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core/ndstrides: implement np_identity() and np_eye()

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lyken 2024-08-20 15:17:10 +08:00
parent 0ec4d13735
commit a004703ec2
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GPG Key ID: 3BD5FC6AC8325DD8
2 changed files with 73 additions and 20 deletions

View File

@ -1905,15 +1905,23 @@ pub fn gen_ndarray_eye<'ctx>(
))
}?;
call_ndarray_eye_impl(
generator,
context,
context.primitives.float,
nrows_arg.into_int_value(),
ncols_arg.into_int_value(),
offset_arg.into_int_value(),
)
.map(NDArrayValue::into)
let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let nrows = Int(Int32)
.check_value(generator, context.ctx, nrows_arg)
.unwrap()
.s_extend_or_bit_cast(generator, context, SizeT);
let ncols = Int(Int32)
.check_value(generator, context.ctx, ncols_arg)
.unwrap()
.s_extend_or_bit_cast(generator, context, SizeT);
let offset = Int(Int32)
.check_value(generator, context.ctx, offset_arg)
.unwrap()
.s_extend_or_bit_cast(generator, context, SizeT);
let ndarray = NDArrayObject::make_np_eye(generator, context, dtype, nrows, ncols, offset);
Ok(ndarray.instance.value)
}
/// Generates LLVM IR for `ndarray.identity`.
@ -1927,20 +1935,15 @@ pub fn gen_ndarray_identity<'ctx>(
assert!(obj.is_none());
assert_eq!(args.len(), 1);
let llvm_usize = generator.get_size_type(context.ctx);
let (dtype, _) = unpack_ndarray_var_tys(&mut context.unifier, fun.0.ret);
let n_ty = fun.0.args[0].ty;
let n_arg = args[0].1.clone().to_basic_value_enum(context, generator, n_ty)?;
call_ndarray_eye_impl(
generator,
context,
context.primitives.float,
n_arg.into_int_value(),
n_arg.into_int_value(),
llvm_usize.const_zero(),
)
.map(NDArrayValue::into)
let n = Int(Int32).check_value(generator, context.ctx, n_arg).unwrap();
let n = n.s_extend_or_bit_cast(generator, context, SizeT);
let ndarray = NDArrayObject::make_np_identity(generator, context, dtype, n);
Ok(ndarray.instance.value)
}
/// Generates LLVM IR for `ndarray.copy`.

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@ -1,4 +1,4 @@
use inkwell::values::BasicValueEnum;
use inkwell::{values::BasicValueEnum, IntPredicate};
use crate::{
codegen::{
@ -123,4 +123,54 @@ impl<'ctx> NDArrayObject<'ctx> {
let fill_value = ndarray_one_value(generator, ctx, dtype);
NDArrayObject::make_np_full(generator, ctx, dtype, ndims, shape, fill_value)
}
/// Create an ndarray like `np.eye`.
pub fn make_np_eye<G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
dtype: Type,
nrows: Instance<'ctx, Int<SizeT>>,
ncols: Instance<'ctx, Int<SizeT>>,
offset: Instance<'ctx, Int<SizeT>>,
) -> Self {
let ndzero = ndarray_zero_value(generator, ctx, dtype);
let ndone = ndarray_one_value(generator, ctx, dtype);
let ndarray = NDArrayObject::alloca_dynamic_shape(generator, ctx, dtype, &[nrows, ncols]);
// Create data and make the matrix like look np.eye()
ndarray.create_data(generator, ctx);
ndarray
.foreach(generator, ctx, |generator, ctx, _hooks, nditer| {
// NOTE: rows and cols can never be zero here, since this ndarray's `np.size` would be zero
// and this loop would not execute.
// Load up `row_i` and `col_i` from indices.
let row_i = nditer.get_indices().get_index_const(generator, ctx, 0);
let col_i = nditer.get_indices().get_index_const(generator, ctx, 1);
let be_one = row_i.add(ctx, offset).compare(ctx, IntPredicate::EQ, col_i);
let value = ctx.builder.build_select(be_one.value, ndone, ndzero, "value").unwrap();
let p = nditer.get_pointer(generator, ctx);
ctx.builder.build_store(p, value).unwrap();
Ok(())
})
.unwrap();
ndarray
}
/// Create an ndarray like `np.identity`.
pub fn make_np_identity<G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
dtype: Type,
size: Instance<'ctx, Int<SizeT>>,
) -> Self {
// Convenient implementation
let offset = Int(SizeT).const_0(generator, ctx.ctx);
NDArrayObject::make_np_eye(generator, ctx, dtype, size, size, offset)
}
}