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ndstrides: [10] Reimplement binops, unary ops, and cmpops. #520

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lyken wants to merge 4 commits from ndstrides-10-ops into ndstrides-9-subassign
pull from: ndstrides-10-ops
merge into: M-Labs:ndstrides-9-subassign
Conversation 1 Commits 4 Files Changed 3 +37 -76
1 changed files with 37 additions and 76 deletions
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113
nac3core/src/codegen/expr.rs
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@ -23,8 +23,8 @@ use nac3parser::ast::{
use super::{ use super::{
classes::{ classes::{
ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, NDArrayValue, ProxyType, ProxyValue, ArrayLikeIndexer, ArrayLikeValue, ListType, ListValue, ProxyType, ProxyValue, RangeValue,
RangeValue, UntypedArrayLikeAccessor, UntypedArrayLikeAccessor,
}, },
concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore}, concrete_type::{ConcreteFuncArg, ConcreteTypeEnum, ConcreteTypeStore},
gen_in_range_check, get_llvm_abi_type, get_llvm_type, get_va_count_arg_name, gen_in_range_check, get_llvm_abi_type, get_llvm_type, get_va_count_arg_name,
@ -34,7 +34,7 @@ use super::{
call_int_umin, call_memcpy_generic, call_int_umin, call_memcpy_generic,
}, },
macros::codegen_unreachable, macros::codegen_unreachable,
need_sret, numpy, need_sret,
object::{ object::{
any::AnyObject, any::AnyObject,
ndarray::{ ndarray::{
@ -50,7 +50,7 @@ use super::{
}; };
use crate::{ use crate::{
symbol_resolver::{SymbolValue, ValueEnum}, symbol_resolver::{SymbolValue, ValueEnum},
toplevel::{helper::PrimDef, numpy::unpack_ndarray_var_tys, DefinitionId, TopLevelDef}, toplevel::{helper::PrimDef, DefinitionId, TopLevelDef},
typecheck::{ typecheck::{
magic_methods::{Binop, BinopVariant, HasOpInfo}, magic_methods::{Binop, BinopVariant, HasOpInfo},
typedef::{FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap}, typedef::{FunSignature, FuncArg, Type, TypeEnum, TypeVarId, Unifier, VarMap},
@ -1850,85 +1850,46 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
if left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) if left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
|| right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) || right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
{ {
let llvm_usize = generator.get_size_type(ctx.ctx); let (Some(left_ty), left) = left else { codegen_unreachable!(ctx) };
let (Some(right_ty), right) = comparators[0] else { codegen_unreachable!(ctx) };
let (Some(left_ty), lhs) = left else { codegen_unreachable!(ctx) };
let (Some(right_ty), rhs) = comparators[0] else { codegen_unreachable!(ctx) };
let op = ops[0]; let op = ops[0];
let is_ndarray1 = let left = AnyObject { value: left, ty: left_ty };
left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()); let left =
let is_ndarray2 = ScalarOrNDArray::split_object(generator, ctx, left).to_ndarray(generator, ctx);
right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
return if is_ndarray1 && is_ndarray2 { let right = AnyObject { value: right, ty: right_ty };
let (ndarray_dtype1, _) = unpack_ndarray_var_tys(&mut ctx.unifier, left_ty); let right =
let (ndarray_dtype2, _) = unpack_ndarray_var_tys(&mut ctx.unifier, right_ty); ScalarOrNDArray::split_object(generator, ctx, right).to_ndarray(generator, ctx);
assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2)); let result_ndarray = NDArrayObject::broadcast_starmap(
generator,
ctx,
&[left, right],
NDArrayOut::NewNDArray { dtype: ctx.primitives.bool },
|generator, ctx, scalars| {
let left_scalar = scalars[0];
let right_scalar = scalars[1];
let left_val = let val = gen_cmpop_expr_with_values(
NDArrayValue::from_ptr_val(lhs.into_pointer_value(), llvm_usize, None); generator,
let res = numpy::ndarray_elementwise_binop_impl( ctx,
generator, (Some(left.dtype), left_scalar),
ctx, &[op],
ctx.primitives.bool, &[(Some(right.dtype), right_scalar)],
None, )?
(left_val.as_base_value().into(), false), .unwrap()
(rhs, false), .to_basic_value_enum(
|generator, ctx, (lhs, rhs)| { ctx,
let val = gen_cmpop_expr_with_values( generator,
generator, ctx.primitives.bool,
ctx, )?;
(Some(ndarray_dtype1), lhs),
&[op],
&[(Some(ndarray_dtype2), rhs)],
)?
.unwrap()
.to_basic_value_enum(
ctx,
generator,
ctx.primitives.bool,
)?;
Ok(generator.bool_to_i8(ctx, val.into_int_value()).into()) Ok(generator.bool_to_i8(ctx, val.into_int_value()).into())
}, },
)?; )?;
Ok(Some(res.as_base_value().into())) return Ok(Some(result_ndarray.instance.value.into()));
} else {
let (ndarray_dtype, _) = unpack_ndarray_var_tys(
&mut ctx.unifier,
if is_ndarray1 { left_ty } else { right_ty },
);
let res = numpy::ndarray_elementwise_binop_impl(
generator,
ctx,
ctx.primitives.bool,
None,
(lhs, !is_ndarray1),
(rhs, !is_ndarray2),
|generator, ctx, (lhs, rhs)| {
let val = gen_cmpop_expr_with_values(
generator,
ctx,
(Some(ndarray_dtype), lhs),
&[op],
&[(Some(ndarray_dtype), rhs)],
)?
.unwrap()
.to_basic_value_enum(
ctx,
generator,
ctx.primitives.bool,
)?;
Ok(generator.bool_to_i8(ctx, val.into_int_value()).into())
},
)?;
Ok(Some(res.as_base_value().into()))
};
} }
} }