core/ndstrides: implement binop
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cb8cea4286
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@ -12,6 +12,7 @@ use crate::{
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call_int_umin, call_memcpy_generic,
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},
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need_sret, numpy,
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object::ndarray::{NDArrayOut, ScalarOrNDArray},
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stmt::{
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gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
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gen_var,
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@ -28,7 +29,10 @@ use crate::{
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use inkwell::{
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attributes::{Attribute, AttributeLoc},
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types::{AnyType, BasicType, BasicTypeEnum},
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values::{BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue, StructValue},
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values::{
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BasicValue, BasicValueEnum, CallSiteValue, FunctionValue, IntValue, PointerValue,
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StructValue,
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},
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AddressSpace, IntPredicate, OptimizationLevel,
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};
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use itertools::{chain, izip, Either, Itertools};
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@ -1544,99 +1548,71 @@ pub fn gen_binop_expr_with_values<'ctx, G: CodeGenerator>(
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} else if ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
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|| ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id())
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{
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let llvm_usize = generator.get_size_type(ctx.ctx);
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let left =
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ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty1, value: left_val });
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let right =
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ScalarOrNDArray::split_object(generator, ctx, AnyObject { ty: ty2, value: right_val });
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let is_ndarray1 = ty1.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
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let is_ndarray2 = ty2.obj_id(&ctx.unifier).is_some_and(|id| id == PrimDef::NDArray.id());
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// Inhomogeneous binary operations are not supported.
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assert!(ctx.unifier.unioned(left.get_dtype(), right.get_dtype()));
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if is_ndarray1 && is_ndarray2 {
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let (ndarray_dtype1, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty1);
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let (ndarray_dtype2, _) = unpack_ndarray_var_tys(&mut ctx.unifier, ty2);
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let common_dtype = left.get_dtype();
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assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
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let out = match op.variant {
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BinopVariant::Normal => NDArrayOut::NewNDArray { dtype: common_dtype },
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BinopVariant::AugAssign => {
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// If this is an augmented assignment.
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// `left` has to be an ndarray. If it were a scalar then NAC3 simply doesn't support it.
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if let ScalarOrNDArray::NDArray(out_ndarray) = left {
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NDArrayOut::WriteToNDArray { ndarray: out_ndarray }
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} else {
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panic!("left must be an ndarray")
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}
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}
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};
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let left_val =
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NDArrayValue::from_ptr_val(left_val.into_pointer_value(), llvm_usize, None);
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let right_val =
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NDArrayValue::from_ptr_val(right_val.into_pointer_value(), llvm_usize, None);
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let res = if op.base == Operator::MatMult {
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// MatMult is the only binop which is not an elementwise op
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numpy::ndarray_matmul_2d(
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generator,
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ctx,
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ndarray_dtype1,
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match op.variant {
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BinopVariant::Normal => None,
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BinopVariant::AugAssign => Some(left_val),
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},
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left_val,
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right_val,
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)?
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} else {
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numpy::ndarray_elementwise_binop_impl(
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generator,
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ctx,
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ndarray_dtype1,
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match op.variant {
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BinopVariant::Normal => None,
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BinopVariant::AugAssign => Some(left_val),
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},
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(left_val.as_base_value().into(), false),
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(right_val.as_base_value().into(), false),
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|generator, ctx, (lhs, rhs)| {
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gen_binop_expr_with_values(
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generator,
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ctx,
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(&Some(ndarray_dtype1), lhs),
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op,
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(&Some(ndarray_dtype2), rhs),
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ctx.current_loc,
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)?
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.unwrap()
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.to_basic_value_enum(
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ctx,
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generator,
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ndarray_dtype1,
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)
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},
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)?
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};
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Ok(Some(res.as_base_value().into()))
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if op.base == Operator::MatMult {
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// Handle matrix multiplication.
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todo!()
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} else {
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let (ndarray_dtype, _) =
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unpack_ndarray_var_tys(&mut ctx.unifier, if is_ndarray1 { ty1 } else { ty2 });
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let ndarray_val = NDArrayValue::from_ptr_val(
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if is_ndarray1 { left_val } else { right_val }.into_pointer_value(),
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llvm_usize,
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None,
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);
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let res = numpy::ndarray_elementwise_binop_impl(
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// For other operations, they are all elementwise operations.
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// There are only three cases:
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// - LHS is a scalar, RHS is an ndarray.
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// - LHS is an ndarray, RHS is a scalar.
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// - LHS is an ndarray, RHS is an ndarray.
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//
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// For all cases, the scalar operand is promoted to an ndarray,
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// the two are then broadcasted, and starmapped through.
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let left = left.to_ndarray(generator, ctx);
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let right = right.to_ndarray(generator, ctx);
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let result = NDArrayObject::broadcast_starmap(
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generator,
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ctx,
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ndarray_dtype,
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match op.variant {
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BinopVariant::Normal => None,
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BinopVariant::AugAssign => Some(ndarray_val),
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},
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(left_val, !is_ndarray1),
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(right_val, !is_ndarray2),
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|generator, ctx, (lhs, rhs)| {
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gen_binop_expr_with_values(
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&[left, right],
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out,
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|generator, ctx, scalars| {
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let left_value = scalars[0];
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let right_value = scalars[1];
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let result = gen_binop_expr_with_values(
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generator,
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ctx,
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(&Some(ndarray_dtype), lhs),
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(&Some(left.dtype), left_value),
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op,
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(&Some(ndarray_dtype), rhs),
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(&Some(right.dtype), right_value),
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ctx.current_loc,
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)?
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.unwrap()
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.to_basic_value_enum(ctx, generator, ndarray_dtype)
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},
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)?;
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.to_basic_value_enum(ctx, generator, common_dtype)?;
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Ok(Some(res.as_base_value().into()))
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Ok(result)
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},
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)
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.unwrap();
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Ok(Some(ValueEnum::Dynamic(result.instance.value.as_basic_value_enum())))
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}
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} else {
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let left_ty_enum = ctx.unifier.get_ty_immutable(left_ty.unwrap());
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