
irrt::{handle_slice_indices, list_slice_assignment}, irrt::{handle_slice_indices, list_slice_assignment},
macros::codegen_unreachable, macros::codegen_unreachable,
object::{
any::AnyObject,
ndarray::{
indexing::util::gen_ndarray_subscript_ndindices, NDArrayObject, ScalarOrNDArray,
},
},
CodeGenContext, CodeGenerator, CodeGenContext, CodeGenerator,
}; };
use crate::{ use crate::{
@ -411,7 +417,47 @@ pub fn gen_setitem<'ctx, G: CodeGenerator>(
if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() => if *obj_id == ctx.primitives.ndarray.obj_id(&ctx.unifier).unwrap() =>
{ {
// Handle NDArray item assignment // Handle NDArray item assignment
todo!("ndarray subscript assignment is not yet implemented"); // Process target
let target = generator
.gen_expr(ctx, target)?
.unwrap()
.to_basic_value_enum(ctx, generator, target_ty)?;
let target = AnyObject { value: target, ty: target_ty };
// Process key
let key = gen_ndarray_subscript_ndindices(generator, ctx, key)?;
// Process value
let value = value.to_basic_value_enum(ctx, generator, value_ty)?;
let value = AnyObject { value, ty: value_ty };
/*
Reference code:
```python
target = target[key]
value = np.asarray(value)
shape = np.broadcast_shape((target, value))
target = np.broadcast_to(target, shape)
value = np.broadcast_to(value, shape)
...and finally copy 1-1 from value to target.
```
*/
let target = NDArrayObject::from_object(generator, ctx, target);
let target = target.index(generator, ctx, &key);
let value =
ScalarOrNDArray::split_object(generator, ctx, value).to_ndarray(generator, ctx);
let broadcast_result = NDArrayObject::broadcast(generator, ctx, &[target, value]);
let target = broadcast_result.ndarrays[0];
let value = broadcast_result.ndarrays[1];
target.copy_data_from(generator, ctx, value);
} }
_ => { _ => {
panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty)); panic!("encountered unknown target type: {}", ctx.unifier.stringify(target_ty));