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Author SHA1 Message Date
David Mak b461cdccb6 WIP 2024-11-22 00:00:20 +08:00
David Mak a370a52658 [core] WIP - Implemented construct_* for NDArrays 2024-11-22 00:00:20 +08:00
David Mak 7753057e22 [core] Add itemsize and strides to NDArray struct 2024-11-22 00:00:20 +08:00
10 changed files with 123 additions and 296 deletions

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@ -15,10 +15,9 @@ use pyo3::{
use nac3core::{
codegen::{
expr::{destructure_range, gen_call},
irrt::ndarray::call_ndarray_calc_size,
irrt::call_ndarray_calc_size,
llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
type_aligned_alloca,
types::{NDArrayType, ProxyType},
values::{
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, ProxyValue,
@ -643,12 +642,27 @@ fn format_rpc_ret<'ctx>(
// (4 + 4 * ndims) bytes with 8-byte alignment
let sizeof_dims =
ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
let buffer_size =
let unaligned_buffer_size =
ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
let stackptr = call_stacksave(ctx, None);
let buffer =
type_aligned_alloca(generator, ctx, llvm_i8_8, buffer_size, Some("rpc.buffer"));
// Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
let buffer = ctx
.builder
.build_array_alloca(
llvm_i8_8,
ctx.builder
.build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
.unwrap(),
"rpc.buffer",
)
.unwrap();
let buffer = ctx
.builder
.build_bit_cast(buffer, llvm_pi8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap();
let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
// The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
@ -722,7 +736,7 @@ fn format_rpc_ret<'ctx>(
}
unsafe {
ndarray.create_data(generator, ctx, num_elements);
ndarray.create_data(generator, ctx, llvm_elem_ty, num_elements);
}
let ndarray_data = ndarray.data().base_ptr(ctx, generator);

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@ -923,8 +923,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let n = NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None);
let n_sz =
irrt::ndarray::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
let n_sz_eqz = ctx
.builder

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@ -32,7 +32,7 @@ use super::{
gen_for_callback_incrementing, gen_if_callback, gen_if_else_expr_callback, gen_raise,
gen_var,
},
types::{ListType, NDArrayType, ProxyType},
types::{ListType, ProxyType},
values::{
ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue, RangeValue,
TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
@ -43,7 +43,7 @@ use crate::{
symbol_resolver::{SymbolValue, ValueEnum},
toplevel::{
helper::PrimDef,
numpy::unpack_ndarray_var_tys,
numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
DefinitionId, TopLevelDef,
},
typecheck::{
@ -2595,6 +2595,14 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
_ => 1,
};
let ndarray_ndims_ty = ctx.unifier.get_fresh_literal(
ndims.iter().map(|v| SymbolValue::U64(v - subscripted_dims)).collect(),
None,
);
let ndarray_ty =
make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(ty), Some(ndarray_ndims_ty));
let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
let llvm_ndarray_data_t = ctx.get_llvm_type(generator, ty).as_basic_type_enum();
let sizeof_elem = llvm_ndarray_data_t.size_of().unwrap();
@ -2789,15 +2797,26 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
let num_dims = v.load_ndims(ctx);
let num_dims = ctx.builder
.build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
.unwrap();
// Create a new array, remove the top dimension from the dimension-size-list, and copy the
// elements over
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_ndarray_data_t)
.construct_uninitialized(generator, ctx, num_dims, None);
let subscripted_ndarray =
generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
let ndarray = NDArrayValue::from_pointer_value(
subscripted_ndarray,
llvm_ndarray_data_t,
None,
llvm_usize,
None,
);
let num_dims = v.load_ndims(ctx);
ndarray.store_ndims(
ctx,
generator,
ctx.builder
.build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
.unwrap(),
);
let ndarray_num_dims = ndarray.load_ndims(ctx);
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
@ -2829,7 +2848,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
llvm_i1.const_zero(),
);
let ndarray_num_elems = ndarray::call_ndarray_calc_size(
let ndarray_num_elems = call_ndarray_calc_size(
generator,
ctx,
&ndarray.shape().as_slice_value(ctx, generator),
@ -2840,7 +2859,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
.build_int_z_extend_or_bit_cast(ndarray_num_elems, sizeof_elem.get_type(), "")
.unwrap();
unsafe {
ndarray.create_data(generator, ctx, ndarray_num_elems);
ndarray.create_data(generator, ctx, llvm_ndarray_data_t, ndarray_num_elems);
}
let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
@ -3599,7 +3618,10 @@ pub fn create_fn_and_call<'ctx>(
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
) -> Option<BasicValueEnum<'ctx>> {
let intrinsic_fn = ctx.module.get_function(fn_name).unwrap_or_else(|| {
let params = params.iter().copied().map(BasicTypeEnum::into).collect_vec();
let params = params.iter()
.copied()
.map(BasicTypeEnum::into)
.collect_vec();
let fn_type = if let Some(ret_type) = ret_type {
ret_type.fn_type(params.as_slice(), is_var_args)
} else {
@ -3613,7 +3635,10 @@ pub fn create_fn_and_call<'ctx>(
configure(&intrinsic_fn);
}
let args = args.iter().copied().map(BasicValueEnum::into).collect_vec();
let args = args.iter()
.copied()
.map(BasicValueEnum::into)
.collect_vec();
ctx.builder
.build_call(intrinsic_fn, args.as_slice(), call_value_name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
@ -3624,7 +3649,7 @@ pub fn create_fn_and_call<'ctx>(
/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
///
/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
/// parameters and arguments to be specified as tuples to better indicate the expected type and
/// parameters and arguments to be specified as tuples to better indicate the expected type and
/// actual value of each parameter-argument pair of the call.
pub fn create_and_call_function<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
@ -3635,8 +3660,7 @@ pub fn create_and_call_function<'ctx>(
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
) -> Option<BasicValueEnum<'ctx>> {
let param_tys = params.iter().map(|(ty, _)| ty).copied().map(BasicTypeEnum::into).collect_vec();
let arg_values =
params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
let arg_values = params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
create_fn_and_call(
ctx,
@ -3662,7 +3686,9 @@ pub fn infer_and_call_function<'ctx>(
value_name: Option<&str>,
configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
) -> Option<BasicValueEnum<'ctx>> {
let param_tys = args.iter().map(BasicValueEnum::get_type).collect_vec();
let param_tys = args.iter()
.map(BasicValueEnum::get_type)
.collect_vec();
create_fn_and_call(
ctx,

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@ -13,11 +13,12 @@ use super::{CodeGenContext, CodeGenerator};
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
pub use list::*;
pub use math::*;
pub use ndarray::*;
pub use slice::*;
mod list;
mod math;
pub mod ndarray;
mod ndarray;
mod slice;
#[must_use]

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@ -201,52 +201,6 @@ pub fn call_memcpy_generic<'ctx>(
call_memcpy(ctx, dest, src, len, is_volatile);
}
/// Invokes the `llvm.memcpy` intrinsic.
///
/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
/// Moreover, `len` now refers to the number of elements (rather than bytes) to copy.
pub fn call_memcpy_generic_array<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
dest: PointerValue<'ctx>,
src: PointerValue<'ctx>,
len: IntValue<'ctx>,
is_volatile: IntValue<'ctx>,
) {
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
let dest_elem_t = dest.get_type().get_element_type();
let src_elem_t = src.get_type().get_element_type();
let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
dest
} else {
ctx.builder
.build_bit_cast(dest, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
src
} else {
ctx.builder
.build_bit_cast(src, llvm_p0i8, "")
.map(BasicValueEnum::into_pointer_value)
.unwrap()
};
let len = ctx.builder.build_int_cast(len, llvm_sizeof_expr_t, "").unwrap();
let len = ctx.builder.build_int_mul(
len,
src_elem_t.size_of().unwrap(),
""
).unwrap();
call_memcpy(ctx, dest, src, len, is_volatile);
}
/// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
///
/// Arguments:
@ -389,25 +343,3 @@ pub fn call_float_powi<'ctx>(
.map(Either::unwrap_left)
.unwrap()
}
/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
pub fn call_int_ctpop<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
src: IntValue<'ctx>,
name: Option<&str>,
) -> IntValue<'ctx> {
const FN_NAME: &str = "llvm.ctpop";
let llvm_src_t = src.get_type();
let intrinsic_fn = Intrinsic::find(FN_NAME)
.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
.unwrap();
ctx.builder
.build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
.map(CallSiteValue::try_as_basic_value)
.map(|v| v.map_left(BasicValueEnum::into_int_value))
.map(Either::unwrap_left)
.unwrap()
}

View File

@ -1119,106 +1119,3 @@ fn gen_in_range_check<'ctx>(
fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
format!("__{}_va_count", &arg_name).into()
}
/// Returns the alignment of the type.
///
/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
match ty.into() {
BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
BasicTypeEnum::IntType(ty) => ty.get_alignment(),
BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
BasicTypeEnum::StructType(ty) => ty.get_alignment(),
BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
}
}
/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
/// given type.
///
/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
/// aligned with the alignment of `align_ty`.
pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
align_ty: impl Into<BasicTypeEnum<'ctx>>,
size: IntValue<'ctx>,
name: Option<&str>,
) -> PointerValue<'ctx> {
/// Round `val` up to its modulo `power_of_two`.
fn round_up<'ctx>(
ctx: &CodeGenContext<'ctx, '_>,
val: IntValue<'ctx>,
power_of_two: IntValue<'ctx>,
) -> IntValue<'ctx> {
debug_assert_eq!(
val.get_type().get_bit_width(),
power_of_two.get_type().get_bit_width(),
"`val` ({}) and `power_of_two` ({}) must be the same type",
val.get_type(),
power_of_two.get_type(),
);
let llvm_val_t = val.get_type();
let max_rem =
ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
ctx.builder
.build_and(
ctx.builder.build_int_add(val, max_rem, "").unwrap(),
ctx.builder.build_not(max_rem, "").unwrap(),
"",
)
.unwrap()
}
let llvm_i8 = ctx.ctx.i8_type();
let llvm_pi8 = llvm_i8.ptr_type(AddressSpace::default());
let llvm_usize = generator.get_size_type(ctx.ctx);
let align_ty = align_ty.into();
let size = ctx.builder.build_int_cast(size, llvm_usize, "").unwrap();
debug_assert_eq!(
size.get_type().get_bit_width(),
llvm_usize.get_bit_width(),
"Expected size_t ({}) for parameter `size` of `aligned_alloca`, got {}",
llvm_usize,
size.get_type(),
);
let alignment = get_type_alignment(align_ty);
let alignment = ctx.builder.build_int_cast(alignment, llvm_usize, "").unwrap();
if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
let alignment_bitcount = llvm_intrinsics::call_int_ctpop(ctx, alignment, None);
ctx.make_assert(
generator,
ctx.builder
.build_int_compare(
IntPredicate::EQ,
alignment_bitcount,
alignment_bitcount.get_type().const_int(1, false),
"",
)
.unwrap(),
"0:AssertionError",
"Expected power-of-two alignment for aligned_alloca, got {0}",
[Some(alignment), None, None],
ctx.current_loc,
);
}
let buffer_size = round_up(ctx, size, alignment);
let aligned_slices = ctx.builder.build_int_unsigned_div(buffer_size, alignment, "").unwrap();
// Just to be absolutely sure, alloca in [i8 x alignment] slices
let buffer = ctx.builder.build_array_alloca(align_ty, aligned_slices, "").unwrap();
ctx.builder
.build_bit_cast(buffer, llvm_pi8, name.unwrap_or_default())
.map(BasicValueEnum::into_pointer_value)
.unwrap()
}

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@ -10,11 +10,8 @@ use nac3parser::ast::{Operator, StrRef};
use super::{
expr::gen_binop_expr_with_values,
irrt::{
calculate_len_for_slice_range,
ndarray::{
call_ndarray_calc_broadcast, call_ndarray_calc_broadcast_index,
call_ndarray_calc_nd_indices, call_ndarray_calc_size,
},
calculate_len_for_slice_range, call_ndarray_calc_broadcast,
call_ndarray_calc_broadcast_index, call_ndarray_calc_nd_indices, call_ndarray_calc_size,
},
llvm_intrinsics::{self, call_memcpy_generic},
macros::codegen_unreachable,
@ -41,7 +38,6 @@ use crate::{
};
/// Creates an uninitialized `NDArray` instance.
#[deprecated = "Use NDArrayType::construct_uninitialized instead."]
fn create_ndarray_uninitialized<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -85,7 +81,6 @@ where
) -> Result<IntValue<'ctx>, String>,
{
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
// Assert that all dimensions are non-negative
let shape_len = shape_len_fn(generator, ctx, shape)?;
@ -125,10 +120,10 @@ where
llvm_usize.const_int(1, false),
)?;
let num_dims = shape_len_fn(generator, ctx, shape)?;
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty)
.construct_uninitialized(generator, ctx, num_dims, None);
let num_dims = shape_len_fn(generator, ctx, shape)?;
ndarray.store_ndims(ctx, generator, num_dims);
let ndarray_num_dims = ndarray.load_ndims(ctx);
ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
@ -218,7 +213,7 @@ fn ndarray_init_data<'ctx, G: CodeGenerator + ?Sized>(
(None, None),
);
unsafe {
ndarray.create_data(generator, ctx, ndarray_num_elems);
ndarray.create_data(generator, ctx, llvm_ndarray_data_t, ndarray_num_elems);
}
ndarray
@ -1266,7 +1261,6 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
) -> Result<NDArrayValue<'ctx>, String> {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let ndarray = if slices.is_empty() {
create_ndarray_dyn_shape(
@ -1280,8 +1274,8 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
},
)?
} else {
let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_elem_ty)
.construct_uninitialized(generator, ctx, this.load_ndims(ctx), None);
let ndarray = create_ndarray_uninitialized(generator, ctx, elem_ty)?;
ndarray.store_ndims(ctx, generator, this.load_ndims(ctx));
let ndims = this.load_ndims(ctx);
ndarray.create_shape(ctx, llvm_usize, ndims);

View File

@ -82,7 +82,7 @@ impl<'ctx> NDArrayType<'ctx> {
Ok(())
}
// TODO: Move this as a member of this Struct
// TODO: Move this into e.g. StructProxyType
#[must_use]
fn fields(
ctx: impl AsContextRef<'ctx>,
@ -189,20 +189,22 @@ impl<'ctx> NDArrayType<'ctx> {
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
// ndims: u64,
ndims: IntValue<'ctx>,
ndims: u64,
name: Option<&'ctx str>,
) -> <Self as ProxyType<'ctx>>::Value {
let ndarray = self.new_value(generator, ctx, name);
let itemsize =
ctx.builder.build_int_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "").unwrap();
let itemsize = ctx
.builder
.build_int_z_extend_or_bit_cast(self.dtype.size_of().unwrap(), self.llvm_usize, "")
.unwrap();
ndarray.store_itemsize(ctx, generator, itemsize);
ndarray.store_ndims(ctx, generator, ndims);
let ndims_val = self.llvm_usize.const_int(ndims, false);
ndarray.store_ndims(ctx, generator, ndims_val);
ndarray.create_shape(ctx, self.llvm_usize, ndims);
ndarray.create_strides(ctx, self.llvm_usize, ndims);
ndarray.create_shape(ctx, self.llvm_usize, ndims_val);
ndarray.create_strides(ctx, self.llvm_usize, ndims_val);
ndarray
}
@ -218,14 +220,7 @@ impl<'ctx> NDArrayType<'ctx> {
shape: &[u64],
name: Option<&'ctx str>,
) -> <Self as ProxyType<'ctx>>::Value {
let llvm_usize = generator.get_size_type(ctx.ctx);
let ndarray = self.construct_uninitialized(
generator,
ctx,
llvm_usize.const_int(shape.len() as u64, false),
name,
);
let ndarray = self.construct_uninitialized(generator, ctx, shape.len() as u64, name);
// Write shape
let ndarray_shape = ndarray.shape();
@ -255,14 +250,7 @@ impl<'ctx> NDArrayType<'ctx> {
shape: &[IntValue<'ctx>],
name: Option<&'ctx str>,
) -> <Self as ProxyType<'ctx>>::Value {
let llvm_usize = generator.get_size_type(ctx.ctx);
let ndarray = self.construct_uninitialized(
generator,
ctx,
llvm_usize.const_int(shape.len() as u64, false),
name,
);
let ndarray = self.construct_uninitialized(generator, ctx, shape.len() as u64, name);
// Write shape
let ndarray_shape = ndarray.shape();

View File

@ -145,7 +145,7 @@ where
}
/// Sets the value of this field for a given `obj`.
pub fn set_for_value(&self, obj: StructValue<'ctx>, value: Value) {
pub fn set_from_value(&self, obj: StructValue<'ctx>, value: Value) {
obj.set_field_at_index(self.index, value);
}

View File

@ -9,11 +9,10 @@ use super::{
UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
};
use crate::codegen::{
irrt,
llvm_intrinsics::{call_int_umin, call_memcpy_generic_array},
irrt::{call_ndarray_calc_size, call_ndarray_flatten_index},
llvm_intrinsics::call_int_umin,
stmt::gen_for_callback_incrementing,
type_aligned_alloca,
types::{structure::StructField, NDArrayType},
types::NDArrayType,
CodeGenContext, CodeGenerator,
};
@ -78,10 +77,12 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
}
fn itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> StructField<'ctx, IntValue<'ctx>> {
/// Returns the pointer to the field storing the size of each element of this `NDArray`.
fn ptr_to_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
self.get_type()
.get_fields(ctx.ctx, self.llvm_usize)
.itemsize
.ptr_by_gep(ctx, self.value, self.name)
}
/// Stores the size of each element `itemsize` into this instance.
@ -89,16 +90,18 @@ impl<'ctx> NDArrayValue<'ctx> {
&self,
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
itemsize: IntValue<'ctx>,
ndims: IntValue<'ctx>,
) {
debug_assert_eq!(itemsize.get_type(), generator.get_size_type(ctx.ctx));
debug_assert_eq!(ndims.get_type(), generator.get_size_type(ctx.ctx));
self.itemsize(ctx).set(ctx, self.value, itemsize, self.name);
let pndims = self.ptr_to_ndims(ctx);
ctx.builder.build_store(pndims, ndims).unwrap();
}
/// Returns the size of each element of this `NDArray` as a value.
pub fn load_itemsize(&self, ctx: &CodeGenContext<'ctx, '_>) -> IntValue<'ctx> {
self.itemsize(ctx).get(ctx, self.value, self.name)
let pndims = self.ptr_to_ndims(ctx);
ctx.builder.build_load(pndims, "").map(BasicValueEnum::into_int_value).unwrap()
}
/// Returns the double-indirection pointer to the `shape` array, as if by calling
@ -142,7 +145,7 @@ impl<'ctx> NDArrayValue<'ctx> {
/// Stores the array of dimension sizes `dims` into this instance.
fn store_strides(&self, ctx: &CodeGenContext<'ctx, '_>, dims: PointerValue<'ctx>) {
ctx.builder.build_store(self.ptr_to_strides(ctx), dims).unwrap();
ctx.builder.build_store(self.ptr_to_shape(ctx), dims).unwrap();
}
/// Convenience method for creating a new array storing the stride with the given `size`.
@ -152,7 +155,7 @@ impl<'ctx> NDArrayValue<'ctx> {
llvm_usize: IntType<'ctx>,
size: IntValue<'ctx>,
) {
self.store_strides(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
self.store_shape(ctx, ctx.builder.build_array_alloca(llvm_usize, size, "").unwrap());
}
/// Returns a proxy object to the field storing the stride of each dimension of this `NDArray`.
@ -190,17 +193,16 @@ impl<'ctx> NDArrayValue<'ctx> {
pub unsafe fn create_data<G: CodeGenerator + ?Sized>(
&self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ctx: &CodeGenContext<'ctx, '_>,
elem_ty: BasicTypeEnum<'ctx>,
size: IntValue<'ctx>,
) {
// let itemsize =
// ctx.builder.build_int_cast(self.load_itemsize(ctx), size.get_type(), "").unwrap();
let itemsize =
ctx.builder.build_int_cast(self.dtype.size_of().unwrap(), size.get_type(), "").unwrap();
ctx.builder.build_int_cast(elem_ty.size_of().unwrap(), size.get_type(), "").unwrap();
let nbytes = ctx.builder.build_int_mul(size, itemsize, "").unwrap();
// let nbytes = self.nbytes(generator, ctx);
let data = type_aligned_alloca(generator, ctx, self.dtype, nbytes, None);
// TODO: What about alignment?
let data = ctx.builder.build_array_alloca(ctx.ctx.i8_type(), nbytes, "").unwrap();
self.store_data(ctx, data);
// self.set_strides_contiguous(generator, ctx);
@ -219,15 +221,7 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx: &mut CodeGenContext<'ctx, '_>,
shape: PointerValue<'ctx>,
) {
let num_items = self.load_ndims(ctx);
call_memcpy_generic_array(
ctx,
self.shape().base_ptr(ctx, generator),
shape,
num_items,
ctx.ctx.bool_type().const_zero(),
);
todo!()
}
/// Copy shape dimensions from an ndarray.
@ -238,9 +232,7 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx: &mut CodeGenContext<'ctx, '_>,
src_ndarray: NDArrayValue<'ctx>,
) {
assert_eq!(self.ndims, src_ndarray.ndims);
let src_shape = src_ndarray.shape().base_ptr(ctx, generator);
self.copy_shape_from_array(generator, ctx, src_shape);
todo!()
}
/// Copy strides dimensions from an array.
@ -250,15 +242,7 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx: &mut CodeGenContext<'ctx, '_>,
strides: PointerValue<'ctx>,
) {
let num_items = self.load_ndims(ctx);
call_memcpy_generic_array(
ctx,
self.strides().base_ptr(ctx, generator),
strides,
num_items,
ctx.ctx.bool_type().const_zero(),
);
todo!()
}
/// Copy strides dimensions from an ndarray.
@ -269,9 +253,7 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx: &mut CodeGenContext<'ctx, '_>,
src_ndarray: NDArrayValue<'ctx>,
) {
assert_eq!(self.ndims, src_ndarray.ndims);
let src_strides = src_ndarray.strides().base_ptr(ctx, generator);
self.copy_strides_from_array(generator, ctx, src_strides);
todo!()
}
/// Get the `np.size()` of this ndarray.
@ -280,7 +262,7 @@ impl<'ctx> NDArrayValue<'ctx> {
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
) -> IntValue<'ctx> {
irrt::ndarray::call_nac3_ndarray_size(generator, ctx, *self)
todo!()
}
/// Get the `ndarray.nbytes` of this ndarray.
@ -289,7 +271,7 @@ impl<'ctx> NDArrayValue<'ctx> {
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
) -> IntValue<'ctx> {
irrt::ndarray::call_nac3_ndarray_nbytes(generator, ctx, *self)
todo!()
}
/// Get the `len()` of this ndarray.
@ -298,7 +280,7 @@ impl<'ctx> NDArrayValue<'ctx> {
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
) -> IntValue<'ctx> {
irrt::ndarray::call_nac3_ndarray_len(generator, ctx, *self)
todo!()
}
/// Check if this ndarray is C-contiguous.
@ -309,18 +291,18 @@ impl<'ctx> NDArrayValue<'ctx> {
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
) -> IntValue<'ctx> {
irrt::ndarray::call_nac3_ndarray_is_c_contiguous(generator, ctx, *self)
todo!()
}
/// Call [`call_nac3_ndarray_set_strides_by_shape`] on this ndarray to update `strides`.
///
/// Update the ndarray's strides to make the ndarray contiguous.
pub fn set_strides_contiguous<G: CodeGenerator + ?Sized>(
&self,
self,
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
ctx: &CodeGenContext<'ctx, '_>,
) {
irrt::ndarray::call_nac3_ndarray_set_strides_by_shape(generator, ctx, *self);
todo!()
}
/// Copy data from another ndarray.
@ -335,8 +317,7 @@ impl<'ctx> NDArrayValue<'ctx> {
ctx: &mut CodeGenContext<'ctx, '_>,
src: NDArrayValue<'ctx>,
) {
assert_eq!(self.dtype, src.dtype, "self and src dtype should match");
irrt::ndarray::call_nac3_ndarray_copy_data(generator, ctx, src, *self);
todo!()
}
}
@ -390,12 +371,7 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayDataProxy<'ctx, '_> {
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
) -> IntValue<'ctx> {
irrt::ndarray::call_ndarray_calc_size(
generator,
ctx,
&self.as_slice_value(ctx, generator),
(None, None),
)
call_ndarray_calc_size(generator, ctx, &self.as_slice_value(ctx, generator), (None, None))
}
}
@ -504,7 +480,7 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
indices_elem_ty.get_bit_width()
);
let index = irrt::ndarray::call_ndarray_flatten_index(generator, ctx, *self.0, indices);
let index = call_ndarray_flatten_index(generator, ctx, *self.0, indices);
let sizeof_elem = ctx
.builder
.build_int_truncate_or_bit_cast(
@ -728,7 +704,7 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayStridesProxy<'ctx, '_> {
ctx: &CodeGenContext<'ctx, '_>,
generator: &G,
) -> AnyTypeEnum<'ctx> {
self.0.strides().base_ptr(ctx, generator).get_type().get_element_type()
self.0.shape().base_ptr(ctx, generator).get_type().get_element_type()
}
fn base_ptr<G: CodeGenerator + ?Sized>(
@ -736,10 +712,10 @@ impl<'ctx> ArrayLikeValue<'ctx> for NDArrayStridesProxy<'ctx, '_> {
ctx: &CodeGenContext<'ctx, '_>,
_: &G,
) -> PointerValue<'ctx> {
let var_name = self.0.name.map(|v| format!("{v}.strides")).unwrap_or_default();
let var_name = self.0.name.map(|v| format!("{v}.data")).unwrap_or_default();
ctx.builder
.build_load(self.0.ptr_to_strides(ctx), var_name.as_str())
.build_load(self.0.ptr_to_shape(ctx), var_name.as_str())
.map(BasicValueEnum::into_pointer_value)
.unwrap()
}