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3 Commits
acd976289f
...
b461cdccb6
Author | SHA1 | Date |
---|---|---|
David Mak | b461cdccb6 | |
David Mak | a370a52658 | |
David Mak | 7753057e22 |
|
@ -15,10 +15,9 @@ use pyo3::{
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use nac3core::{
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codegen::{
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expr::{destructure_range, gen_call},
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irrt::ndarray::call_ndarray_calc_size,
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irrt::call_ndarray_calc_size,
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llvm_intrinsics::{call_int_smax, call_memcpy_generic, call_stackrestore, call_stacksave},
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stmt::{gen_block, gen_for_callback_incrementing, gen_if_callback, gen_with},
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type_aligned_alloca,
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types::{NDArrayType, ProxyType},
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values::{
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ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue, ProxyValue,
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@ -643,12 +642,27 @@ fn format_rpc_ret<'ctx>(
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// (4 + 4 * ndims) bytes with 8-byte alignment
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let sizeof_dims =
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ctx.builder.build_int_mul(ndarray.load_ndims(ctx), llvm_usize_sizeof, "").unwrap();
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let buffer_size =
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let unaligned_buffer_size =
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ctx.builder.build_int_add(sizeof_dims, llvm_pdata_sizeof, "").unwrap();
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let buffer_size = round_up(ctx, unaligned_buffer_size, llvm_usize.const_int(8, false));
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let stackptr = call_stacksave(ctx, None);
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let buffer =
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type_aligned_alloca(generator, ctx, llvm_i8_8, buffer_size, Some("rpc.buffer"));
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// Just to be absolutely sure, alloca in [i8 x 8] slices to force 8-byte alignment
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let buffer = ctx
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.builder
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.build_array_alloca(
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llvm_i8_8,
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ctx.builder
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.build_int_unsigned_div(buffer_size, llvm_usize.const_int(8, false), "")
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.unwrap(),
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"rpc.buffer",
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)
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.unwrap();
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let buffer = ctx
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.builder
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.build_bit_cast(buffer, llvm_pi8, "")
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.map(BasicValueEnum::into_pointer_value)
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.unwrap();
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let buffer = ArraySliceValue::from_ptr_val(buffer, buffer_size, None);
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// The first call to `rpc_recv` reads the top-level ndarray object: [pdata, shape]
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@ -722,7 +736,7 @@ fn format_rpc_ret<'ctx>(
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}
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unsafe {
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ndarray.create_data(generator, ctx, num_elements);
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ndarray.create_data(generator, ctx, llvm_elem_ty, num_elements);
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}
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let ndarray_data = ndarray.data().base_ptr(ctx, generator);
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|
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@ -923,8 +923,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
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let llvm_elem_ty = ctx.get_llvm_type(generator, elem_ty);
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let n = NDArrayValue::from_pointer_value(n, llvm_elem_ty, None, llvm_usize, None);
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let n_sz =
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irrt::ndarray::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
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let n_sz = irrt::call_ndarray_calc_size(generator, ctx, &n.shape(), (None, None));
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if ctx.registry.llvm_options.opt_level == OptimizationLevel::None {
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let n_sz_eqz = ctx
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.builder
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|
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@ -32,7 +32,7 @@ use super::{
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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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},
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types::{ListType, NDArrayType, ProxyType},
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types::{ListType, ProxyType},
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values::{
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ArrayLikeIndexer, ArrayLikeValue, ListValue, NDArrayValue, ProxyValue, RangeValue,
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TypedArrayLikeAccessor, UntypedArrayLikeAccessor,
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@ -43,7 +43,7 @@ use crate::{
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symbol_resolver::{SymbolValue, ValueEnum},
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toplevel::{
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helper::PrimDef,
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numpy::unpack_ndarray_var_tys,
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numpy::{make_ndarray_ty, unpack_ndarray_var_tys},
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DefinitionId, TopLevelDef,
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},
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typecheck::{
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@ -2595,6 +2595,14 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
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_ => 1,
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};
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let ndarray_ndims_ty = ctx.unifier.get_fresh_literal(
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ndims.iter().map(|v| SymbolValue::U64(v - subscripted_dims)).collect(),
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None,
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);
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let ndarray_ty =
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make_ndarray_ty(&mut ctx.unifier, &ctx.primitives, Some(ty), Some(ndarray_ndims_ty));
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let llvm_pndarray_t = ctx.get_llvm_type(generator, ndarray_ty).into_pointer_type();
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let llvm_ndarray_t = llvm_pndarray_t.get_element_type().into_struct_type();
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let llvm_ndarray_data_t = ctx.get_llvm_type(generator, ty).as_basic_type_enum();
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let sizeof_elem = llvm_ndarray_data_t.size_of().unwrap();
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@ -2789,15 +2797,26 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
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let Some(index_addr) = make_indices_arr(generator, ctx)? else { return Ok(None) };
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let num_dims = v.load_ndims(ctx);
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let num_dims = ctx.builder
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.build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
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.unwrap();
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// Create a new array, remove the top dimension from the dimension-size-list, and copy the
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// elements over
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let ndarray = NDArrayType::new(generator, ctx.ctx, llvm_ndarray_data_t)
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.construct_uninitialized(generator, ctx, num_dims, None);
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let subscripted_ndarray =
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generator.gen_var_alloc(ctx, llvm_ndarray_t.into(), None)?;
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let ndarray = NDArrayValue::from_pointer_value(
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subscripted_ndarray,
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llvm_ndarray_data_t,
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None,
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llvm_usize,
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None,
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);
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let num_dims = v.load_ndims(ctx);
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ndarray.store_ndims(
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ctx,
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generator,
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ctx.builder
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.build_int_sub(num_dims, llvm_usize.const_int(1, false), "")
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.unwrap(),
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);
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let ndarray_num_dims = ndarray.load_ndims(ctx);
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ndarray.create_shape(ctx, llvm_usize, ndarray_num_dims);
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@ -2829,7 +2848,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
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llvm_i1.const_zero(),
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);
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let ndarray_num_elems = ndarray::call_ndarray_calc_size(
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let ndarray_num_elems = call_ndarray_calc_size(
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generator,
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ctx,
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&ndarray.shape().as_slice_value(ctx, generator),
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@ -2840,7 +2859,7 @@ fn gen_ndarray_subscript_expr<'ctx, G: CodeGenerator>(
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.build_int_z_extend_or_bit_cast(ndarray_num_elems, sizeof_elem.get_type(), "")
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.unwrap();
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unsafe {
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ndarray.create_data(generator, ctx, ndarray_num_elems);
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ndarray.create_data(generator, ctx, llvm_ndarray_data_t, ndarray_num_elems);
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}
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let v_data_src_ptr = v.data().ptr_offset(ctx, generator, &index_addr, None);
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@ -3599,7 +3618,10 @@ pub fn create_fn_and_call<'ctx>(
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configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
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) -> Option<BasicValueEnum<'ctx>> {
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let intrinsic_fn = ctx.module.get_function(fn_name).unwrap_or_else(|| {
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let params = params.iter().copied().map(BasicTypeEnum::into).collect_vec();
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let params = params.iter()
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.copied()
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.map(BasicTypeEnum::into)
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.collect_vec();
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let fn_type = if let Some(ret_type) = ret_type {
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ret_type.fn_type(params.as_slice(), is_var_args)
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} else {
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@ -3613,7 +3635,10 @@ pub fn create_fn_and_call<'ctx>(
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configure(&intrinsic_fn);
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}
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let args = args.iter().copied().map(BasicValueEnum::into).collect_vec();
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let args = args.iter()
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.copied()
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.map(BasicValueEnum::into)
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.collect_vec();
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ctx.builder
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.build_call(intrinsic_fn, args.as_slice(), call_value_name.unwrap_or_default())
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.map(CallSiteValue::try_as_basic_value)
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@ -3624,7 +3649,7 @@ pub fn create_fn_and_call<'ctx>(
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/// Creates a function in the current module and inserts a `call` instruction into the LLVM IR.
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///
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/// This is a wrapper around [`create_fn_and_call`] for non-vararg function. This function allows
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/// parameters and arguments to be specified as tuples to better indicate the expected type and
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/// parameters and arguments to be specified as tuples to better indicate the expected type and
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/// actual value of each parameter-argument pair of the call.
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pub fn create_and_call_function<'ctx>(
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ctx: &CodeGenContext<'ctx, '_>,
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@ -3635,8 +3660,7 @@ pub fn create_and_call_function<'ctx>(
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configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
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) -> Option<BasicValueEnum<'ctx>> {
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let param_tys = params.iter().map(|(ty, _)| ty).copied().map(BasicTypeEnum::into).collect_vec();
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let arg_values =
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params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
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let arg_values = params.iter().map(|(_, value)| value).copied().map(BasicValueEnum::into).collect_vec();
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create_fn_and_call(
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ctx,
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@ -3662,7 +3686,9 @@ pub fn infer_and_call_function<'ctx>(
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value_name: Option<&str>,
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configure: Option<&dyn Fn(&FunctionValue<'ctx>)>,
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) -> Option<BasicValueEnum<'ctx>> {
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let param_tys = args.iter().map(BasicValueEnum::get_type).collect_vec();
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let param_tys = args.iter()
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.map(BasicValueEnum::get_type)
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.collect_vec();
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create_fn_and_call(
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ctx,
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|
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@ -13,11 +13,12 @@ use super::{CodeGenContext, CodeGenerator};
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use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
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pub use list::*;
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pub use math::*;
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pub use ndarray::*;
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pub use slice::*;
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mod list;
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mod math;
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pub mod ndarray;
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mod ndarray;
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mod slice;
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#[must_use]
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|
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@ -201,52 +201,6 @@ pub fn call_memcpy_generic<'ctx>(
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call_memcpy(ctx, dest, src, len, is_volatile);
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}
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/// Invokes the `llvm.memcpy` intrinsic.
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///
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/// Unlike [`call_memcpy`], this function accepts any type of pointer value. If `dest` or `src` is
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/// not a pointer to an integer, the pointer(s) will be cast to `i8*` before invoking `memcpy`.
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/// Moreover, `len` now refers to the number of elements (rather than bytes) to copy.
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pub fn call_memcpy_generic_array<'ctx>(
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ctx: &CodeGenContext<'ctx, '_>,
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dest: PointerValue<'ctx>,
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src: PointerValue<'ctx>,
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len: IntValue<'ctx>,
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is_volatile: IntValue<'ctx>,
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) {
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let llvm_i8 = ctx.ctx.i8_type();
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let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
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let llvm_sizeof_expr_t = llvm_i8.size_of().get_type();
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let dest_elem_t = dest.get_type().get_element_type();
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let src_elem_t = src.get_type().get_element_type();
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let dest = if matches!(dest_elem_t, IntType(t) if t.get_bit_width() == 8) {
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dest
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} else {
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ctx.builder
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.build_bit_cast(dest, llvm_p0i8, "")
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.map(BasicValueEnum::into_pointer_value)
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.unwrap()
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};
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let src = if matches!(src_elem_t, IntType(t) if t.get_bit_width() == 8) {
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src
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} else {
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ctx.builder
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.build_bit_cast(src, llvm_p0i8, "")
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.map(BasicValueEnum::into_pointer_value)
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.unwrap()
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};
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let len = ctx.builder.build_int_cast(len, llvm_sizeof_expr_t, "").unwrap();
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let len = ctx.builder.build_int_mul(
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len,
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src_elem_t.size_of().unwrap(),
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""
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).unwrap();
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call_memcpy(ctx, dest, src, len, is_volatile);
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}
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/// Macro to find and generate build call for llvm intrinsic (body of llvm intrinsic function)
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///
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/// Arguments:
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|
@ -389,25 +343,3 @@ pub fn call_float_powi<'ctx>(
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.map(Either::unwrap_left)
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.unwrap()
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}
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/// Invokes the [`llvm.ctpop`](https://llvm.org/docs/LangRef.html#llvm-ctpop-intrinsic) intrinsic.
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pub fn call_int_ctpop<'ctx>(
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ctx: &CodeGenContext<'ctx, '_>,
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src: IntValue<'ctx>,
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name: Option<&str>,
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) -> IntValue<'ctx> {
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const FN_NAME: &str = "llvm.ctpop";
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let llvm_src_t = src.get_type();
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let intrinsic_fn = Intrinsic::find(FN_NAME)
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.and_then(|intrinsic| intrinsic.get_declaration(&ctx.module, &[llvm_src_t.into()]))
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.unwrap();
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ctx.builder
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.build_call(intrinsic_fn, &[src.into()], name.unwrap_or_default())
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.map(CallSiteValue::try_as_basic_value)
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.map(|v| v.map_left(BasicValueEnum::into_int_value))
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.map(Either::unwrap_left)
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.unwrap()
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}
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|
|
|
@ -1119,106 +1119,3 @@ fn gen_in_range_check<'ctx>(
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fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
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format!("__{}_va_count", &arg_name).into()
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}
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/// Returns the alignment of the type.
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///
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/// This is necessary as `get_alignment` is not implemented as part of [`BasicType`].
|
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pub fn get_type_alignment<'ctx>(ty: impl Into<BasicTypeEnum<'ctx>>) -> IntValue<'ctx> {
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match ty.into() {
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BasicTypeEnum::ArrayType(ty) => ty.get_alignment(),
|
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BasicTypeEnum::FloatType(ty) => ty.get_alignment(),
|
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BasicTypeEnum::IntType(ty) => ty.get_alignment(),
|
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BasicTypeEnum::PointerType(ty) => ty.get_alignment(),
|
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BasicTypeEnum::StructType(ty) => ty.get_alignment(),
|
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BasicTypeEnum::VectorType(ty) => ty.get_alignment(),
|
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}
|
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}
|
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|
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/// Inserts an `alloca` instruction with allocation `size` given in bytes and the alignment of the
|
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/// given type.
|
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///
|
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/// The returned [`PointerValue`] will have a type of `i8*`, a size of at least `size`, and will be
|
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/// aligned with the alignment of `align_ty`.
|
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pub fn type_aligned_alloca<'ctx, G: CodeGenerator + ?Sized>(
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generator: &mut G,
|
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ctx: &mut CodeGenContext<'ctx, '_>,
|
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align_ty: impl Into<BasicTypeEnum<'ctx>>,
|
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size: IntValue<'ctx>,
|
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name: Option<&str>,
|
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) -> PointerValue<'ctx> {
|
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/// Round `val` up to its modulo `power_of_two`.
|
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fn round_up<'ctx>(
|
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ctx: &CodeGenContext<'ctx, '_>,
|
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val: IntValue<'ctx>,
|
||||
power_of_two: IntValue<'ctx>,
|
||||
) -> IntValue<'ctx> {
|
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debug_assert_eq!(
|
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val.get_type().get_bit_width(),
|
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power_of_two.get_type().get_bit_width(),
|
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"`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 =
|
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ctx.builder.build_int_sub(power_of_two, llvm_val_t.const_int(1, false), "").unwrap();
|
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ctx.builder
|
||||
.build_and(
|
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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()
|
||||
}
|
||||
|
|
|
@ -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);
|
||||
|
|
|
@ -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();
|
||||
|
|
|
@ -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);
|
||||
}
|
||||
|
||||
|
|
|
@ -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()
|
||||
}
|
||||
|
|
Loading…
Reference in New Issue