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core/ndstrides: implement np_dot() for scalars and 1D

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lyken 2024-08-20 21:18:59 +08:00
parent 70c26561e1
commit 566ce7df50
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GPG Key ID: 3BD5FC6AC8325DD8
2 changed files with 75 additions and 63 deletions
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134
nac3core/src/codegen/numpy.rs
View File

@ -5,7 +5,6 @@ use crate::{
ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter, ProxyType, ProxyValue, TypedArrayLikeAccessor, TypedArrayLikeAdapter,
TypedArrayLikeMutator, UntypedArrayLikeAccessor, UntypedArrayLikeMutator, TypedArrayLikeMutator, UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
}, },
expr::gen_binop_expr_with_values,
irrt::{ irrt::{
calculate_len_for_slice_range, call_ndarray_calc_broadcast, calculate_len_for_slice_range, call_ndarray_calc_broadcast,
call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices, call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices,
@ -15,9 +14,12 @@ use crate::{
model::*, model::*,
object::{ object::{
any::AnyObject, any::AnyObject,
ndarray::{shape_util::parse_numpy_int_sequence, NDArrayObject}, ndarray::{nditer::NDIterHandle, shape_util::parse_numpy_int_sequence, NDArrayObject},
},
stmt::{
gen_for_callback, gen_for_callback_incrementing, gen_for_range_callback,
gen_if_else_expr_callback,
}, },
stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
CodeGenContext, CodeGenerator, CodeGenContext, CodeGenerator,
}, },
symbol_resolver::ValueEnum, symbol_resolver::ValueEnum,
@ -26,21 +28,18 @@ use crate::{
numpy::{make_ndarray_ty, unpack_ndarray_var_tys}, numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
DefinitionId, DefinitionId,
}, },
typecheck::{ typecheck::typedef::{FunSignature, Type},
magic_methods::Binop,
typedef::{FunSignature, Type},
},
}; };
use inkwell::{ use inkwell::{
types::BasicType, types::BasicType,
values::{BasicValueEnum, IntValue, PointerValue}, values::{BasicValueEnum, IntValue, PointerValue},
AddressSpace, IntPredicate, OptimizationLevel, AddressSpace, IntPredicate,
}; };
use inkwell::{ use inkwell::{
types::{AnyTypeEnum, BasicTypeEnum, PointerType}, types::{AnyTypeEnum, BasicTypeEnum, PointerType},
values::BasicValue, values::BasicValue,
}; };
use nac3parser::ast::{Operator, StrRef}; use nac3parser::ast::StrRef;
/// Creates an uninitialized `NDArray` instance. /// Creates an uninitialized `NDArray` instance.
fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>( fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
@ -1708,77 +1707,88 @@ pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
) -> Result<BasicValueEnum<'ctx>, String> { ) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_dot"; const FN_NAME: &str = "ndarray_dot";
let (x1_ty, x1) = x1; let (x1_ty, x1) = x1;
let (_, x2) = x2; let (x2_ty, x2) = x2;
let llvm_usize = generator.get_size_type(ctx.ctx);
match (x1, x2) { match (x1, x2) {
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => { (BasicValueEnum::PointerValue(_), BasicValueEnum::PointerValue(_)) => {
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None); let a = AnyObject { ty: x1_ty, value: x1 };
let n2 = NDArrayValue::from_ptr_val(n2, llvm_usize, None); let b = AnyObject { ty: x2_ty, value: x2 };
let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None)); let a = NDArrayObject::from_object(generator, ctx, a);
let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None)); let b = NDArrayObject::from_object(generator, ctx, b);
// TODO: General `np.dot()` https://numpy.org/doc/stable/reference/generated/numpy.dot.html.
assert_eq!(a.ndims, 1);
assert_eq!(b.ndims, 1);
let common_dtype = a.dtype;
// Check shapes.
let a_size = a.size(generator, ctx);
let b_size = b.size(generator, ctx);
let same_shape = a_size.compare(ctx, IntPredicate::EQ, b_size);
ctx.make_assert( ctx.make_assert(
generator, generator,
ctx.builder.build_int_compare(IntPredicate::EQ, n1_sz, n2_sz, "").unwrap(), same_shape.value,
"0:ValueError", "0:ValueError",
"shapes ({0}), ({1}) not aligned", "shapes ({0},) and ({1},) not aligned: {0} (dim 0) != {1} (dim 1)",
[Some(n1_sz), Some(n2_sz), None], [Some(a_size.value), Some(b_size.value), None],
ctx.current_loc, ctx.current_loc,
); );
let identity = let dtype_llvm = ctx.get_llvm_type(generator, common_dtype);
unsafe { n1.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
let acc = ctx.builder.build_alloca(identity.get_type(), "").unwrap();
ctx.builder.build_store(acc, identity.get_type().const_zero()).unwrap();
gen_for_callback_incrementing( let result = ctx.builder.build_alloca(dtype_llvm, "np_dot_result").unwrap();
ctx.builder.build_store(result, dtype_llvm.const_zero()).unwrap();
// Do dot product.
gen_for_callback(
generator, generator,
ctx, ctx,
None, Some("np_dot"),
llvm_usize.const_zero(), |generator, ctx| {
(n1_sz, false), let a_iter = NDIterHandle::new(generator, ctx, a);
|generator, ctx, _, idx| { let b_iter = NDIterHandle::new(generator, ctx, b);
let elem1 = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) }; Ok((a_iter, b_iter))
let elem2 = unsafe { n2.data().get_unchecked(ctx, generator, &idx, None) }; },
|generator, ctx, (a_iter, _b_iter)| {
// Only a_iter drives the condition, b_iter should have the same status.
Ok(a_iter.has_next(generator, ctx).value)
},
|generator, ctx, _hooks, (a_iter, b_iter)| {
let a_scalar = a_iter.get_scalar(generator, ctx).value;
let b_scalar = b_iter.get_scalar(generator, ctx).value;
let product = match elem1 { let old_result = ctx.builder.build_load(result, "").unwrap();
BasicValueEnum::IntValue(e1) => ctx let new_result: BasicValueEnum<'ctx> = match old_result {
.builder BasicValueEnum::IntValue(old_result) => {
.build_int_mul(e1, elem2.into_int_value(), "") let a_scalar = a_scalar.into_int_value();
.unwrap() let b_scalar = b_scalar.into_int_value();
.as_basic_value_enum(), let x = ctx.builder.build_int_mul(a_scalar, b_scalar, "").unwrap();
BasicValueEnum::FloatValue(e1) => ctx ctx.builder.build_int_add(old_result, x, "").unwrap().into()
.builder }
.build_float_mul(e1, elem2.into_float_value(), "") BasicValueEnum::FloatValue(old_result) => {
.unwrap() let a_scalar = a_scalar.into_float_value();
.as_basic_value_enum(), let b_scalar = b_scalar.into_float_value();
_ => unreachable!(), let x = ctx.builder.build_float_mul(a_scalar, b_scalar, "").unwrap();
ctx.builder.build_float_add(old_result, x, "").unwrap().into()
}
_ => {
panic!("Unrecognized dtype: {}", ctx.unifier.stringify(common_dtype));
}
}; };
let acc_val = ctx.builder.build_load(acc, "").unwrap();
let acc_val = match acc_val {
BasicValueEnum::IntValue(e1) => ctx
.builder
.build_int_add(e1, product.into_int_value(), "")
.unwrap()
.as_basic_value_enum(),
BasicValueEnum::FloatValue(e1) => ctx
.builder
.build_float_add(e1, product.into_float_value(), "")
.unwrap()
.as_basic_value_enum(),
_ => unreachable!(),
};
ctx.builder.build_store(acc, acc_val).unwrap();
ctx.builder.build_store(result, new_result).unwrap();
Ok(()) Ok(())
}, },
llvm_usize.const_int(1, false), |generator, ctx, (a_iter, b_iter)| {
)?; a_iter.next(generator, ctx);
let acc_val = ctx.builder.build_load(acc, "").unwrap(); b_iter.next(generator, ctx);
Ok(acc_val) Ok(())
},
)
.unwrap();
Ok(ctx.builder.build_load(result, "").unwrap())
} }
(BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => { (BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum()) Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())

4
nac3core/src/toplevel/builtins.rs
View File

@ -2052,10 +2052,12 @@ impl<'a> BuiltinBuilder<'a> {
Box::new(move |ctx, _, fun, args, generator| { Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty; let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?; let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty; let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?; let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?)) let result = ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?;
Ok(Some(result))
}), }),
), ),