From bc88819eafb1b945e56e4d1e05fc8fda2de9594d Mon Sep 17 00:00:00 2001 From: lyken Date: Tue, 20 Aug 2024 17:31:55 +0800 Subject: [PATCH] core/ndstrides: implement binop --- nac3core/src/codegen/expr.rs | 136 +++++++++++++++-------------------- 1 file changed, 56 insertions(+), 80 deletions(-) diff --git a/nac3core/src/codegen/expr.rs b/nac3core/src/codegen/expr.rs index f4555885..ffd62781 100644 --- a/nac3core/src/codegen/expr.rs +++ b/nac3core/src/codegen/expr.rs @@ -13,6 +13,7 @@ use crate::{ }, macros::codegen_unreachable, need_sret, numpy, + object::ndarray::{NDArrayOut, ScalarOrNDArray}, stmt::{ gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise, gen_var, @@ -29,7 +30,10 @@ use crate::{ use inkwell::{ attributes::{Attribute, AttributeLoc}, types::{AnyType, BasicType, BasicTypeEnum}, - values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, StructValue}, + values::{ + BasicValue, BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, + StructValue, + }, AddressSpace, IntPredicate, OptimizationLevel, }; use itertools::{chain, izip, Either, Itertools}; @@ -1543,99 +1547,71 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>( } else if ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) || ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()) { - let llvm_usize = generator.get_size_type(ctx.ctx); + let left = + ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty1, value: left_val }); + let right = + ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty2, value: right_val }); - let is_ndarray1 = ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()); - let is_ndarray2 = ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id()); + // Inhomogeneous binary operations are not supported. + assert!(ctx.unifier.unioned(left.get_dtype(), right.get_dtype())); - if is_ndarray1 && is_ndarray2 { - let (ndarray_dtype1, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty1); - let (ndarray_dtype2, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty2); + let common_dtype = left.get_dtype(); - assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2)); + let out = match op.variant { + BinopVariant::Normal => NDArrayOut::NewNDArray { dtype: common_dtype }, + BinopVariant::AugAssign => { + // If this is an augmented assignment. + // `left` has to be an ndarray. If it were a scalar then NAC3 simply doesn't support it. + if let ScalarOrNDArray::NDArray(out_ndarray) = left { + NDArrayOut::WriteToNDArray { ndarray: out_ndarray } + } else { + panic!("left must be an ndarray") + } + } + }; - let left_val = - NDArrayValue::from_ptr_val(left_val.into_pointer_value(), llvm_usize, None); - let right_val = - NDArrayValue::from_ptr_val(right_val.into_pointer_value(), llvm_usize, None); - - let res = if op.base == Operator::MatMult { - // MatMult is the only binop which is not an elementwise op - numpy::ndarray_matmul_2d( - generator, - ctx, - ndarray_dtype1, - match op.variant { - BinopVariant::Normal => None, - BinopVariant::AugAssign => Some(left_val), - }, - left_val, - right_val, - )? - } else { - numpy::ndarray_elementwise_binop_impl( - generator, - ctx, - ndarray_dtype1, - match op.variant { - BinopVariant::Normal => None, - BinopVariant::AugAssign => Some(left_val), - }, - (left_val.as_base_value().into(), false), - (right_val.as_base_value().into(), false), - |generator, ctx, (lhs, rhs)| { - gen_binop_expr_with_values( - generator, - ctx, - (&Some(ndarray_dtype1), lhs), - op, - (&Some(ndarray_dtype2), rhs), - ctx.current_loc, - )? - .unwrap() - .to_basic_value_enum( - ctx, - generator, - ndarray_dtype1, - ) - }, - )? - }; - - Ok(Some(res.as_base_value().into())) + if op.base == Operator::MatMult { + // Handle matrix multiplication. + todo!() } else { - let (ndarray_dtype, _) = - unpack_ndarray_var_tys(&mut ctx.unifier, if is_ndarray1 { ty1 } else { ty2 }); - let ndarray_val = NDArrayValue::from_ptr_val( - if is_ndarray1 { left_val } else { right_val }.into_pointer_value(), - llvm_usize, - None, - ); - let res = numpy::ndarray_elementwise_binop_impl( + // For other operations, they are all elementwise operations. + + // There are only three cases: + // - LHS is a scalar, RHS is an ndarray. + // - LHS is an ndarray, RHS is a scalar. + // - LHS is an ndarray, RHS is an ndarray. + // + // For all cases, the scalar operand is promoted to an ndarray, + // the two are then broadcasted, and starmapped through. + + let left = left.to_ndarray(generator, ctx); + let right = right.to_ndarray(generator, ctx); + + let result = NDArrayObject::broadcast_starmap( generator, ctx, - ndarray_dtype, - match op.variant { - BinopVariant::Normal => None, - BinopVariant::AugAssign => Some(ndarray_val), - }, - (left_val, !is_ndarray1), - (right_val, !is_ndarray2), - |generator, ctx, (lhs, rhs)| { - gen_binop_expr_with_values( + &[left, right], + out, + |generator, ctx, scalars| { + let left_value = scalars[0]; + let right_value = scalars[1]; + + let result = gen_binop_expr_with_values( generator, ctx, - (&Some(ndarray_dtype), lhs), + (&Some(left.dtype), left_value), op, - (&Some(ndarray_dtype), rhs), + (&Some(right.dtype), right_value), ctx.current_loc, )? .unwrap() - .to_basic_value_enum(ctx, generator, ndarray_dtype) - }, - )?; + .to_basic_value_enum(ctx, generator, common_dtype)?; - Ok(Some(res.as_base_value().into())) + Ok(result) + }, + ) + .unwrap(); + Ok(Some(ValueEnum::Dynamic(result.instance.value.as_basic_value_enum()))) } } else { let left_ty_enum = ctx.unifier.get_ty_immutable(left_ty.unwrap());