core: refactor fold_numpy_function_call_shape_argument

nac3artiq/demo/support_class_attr_issue102.py

@@ -0,0 +1,40 @@
+from min_artiq import *
+from numpy import int32
+
+
+@nac3
+class Demo:
+    attr1: KernelInvariant[int32] = 2
+    attr2: int32 = 4
+    attr3: Kernel[int32]
+
+    @kernel
+    def __init__(self):
+        self.attr3 = 8
+
+
+@nac3
+class NAC3Devices:
+    core: KernelInvariant[Core]
+    attr4: KernelInvariant[int32] = 16
+    
+    def __init__(self):
+        self.core = Core()
+
+    @kernel
+    def run(self):
+        Demo.attr1  # Supported
+        # Demo.attr2  # Field not accessible on Kernel
+        # Demo.attr3  # Only attributes can be accessed in this way
+        # Demo.attr1 = 2  # Attributes are immutable
+
+        self.attr4  # Attributes can be accessed within class
+
+        obj = Demo()
+        obj.attr1  # Attributes can be accessed by class objects
+
+        NAC3Devices.attr4  # Attributes accessible for classes without __init__
+
+
+if __name__ == "__main__":
+    NAC3Devices().run()

nac3artiq/src/codegen.rs

@@ -657,7 +657,7 @@ pub fn attributes_writeback(
                         }
                         if gen_rpc_tag(ctx, *field_ty, &mut scratch_buffer).is_ok() {
                             attributes.push(name.to_string());
-                            let index = ctx.get_attr_index(ty, *name);
+                            let (index, _) = ctx.get_attr_index(ty, *name);
                             values.push((
                                 *field_ty,
                                 ctx.build_gep_and_load(

nac3artiq/src/symbol_resolver.rs

@@ -627,12 +627,15 @@ impl InnerResolver {
         let pyid_to_def = self.pyid_to_def.read();
         let constructor_ty = pyid_to_def.get(&py_obj_id).and_then(|def_id| {
             defs.iter().find_map(|def| {
-                if let TopLevelDef::Class { object_id, methods, constructor, .. } = &*def.read() {
-                    if object_id == def_id
-                        && constructor.is_some()
-                        && methods.iter().any(|(s, _, _)| s == &"__init__".into())
+                if let Some(rear_guard) = def.try_read() {
+                    if let TopLevelDef::Class { object_id, methods, constructor, .. } = &*rear_guard
                     {
-                        return *constructor;
+                        if object_id == def_id
+                            && constructor.is_some()
+                            && methods.iter().any(|(s, _, _)| s == &"__init__".into())
+                        {
+                            return *constructor;
+                        }
                     }
                 }
                 None
@@ -664,7 +667,29 @@ impl InnerResolver {
             primitives,
         )? {
             Ok(s) => s,
-            Err(e) => return Ok(Err(e)),
+            Err(e) => {
+                // Allow access to Class Attributes of Classes without having to initialize Objects
+                if self.pyid_to_def.read().contains_key(&py_obj_id) {
+                    if let Some(def_id) = self.pyid_to_def.read().get(&py_obj_id).copied() {
+                        let def = defs[def_id.0].read();
+                        let TopLevelDef::Class { object_id, .. } = &*def else {
+                            // only object is supported, functions are not supported
+                            unreachable!("function type is not supported, should not be queried")
+                        };
+
+                        let ty = TypeEnum::TObj {
+                            obj_id: *object_id,
+                            params: VarMap::new(),
+                            fields: HashMap::new(),
+                        };
+                        (unifier.add_ty(ty), true)
+                    } else {
+                        return Ok(Err(e));
+                    }
+                } else {
+                    return Ok(Err(e));
+                }
+            }
         };
         match (&*unifier.get_ty(extracted_ty), inst_check) {
             // do the instantiation for these four types

nac3core/src/codegen/expr.rs

@@ -86,19 +86,35 @@ impl<'ctx, 'a> CodeGenContext<'ctx, 'a> {
         get_subst_key(&mut self.unifier, obj, &fun.vars, filter)
     }
 
-    pub fn get_attr_index(&mut self, ty: Type, attr: StrRef) -> usize {
+    /// Checks the field and attributes of classes
+    /// Returns the index of attr in class fields otherwise returns the attribute value
+    pub fn get_attr_index(&mut self, ty: Type, attr: StrRef) -> (usize, Option<Constant>) {
         let obj_id = match &*self.unifier.get_ty(ty) {
             TypeEnum::TObj { obj_id, .. } => *obj_id,
             // we cannot have other types, virtual type should be handled by function calls
             _ => unreachable!(),
         };
         let def = &self.top_level.definitions.read()[obj_id.0];
-        let index = if let TopLevelDef::Class { fields, .. } = &*def.read() {
-            fields.iter().find_position(|x| x.0 == attr).unwrap().0
+        let (index, value) = if let TopLevelDef::Class { fields, attributes, .. } = &*def.read() {
+            if let Some(field_index) = fields.iter().find_position(|x| x.0 == attr) {
+                (field_index.0, None)
+            } else {
+                let attribute_index = attributes.iter().find_position(|x| x.0 == attr).unwrap();
+                (attribute_index.0, Some(attribute_index.1 .2.clone()))
+            }
         } else {
             unreachable!()
         };
-        index
+        (index, value)
+    }
+
+    pub fn get_attr_index_object(&mut self, ty: Type, attr: StrRef) -> usize {
+        match &*self.unifier.get_ty(ty) {
+            TypeEnum::TObj { fields, .. } => {
+                fields.iter().find_position(|x| *x.0 == attr).unwrap().0
+            }
+            _ => unreachable!(),
+        }
     }
 
     pub fn gen_symbol_val<G: CodeGenerator + ?Sized>(
@@ -2166,11 +2182,72 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
         }
         ExprKind::Attribute { value, attr, .. } => {
             // note that we would handle class methods directly in calls
+
+            // Change Class attribute access requests to accessing constants from Class Definition
+            if let Some(c) = value.custom {
+                if let TypeEnum::TFunc(_) = &*ctx.unifier.get_ty(c) {
+                    let defs = ctx.top_level.definitions.read();
+                    let result = defs.iter().find_map(|def| {
+                        if let Some(rear_guard) = def.try_read() {
+                            if let TopLevelDef::Class {
+                                constructor: Some(constructor),
+                                attributes,
+                                ..
+                            } = &*rear_guard
+                            {
+                                if *constructor == c {
+                                    return attributes.iter().find_map(|f| {
+                                        if f.0 == *attr {
+                                            // All other checks performed by this point
+                                            return Some(f.2.clone());
+                                        }
+                                        None
+                                    });
+                                }
+                            }
+                        }
+                        None
+                    });
+                    match result {
+                        Some(val) => {
+                            let mut modified_expr = expr.clone();
+                            modified_expr.node = ExprKind::Constant { value: val, kind: None };
+
+                            return generator.gen_expr(ctx, &modified_expr);
+                        }
+                        None => unreachable!("Function Type should not have attributes"),
+                    }
+                } else if let TypeEnum::TObj { obj_id, fields, params } = &*ctx.unifier.get_ty(c) {
+                    if fields.is_empty() && params.is_empty() {
+                        let defs = ctx.top_level.definitions.read();
+                        let def = defs[obj_id.0].read();
+                        match if let TopLevelDef::Class { attributes, .. } = &*def {
+                            attributes.iter().find_map(|f| {
+                                if f.0 == *attr {
+                                    return Some(f.2.clone());
+                                }
+                                None
+                            })
+                        } else {
+                            None
+                        } {
+                            Some(val) => {
+                                let mut modified_expr = expr.clone();
+                                modified_expr.node = ExprKind::Constant { value: val, kind: None };
+
+                                return generator.gen_expr(ctx, &modified_expr);
+                            }
+                            None => unreachable!(),
+                        }
+                    }
+                }
+            }
+
             match generator.gen_expr(ctx, value)? {
                 Some(ValueEnum::Static(v)) => v.get_field(*attr, ctx).map_or_else(
                     || {
                         let v = v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?;
-                        let index = ctx.get_attr_index(value.custom.unwrap(), *attr);
+                        let (index, _) = ctx.get_attr_index(value.custom.unwrap(), *attr);
                         Ok(ValueEnum::Dynamic(ctx.build_gep_and_load(
                             v.into_pointer_value(),
                             &[zero, int32.const_int(index as u64, false)],
@@ -2180,7 +2257,14 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                     Ok,
                 )?,
                 Some(ValueEnum::Dynamic(v)) => {
-                    let index = ctx.get_attr_index(value.custom.unwrap(), *attr);
+                    let (index, attr_value) = ctx.get_attr_index(value.custom.unwrap(), *attr);
+                    if let Some(val) = attr_value {
+                        // Change to Constant Construct
+                        let mut modified_expr = expr.clone();
+                        modified_expr.node = ExprKind::Constant { value: val, kind: None };
+
+                        return generator.gen_expr(ctx, &modified_expr);
+                    }
                     ValueEnum::Dynamic(ctx.build_gep_and_load(
                         v.into_pointer_value(),
                         &[zero, int32.const_int(index as u64, false)],
@@ -2363,6 +2447,7 @@ pub fn gen_expr<'ctx, G: CodeGenerator>(
                 ExprKind::Attribute { value, attr, .. } => {
                     let Some(val) = generator.gen_expr(ctx, value)? else { return Ok(None) };
 
+                    // Handle Class Method calls
                     let id = if let TypeEnum::TObj { obj_id, .. } =
                         &*ctx.unifier.get_ty(value.custom.unwrap())
                     {

nac3core/src/codegen/numpy.rs

@@ -163,10 +163,11 @@ fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
 ) -> Result<NDArrayValue<'ctx>, String> {
     let llvm_usize = generator.get_size_type(ctx.ctx);
 
-    for shape_dim in shape {
+    for &shape_dim in shape {
+        let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
         let shape_dim_gez = ctx
             .builder
-            .build_int_compare(IntPredicate::SGE, *shape_dim, llvm_usize.const_zero(), "")
+            .build_int_compare(IntPredicate::SGE, shape_dim, llvm_usize.const_zero(), "")
             .unwrap();
 
         ctx.make_assert(
@@ -189,7 +190,8 @@ fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
     let ndarray_num_dims = ndarray.load_ndims(ctx);
     ndarray.create_dim_sizes(ctx, llvm_usize, ndarray_num_dims);
 
-    for (i, shape_dim) in shape.iter().enumerate() {
+    for (i, &shape_dim) in shape.iter().enumerate() {
+        let shape_dim = ctx.builder.build_int_z_extend(shape_dim, llvm_usize, "").unwrap();
         let ndarray_dim = unsafe {
             ndarray.dim_sizes().ptr_offset_unchecked(
                 ctx,
@@ -199,7 +201,7 @@ fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
             )
         };
 
-        ctx.builder.build_store(ndarray_dim, *shape_dim).unwrap();
+        ctx.builder.build_store(ndarray_dim, shape_dim).unwrap();
     }
 
     let ndarray = ndarray_init_data(generator, ctx, elem_ty, ndarray);
@@ -286,22 +288,68 @@ fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
 ///
 /// * `elem_ty` - The element type of the `NDArray`.
 /// * `shape` - The `shape` parameter used to construct the `NDArray`.
+///
+/// ### Notes on `shape`
+///
+/// Just like numpy, the `shape` argument can be:
+///   1. A list of `int32`;   e.g., `np.empty([600, 800, 3])`
+///   2. A tuple of `int32`;  e.g., `np.empty((600, 800, 3))`
+///   3. A scalar `int32`;     e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+///
+/// See also [`typecheck::type_inferencer::fold_numpy_function_call_shape_argument`] to
+/// learn how `shape` gets from being a Python user expression to here.
 fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,
-    shape: ListValue<'ctx>,
+    shape: BasicValueEnum<'ctx>,
 ) -> Result<NDArrayValue<'ctx>, String> {
-    create_ndarray_dyn_shape(
-        generator,
-        ctx,
-        elem_ty,
-        &shape,
-        |_, ctx, shape| Ok(shape.load_size(ctx, None)),
-        |generator, ctx, shape, idx| {
-            Ok(shape.data().get(ctx, generator, &idx, None).into_int_value())
-        },
-    )
+    let llvm_usize = generator.get_size_type(ctx.ctx);
+
+    match shape {
+        BasicValueEnum::PointerValue(shape_list_ptr)
+            if ListValue::is_instance(shape_list_ptr, llvm_usize).is_ok() =>
+        {
+            // 1. A list of ints; e.g., `np.empty([600, 800, 3])`
+
+            let shape_list = ListValue::from_ptr_val(shape_list_ptr, llvm_usize, None);
+            create_ndarray_dyn_shape(
+                generator,
+                ctx,
+                elem_ty,
+                &shape_list,
+                |_, ctx, shape_list| Ok(shape_list.load_size(ctx, None)),
+                |generator, ctx, shape_list, idx| {
+                    Ok(shape_list.data().get(ctx, generator, &idx, None).into_int_value())
+                },
+            )
+        }
+        BasicValueEnum::StructValue(shape_tuple) => {
+            // 2. A tuple of ints; e.g., `np.empty((600, 800, 3))`
+            // Read [`codegen::expr::gen_expr`] to see how `nac3core` translates a Python tuple into LLVM.
+
+            // Get the length/size of the tuple, which also happens to be the value of `ndims`.
+            let ndims = shape_tuple.get_type().count_fields();
+
+            let mut shape = Vec::with_capacity(ndims as usize);
+            for dim_i in 0..ndims {
+                let dim = ctx
+                    .builder
+                    .build_extract_value(shape_tuple, dim_i, format!("dim{dim_i}").as_str())
+                    .unwrap()
+                    .into_int_value();
+
+                shape.push(dim);
+            }
+            create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
+        }
+        BasicValueEnum::IntValue(shape_int) => {
+            // 3. A scalar int; e.g., `np.empty(3)`, this is functionally equivalent to `np.empty([3])`
+
+            create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
+        }
+        _ => unreachable!(),
+    }
 }
 
 /// Generates LLVM IR for populating the entire `NDArray` using a lambda with its flattened index as
@@ -486,7 +534,7 @@ fn call_ndarray_zeros_impl<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,
-    shape: ListValue<'ctx>,
+    shape: BasicValueEnum<'ctx>,
 ) -> Result<NDArrayValue<'ctx>, String> {
     let supported_types = [
         ctx.primitives.int32,
@@ -517,7 +565,7 @@ fn call_ndarray_ones_impl<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,
-    shape: ListValue<'ctx>,
+    shape: BasicValueEnum<'ctx>,
 ) -> Result<NDArrayValue<'ctx>, String> {
     let supported_types = [
         ctx.primitives.int32,
@@ -548,7 +596,7 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
     generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     elem_ty: Type,
-    shape: ListValue<'ctx>,
+    shape: BasicValueEnum<'ctx>,
     fill_value: BasicValueEnum<'ctx>,
 ) -> Result<NDArrayValue<'ctx>, String> {
     let ndarray = call_ndarray_empty_impl(generator, ctx, elem_ty, shape)?;
@@ -1674,17 +1722,11 @@ pub fn gen_ndarray_empty<'ctx>(
     assert!(obj.is_none());
     assert_eq!(args.len(), 1);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
     let shape_ty = fun.0.args[0].ty;
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
-    call_ndarray_empty_impl(
-        generator,
-        context,
-        context.primitives.float,
-        ListValue::from_ptr_val(shape_arg.into_pointer_value(), llvm_usize, None),
-    )
-    .map(NDArrayValue::into)
+    call_ndarray_empty_impl(generator, context, context.primitives.float, shape_arg)
+        .map(NDArrayValue::into)
 }
 
 /// Generates LLVM IR for `ndarray.zeros`.
@@ -1698,17 +1740,11 @@ pub fn gen_ndarray_zeros<'ctx>(
     assert!(obj.is_none());
     assert_eq!(args.len(), 1);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
     let shape_ty = fun.0.args[0].ty;
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
-    call_ndarray_zeros_impl(
-        generator,
-        context,
-        context.primitives.float,
-        ListValue::from_ptr_val(shape_arg.into_pointer_value(), llvm_usize, None),
-    )
-    .map(NDArrayValue::into)
+    call_ndarray_zeros_impl(generator, context, context.primitives.float, shape_arg)
+        .map(NDArrayValue::into)
 }
 
 /// Generates LLVM IR for `ndarray.ones`.
@@ -1722,17 +1758,11 @@ pub fn gen_ndarray_ones<'ctx>(
     assert!(obj.is_none());
     assert_eq!(args.len(), 1);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
     let shape_ty = fun.0.args[0].ty;
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
 
-    call_ndarray_ones_impl(
-        generator,
-        context,
-        context.primitives.float,
-        ListValue::from_ptr_val(shape_arg.into_pointer_value(), llvm_usize, None),
-    )
-    .map(NDArrayValue::into)
+    call_ndarray_ones_impl(generator, context, context.primitives.float, shape_arg)
+        .map(NDArrayValue::into)
 }
 
 /// Generates LLVM IR for `ndarray.full`.
@@ -1746,21 +1776,14 @@ pub fn gen_ndarray_full<'ctx>(
     assert!(obj.is_none());
     assert_eq!(args.len(), 2);
 
-    let llvm_usize = generator.get_size_type(context.ctx);
     let shape_ty = fun.0.args[0].ty;
     let shape_arg = args[0].1.clone().to_basic_value_enum(context, generator, shape_ty)?;
     let fill_value_ty = fun.0.args[1].ty;
     let fill_value_arg =
         args[1].1.clone().to_basic_value_enum(context, generator, fill_value_ty)?;
 
-    call_ndarray_full_impl(
-        generator,
-        context,
-        fill_value_ty,
-        ListValue::from_ptr_val(shape_arg.into_pointer_value(), llvm_usize, None),
-        fill_value_arg,
-    )
-    .map(NDArrayValue::into)
+    call_ndarray_full_impl(generator, context, fill_value_ty, shape_arg, fill_value_arg)
+        .map(NDArrayValue::into)
 }
 
 pub fn gen_ndarray_array<'ctx>(

nac3core/src/codegen/stmt.rs

@@ -113,7 +113,7 @@ pub fn gen_store_target<'ctx, G: CodeGenerator>(
             }
         },
         ExprKind::Attribute { value, attr, .. } => {
-            let index = ctx.get_attr_index(value.custom.unwrap(), *attr);
+            let (index, _) = ctx.get_attr_index(value.custom.unwrap(), *attr);
             let val = if let Some(v) = generator.gen_expr(ctx, value)? {
                 v.to_basic_value_enum(ctx, generator, value.custom.unwrap())?
             } else {

nac3core/src/toplevel/builtins.rs

@@ -83,6 +83,7 @@ pub fn get_exn_constructor(
         object_id: DefinitionId(class_id),
         type_vars: Vec::default(),
         fields: exception_fields,
+        attributes: Vec::default(),
         methods: vec![("__init__".into(), signature, DefinitionId(cons_id))],
         ancestors: vec![
             TypeAnnotation::CustomClass { id: DefinitionId(class_id), params: Vec::default() },
@@ -323,6 +324,9 @@ struct BuiltinBuilder<'a> {
 
     num_or_ndarray_ty: TypeVar,
     num_or_ndarray_var_map: VarMap,
+
+    /// See [`BuiltinBuilder::build_ndarray_from_shape_factory_function`]
+    ndarray_factory_fn_shape_arg_tvar: TypeVar,
 }
 
 impl<'a> BuiltinBuilder<'a> {
@@ -393,6 +397,8 @@ impl<'a> BuiltinBuilder<'a> {
 
         let list_int32 = unifier.add_ty(TypeEnum::TList { ty: int32 });
 
+        let ndarray_factory_fn_shape_arg_tvar = unifier.get_fresh_var(Some("Shape".into()), None);
+
         BuiltinBuilder {
             unifier,
             primitives,
@@ -420,6 +426,8 @@ impl<'a> BuiltinBuilder<'a> {
 
             num_or_ndarray_ty,
             num_or_ndarray_var_map,
+
+            ndarray_factory_fn_shape_arg_tvar,
         }
     }
 
@@ -596,6 +604,7 @@ impl<'a> BuiltinBuilder<'a> {
                 object_id: prim.id(),
                 type_vars: Vec::default(),
                 fields: make_exception_fields(int32, int64, str),
+                attributes: Vec::default(),
                 methods: Vec::default(),
                 ancestors: vec![],
                 constructor: None,
@@ -624,7 +633,8 @@ impl<'a> BuiltinBuilder<'a> {
                 name: prim.name().into(),
                 object_id: prim.id(),
                 type_vars: vec![self.option_tvar.ty],
-                fields: vec![],
+                fields: Vec::default(),
+                attributes: Vec::default(),
                 methods: vec![
                     Self::create_method(PrimDef::OptionIsSome, self.is_some_ty.0),
                     Self::create_method(PrimDef::OptionIsNone, self.is_some_ty.0),
@@ -738,6 +748,7 @@ impl<'a> BuiltinBuilder<'a> {
                 object_id: prim.id(),
                 type_vars: vec![self.ndarray_dtype_tvar.ty, self.ndarray_ndims_tvar.ty],
                 fields: Vec::default(),
+                attributes: Vec::default(),
                 methods: vec![
                     Self::create_method(PrimDef::NDArrayCopy, self.ndarray_copy_ty.0),
                     Self::create_method(PrimDef::NDArrayFill, self.ndarray_fill_ty.0),
@@ -955,21 +966,46 @@ impl<'a> BuiltinBuilder<'a> {
         )
     }
 
-    /// Build ndarray factory functions that only take in an argument `shape` of type `list[int32]` and return an ndarray.
+    /// Build ndarray factory functions that only take in an argument `shape`.
+    ///
+    /// `shape` can be a tuple of int32s, a list of int32s, or a scalar int32.
     fn build_ndarray_from_shape_factory_function(&mut self, prim: PrimDef) -> TopLevelDef {
         debug_assert_prim_is_allowed(
             prim,
             &[PrimDef::FunNpNDArray, PrimDef::FunNpEmpty, PrimDef::FunNpZeros, PrimDef::FunNpOnes],
         );
 
+        // NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
+        // the `param_ty` for `create_fn_by_codegen`.
+        //
+        // Ideally, we should have created a [`TypeVar`] to define all possible input
+        // types for the parameter "shape" like so:
+        // ```rust
+        // self.unifier.get_fresh_var_with_range(
+        //   &[int32, list_int32, /* and more... */],
+        //   Some("T".into()), None)
+        // )
+        // ```
+        //
+        // However, there is (currently) no way to type a tuple of arbitrary length in `nac3core`.
+        //
+        // And this is the best we could do:
+        // ```rust
+        // &[ int32, list_int32, tuple_1_int32, tuple_2_int32, tuple_3_int32, ... ],
+        // ```
+        //
+        // But this is not ideal.
+        //
+        // Instead, we delegate the responsibility of typechecking
+        // to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
+        // and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
+
         create_fn_by_codegen(
             self.unifier,
             &VarMap::new(),
             prim.name(),
             self.ndarray_float,
-            // We are using List[int32] here, as I don't know a way to specify an n-tuple bound on a
-            // type variable
-            &[(self.list_int32, "shape")],
+            &[(self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
             Box::new(move |ctx, obj, fun, args, generator| {
                 let func = match prim {
                     PrimDef::FunNpNDArray | PrimDef::FunNpEmpty => gen_ndarray_empty,

nac3core/src/toplevel/composer.rs

@@ -1057,7 +1057,14 @@ impl TopLevelComposer {
         let (keyword_list, core_config) = core_info;
         let mut class_def = class_def.write();
         let TopLevelDef::Class {
-            object_id, ancestors, fields, methods, resolver, type_vars, ..
+            object_id,
+            ancestors,
+            fields,
+            attributes,
+            methods,
+            resolver,
+            type_vars,
+            ..
         } = &mut *class_def
         else {
             unreachable!("here must be toplevel class def");
@@ -1073,10 +1080,14 @@ impl TopLevelComposer {
             class_body_ast,
             _class_ancestor_def,
             class_fields_def,
+            class_attributes_def,
             class_methods_def,
             class_type_vars_def,
             class_resolver,
-        ) = (*object_id, *name, bases, body, ancestors, fields, methods, type_vars, resolver);
+        ) = (
+            *object_id, *name, bases, body, ancestors, fields, attributes, methods, type_vars,
+            resolver,
+        );
 
         let class_resolver = class_resolver.as_ref().unwrap();
         let class_resolver = class_resolver.as_ref();
@@ -1285,34 +1296,74 @@ impl TopLevelComposer {
                         .unify(method_dummy_ty, method_type)
                         .map_err(|e| HashSet::from([e.to_display(unifier).to_string()]))?;
                 }
-                ast::StmtKind::AnnAssign { target, annotation, value: None, .. } => {
+                ast::StmtKind::AnnAssign { target, annotation, value, .. } => {
                     if let ast::ExprKind::Name { id: attr, .. } = &target.node {
                         if defined_fields.insert(attr.to_string()) {
                             let dummy_field_type = unifier.get_dummy_var().ty;
 
-                            // handle Kernel[T], KernelInvariant[T]
-                            let (annotation, mutable) = match &annotation.node {
-                                ast::ExprKind::Subscript { value, slice, .. }
-                                    if matches!(
-                                        &value.node,
-                                        ast::ExprKind::Name { id, .. } if id == &core_config.kernel_invariant_ann.into()
-                                    ) =>
-                                {
-                                    (slice, false)
+                            let annotation = match value {
+                                None => {
+                                    // handle Kernel[T], KernelInvariant[T]
+                                    let (annotation, mutable) = match &annotation.node {
+                                        ast::ExprKind::Subscript { value, slice, .. }
+                                            if matches!(
+                                                &value.node,
+                                                ast::ExprKind::Name { id, .. } if id == &core_config.kernel_invariant_ann.into()
+                                            ) =>
+                                        {
+                                            (slice, false)
+                                        }
+                                        ast::ExprKind::Subscript { value, slice, .. }
+                                            if matches!(
+                                                &value.node,
+                                                ast::ExprKind::Name { id, .. } if core_config.kernel_ann.map_or(false, |c| id == &c.into())
+                                            ) =>
+                                        {
+                                            (slice, true)
+                                        }
+                                        _ if core_config.kernel_ann.is_none() => (annotation, true),
+                                        _ => continue, // ignore fields annotated otherwise
+                                    };
+                                    class_fields_def.push((*attr, dummy_field_type, mutable));
+                                    annotation
                                 }
-                                ast::ExprKind::Subscript { value, slice, .. }
-                                    if matches!(
-                                        &value.node,
-                                        ast::ExprKind::Name { id, .. } if core_config.kernel_ann.map_or(false, |c| id == &c.into())
-                                    ) =>
-                                {
-                                    (slice, true)
-                                }
-                                _ if core_config.kernel_ann.is_none() => (annotation, true),
-                                _ => continue, // ignore fields annotated otherwise
-                            };
-                            class_fields_def.push((*attr, dummy_field_type, mutable));
+                                // Supporting Class Attributes
+                                Some(boxed_expr) => {
+                                    // Class attributes are set as immutable regardless
+                                    let (annotation, _) = match &annotation.node {
+                                        ast::ExprKind::Subscript { slice, .. } => (slice, false),
+                                        _ if core_config.kernel_ann.is_none() => (annotation, false),
+                                        _ => continue,
+                                    };
 
+                                    match &**boxed_expr {
+                                        ast::Located {location: _, custom: (), node: ast::ExprKind::Constant { value: v, kind: _ }} => {
+                                            // Restricting the types allowed to be defined as class attributes
+                                            match v {
+                                                ast::Constant::Bool(_) | ast::Constant::Str(_) | ast::Constant::Int(_) | ast::Constant::Float(_) => {}
+                                                _ => {
+                                                        return Err(HashSet::from([
+                                                        format!(
+                                                            "unsupported statement in class definition body (at {})",
+                                                            b.location
+                                                        ),
+                                                    ]))
+                                                }
+                                            }
+                                            class_attributes_def.push((*attr, dummy_field_type, v.clone()));
+                                        }
+                                        _ => {
+                                            return Err(HashSet::from([
+                                                format!(
+                                                    "unsupported statement in class definition body (at {})",
+                                                    b.location
+                                                ),
+                                            ]))
+                                        }
+                                    }
+                                    annotation
+                                }
+                            };
                             let parsed_annotation = parse_ast_to_type_annotation_kinds(
                                 class_resolver,
                                 temp_def_list,
@@ -1384,7 +1435,14 @@ impl TopLevelComposer {
         type_var_to_concrete_def: &mut HashMap<Type, TypeAnnotation>,
     ) -> Result<(), HashSet<String>> {
         let TopLevelDef::Class {
-            object_id, ancestors, fields, methods, resolver, type_vars, ..
+            object_id,
+            ancestors,
+            fields,
+            attributes,
+            methods,
+            resolver,
+            type_vars,
+            ..
         } = class_def
         else {
             unreachable!("here must be class def ast")
@@ -1393,10 +1451,11 @@ impl TopLevelComposer {
             _class_id,
             class_ancestor_def,
             class_fields_def,
+            class_attribute_def,
             class_methods_def,
             _class_type_vars_def,
             _class_resolver,
-        ) = (*object_id, ancestors, fields, methods, type_vars, resolver);
+        ) = (*object_id, ancestors, fields, attributes, methods, type_vars, resolver);
 
         // since when this function is called, the ancestors of the direct parent
         // are supposed to be already handled, so we only need to deal with the direct parent
@@ -1407,7 +1466,7 @@ impl TopLevelComposer {
 
         let base = temp_def_list.get(id.0).unwrap();
         let base = base.read();
-        let TopLevelDef::Class { methods, fields, .. } = &*base else {
+        let TopLevelDef::Class { methods, fields, attributes, .. } = &*base else {
             unreachable!("must be top level class def")
         };
 
@@ -1449,7 +1508,7 @@ impl TopLevelComposer {
             }
         }
         // use the new_child_methods to replace all the elements in `class_methods_def`
-        class_methods_def.drain(..);
+        class_methods_def.clear();
         class_methods_def.extend(new_child_methods);
 
         // handle class fields
@@ -1459,7 +1518,9 @@ impl TopLevelComposer {
             let to_be_added = (*anc_field_name, *anc_field_ty, *mutable);
             // find if there is a fields with the same name in the child class
             for (class_field_name, ..) in &*class_fields_def {
-                if class_field_name == anc_field_name {
+                if class_field_name == anc_field_name
+                    || attributes.iter().any(|f| f.0 == *class_field_name)
+                {
                     return Err(HashSet::from([format!(
                         "field `{class_field_name}` has already declared in the ancestor classes"
                     )]));
@@ -1467,14 +1528,33 @@ impl TopLevelComposer {
             }
             new_child_fields.push(to_be_added);
         }
+
+        // handle class attributes
+        let mut new_child_attributes: Vec<(StrRef, Type, ast::Constant)> = Vec::new();
+        for (anc_attr_name, anc_attr_ty, attr_value) in attributes {
+            let to_be_added = (*anc_attr_name, *anc_attr_ty, attr_value.clone());
+            // find if there is a attribute with the same name in the child class
+            for (class_attr_name, ..) in &*class_attribute_def {
+                if class_attr_name == anc_attr_name
+                    || fields.iter().any(|f| f.0 == *class_attr_name)
+                {
+                    return Err(HashSet::from([format!(
+                        "attribute `{class_attr_name}` has already declared in the ancestor classes"
+                    )]));
+                }
+            }
+            new_child_attributes.push(to_be_added);
+        }
+
         for (class_field_name, class_field_ty, mutable) in &*class_fields_def {
             if !is_override.contains(class_field_name) {
                 new_child_fields.push((*class_field_name, *class_field_ty, *mutable));
             }
         }
-        class_fields_def.drain(..);
+        class_fields_def.clear();
         class_fields_def.extend(new_child_fields);
-
+        class_attribute_def.clear();
+        class_attribute_def.extend(new_child_attributes);
         Ok(())
     }
 

nac3core/src/toplevel/helper.rs

@@ -474,6 +474,7 @@ impl TopLevelComposer {
             object_id: obj_id,
             type_vars: Vec::default(),
             fields: Vec::default(),
+            attributes: Vec::default(),
             methods: Vec::default(),
             ancestors: Vec::default(),
             constructor,

nac3core/src/toplevel/mod.rs

@@ -103,6 +103,10 @@ pub enum TopLevelDef {
         ///
         /// Name and type is mutable.
         fields: Vec<(StrRef, Type, bool)>,
+        /// Class Attributes.
+        ///
+        /// Name, type, value.
+        attributes: Vec<(StrRef, Type, ast::Constant)>,
         /// Class methods, pointing to the corresponding function definition.
         methods: Vec<(StrRef, Type, DefinitionId)>,
         /// Ancestor classes, including itself.

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__generic_class.snap

@@ -5,7 +5,7 @@ expression: res_vec
 [
     "Class {\nname: \"Generic_A\",\nancestors: [\"Generic_A[V]\", \"B\"],\nfields: [\"aa\", \"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\"), (\"fun\", \"fn[[a:int32], V]\")],\ntype_vars: [\"V\"]\n}\n",
     "Function {\nname: \"Generic_A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
-    "Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(239)]\n}\n",
+    "Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(240)]\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [\"aa\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"B.foo\",\nsig: \"fn[[b:T], none]\",\nvar_id: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__inheritance_override.snap

@@ -7,7 +7,7 @@ expression: res_vec
     "Function {\nname: \"A.__init__\",\nsig: \"fn[[t:T], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.foo\",\nsig: \"fn[[c:C], none]\",\nvar_id: []\n}\n",
-    "Class {\nname: \"B\",\nancestors: [\"B[typevar228]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar228\"]\n}\n",
+    "Class {\nname: \"B\",\nancestors: [\"B[typevar229]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar229\"]\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"B.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
     "Class {\nname: \"C\",\nancestors: [\"C\", \"B[bool]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\", \"e\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__list_tuple_generic.snap

@@ -5,8 +5,8 @@ expression: res_vec
 [
     "Function {\nname: \"foo\",\nsig: \"fn[[a:list[int32], b:tuple[T, float]], A[B, bool]]\",\nvar_id: []\n}\n",
     "Class {\nname: \"A\",\nancestors: [\"A[T, V]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[v:V], none]\"), (\"fun\", \"fn[[a:T], V]\")],\ntype_vars: [\"T\", \"V\"]\n}\n",
-    "Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(241)]\n}\n",
-    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(246)]\n}\n",
+    "Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(242)]\n}\n",
+    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(247)]\n}\n",
     "Function {\nname: \"gfun\",\nsig: \"fn[[a:A[list[float], int32]], none]\",\nvar_id: []\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [],\nmethods: [(\"__init__\", \"fn[[], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__self1.snap

@@ -3,7 +3,7 @@ source: nac3core/src/toplevel/test.rs
 expression: res_vec
 ---
 [
-    "Class {\nname: \"A\",\nancestors: [\"A[typevar227, typevar228]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar227\", \"typevar228\"]\n}\n",
+    "Class {\nname: \"A\",\nancestors: [\"A[typevar228, typevar229]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar228\", \"typevar229\"]\n}\n",
     "Function {\nname: \"A.__init__\",\nsig: \"fn[[a:A[float, bool], b:B], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.fun\",\nsig: \"fn[[a:A[float, bool]], A[bool, int32]]\",\nvar_id: []\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\", \"A[int64, bool]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\"), (\"foo\", \"fn[[b:B], B]\"), (\"bar\", \"fn[[a:A[list[B], int32]], tuple[A[virtual[A[B, int32]], bool], B]]\")],\ntype_vars: []\n}\n",

nac3core/src/toplevel/snapshots/nac3core__toplevel__test__test_analyze__simple_class_compose.snap

@@ -6,12 +6,12 @@ expression: res_vec
     "Class {\nname: \"A\",\nancestors: [\"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"A.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
-    "Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(247)]\n}\n",
+    "Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(248)]\n}\n",
     "Class {\nname: \"B\",\nancestors: [\"B\", \"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Class {\nname: \"C\",\nancestors: [\"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
     "Function {\nname: \"C.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"C.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
     "Function {\nname: \"foo\",\nsig: \"fn[[a:A], none]\",\nvar_id: []\n}\n",
-    "Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(255)]\n}\n",
+    "Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(256)]\n}\n",
 ]

nac3core/src/toplevel/type_annotation.rs

@@ -470,6 +470,7 @@ pub fn get_type_from_type_annotation_kinds(
                 }
                 result
             };
+            // Class Attributes keep a copy with Class Definition and are not added to objects
             let mut tobj_fields = methods
                 .iter()
                 .map(|(name, ty, _)| {

nac3core/src/typecheck/type_error.rs

@@ -34,6 +34,7 @@ pub enum TypeErrorKind {
     },
     RequiresTypeAnn,
     PolymorphicFunctionPointer,
+    NoSuchAttribute(RecordKey, Type),
 }
 
 #[derive(Debug, Clone)]
@@ -156,6 +157,10 @@ impl<'a> Display for DisplayTypeError<'a> {
                 let t = self.unifier.stringify_with_notes(*t, &mut notes);
                 write!(f, "`{t}::{name}` field/method does not exist")
             }
+            NoSuchAttribute(name, t) => {
+                let t = self.unifier.stringify_with_notes(*t, &mut notes);
+                write!(f, "`{t}::{name}` is not a class attribute")
+            }
             TupleIndexOutOfBounds { index, len } => {
                 write!(
                     f,

nac3core/src/typecheck/type_inferencer/mod.rs

@@ -6,6 +6,7 @@ use std::{cell::RefCell, sync::Arc};
 
 use super::typedef::{Call, FunSignature, FuncArg, RecordField, Type, TypeEnum, Unifier, VarMap};
 use super::{magic_methods::*, type_error::TypeError, typedef::CallId};
+use crate::toplevel::TopLevelDef;
 use crate::{
     symbol_resolver::{SymbolResolver, SymbolValue},
     toplevel::{
@@ -820,6 +821,155 @@ impl<'a> Inferencer<'a> {
         })
     }
 
+    /// Fold an ndarray `shape` argument. This function aims to fold `shape` arguments like that of
+    /// <https://numpy.org/doc/stable/reference/generated/numpy.zeros.html> (for `np_zeros`).
+    ///
+    /// Arguments:
+    ///   * `id` - The name of the function of the function call this `shape` argument is in. Used for error reporting.
+    ///   * `arg_index` - The position (0-based) of this argument in the function call. Used for error reporting.
+    ///   * `shape_expr` - [`Located<ExprKind>`] of the input argument.
+    ///
+    /// On success, it returns a tuple of
+    ///   1) the `ndims` value inferred from the input `shape`,
+    ///   2) and the elaborated expression. Like what other fold functions of [`Inferencer`] would normally return.
+    fn fold_numpy_function_call_shape_argument(
+        &mut self,
+        id: StrRef,
+        arg_index: usize,
+        shape_expr: Located<ExprKind>,
+    ) -> Result<(u64, ast::Expr<Option<Type>>), HashSet<String>> {
+        /*
+            ### Further explanation
+
+            As said, this function aims to fold `shape` arguments, but this is *not* trivial.
+            The root of the issue is that `nac3core` has to deduce the `ndims`
+            of the created (for in the case of `np_zeros`) ndarray statically - i.e., during inference time.
+
+            There are three types of valid input to `shape`:
+              1. A python `List` (all `int32s`);   e.g., `np_zeros([600, 800, 3])`
+              2. A python `Tuple` (all `int32s`);  e.g., `np_zeros((600, 800, 3))`
+              3. An `int32`; e.g., `np_zeros(256)` - this is functionally equivalent to `np_zeros([256])`
+
+            For 2. and 3., `ndims` can be deduce immediately from the inferred type of the input:
+              - For 2. `ndims` is simply the number of elements found in [`TypeEnum::TTuple`] after typechecking the `shape` argument.
+              - For 3. `ndims` is simply 1.
+
+            For 1., `ndims` is supposedly the length of the input list. However, the length of the input list
+            is a runtime property. Therefore (as a hack) we resort to analyzing the argument expression [`ExprKind::List`]
+            itself to extract the input list length statically.
+
+            This implies that the user could only write:
+
+            ```python
+            my_rgba_image = np_zeros([600, 800, 4])
+            # the shape argument is directly written as a list literal.
+            # and `nac3core` could therefore tell that ndims is `3` by
+            # looking at the raw AST expression itself.
+            ```
+
+            But not:
+
+            ```python
+            my_image_dimension = [600, 800, 4]
+            mystery_function_that_mutates_my_list(my_image_dimension)
+            my_image = np_zeros(my_image_dimension)
+            # what is the length now? what is `ndims`?
+
+            # it is *basically impossible* to generally determine the
+            # length of `my_image_dimension` statically for `ndims`!!
+            ```
+        */
+
+        // Auxillary details for error reporting.
+        // Predefined here because `shape_expr` will be moved when doing `fold_expr`
+        let shape_expr_name = shape_expr.node.name();
+        let shape_location = shape_expr.location;
+
+        // Fold `shape`
+        let shape = self.fold_expr(shape_expr)?;
+        let shape_ty = shape.custom.unwrap(); // The inferred type of `shape`
+
+        // Check `shape_ty` to see if its a list of int32s, a tuple of int32s, or just int32.
+        // Otherwise throw an error as that would mean the user wrote an ill-typed `shape_expr`.
+        //
+        // Here, we also take the opportunity to deduce `ndims` statically for 2. and 3.
+        let shape_ty_enum = &*self.unifier.get_ty(shape_ty);
+        let ndims = match shape_ty_enum {
+            TypeEnum::TList { ty } => {
+                // Handle 1. A list of int32s
+
+                // Typecheck
+                self.unifier.unify(*ty, self.primitives.int32).map_err(|err| {
+                    HashSet::from([err
+                        .at(Some(shape_location))
+                        .to_display(self.unifier)
+                        .to_string()])
+                })?;
+
+                // Special handling for (1. A python `List` (all `int32s`)).
+                // Read the doc above this function to see what is going on here.
+                if let ExprKind::List { elts, .. } = &shape.node {
+                    // The user wrote a List literal as the input argument
+                    elts.len() as u64
+                } else {
+                    // This means the user is passing an expression of type `List`,
+                    // but it is done so indirectly (like putting a variable referencing a `List`)
+                    // rather than writing a List literal. We need to report an error.
+                    return Err(HashSet::from([
+                        format!(
+                            "Expected List (must be a literal)/Tuple/int32 for argument {arg_num} of {id} at {shape_location}. \
+                            There, you are passing a value of type List as the argument. \
+                            However, this argument is special - you must only supply this argument with a List literal. \
+                            On the other hand, you may instead pass in a tuple, and there would be no such restriction.",
+                            arg_num = arg_index + 1
+                        )
+                    ]));
+                }
+            }
+            TypeEnum::TTuple { ty: tuple_element_types } => {
+                // Handle 2. A tuple of int32s
+
+                // Typecheck
+                // The expected type is just the tuple but with all its elements being int32.
+                let expected_ty = self.unifier.add_ty(TypeEnum::TTuple {
+                    ty: tuple_element_types.iter().map(|_| self.primitives.int32).collect_vec(),
+                });
+                self.unifier.unify(shape_ty, expected_ty).map_err(|err| {
+                    HashSet::from([err
+                        .at(Some(shape_location))
+                        .to_display(self.unifier)
+                        .to_string()])
+                })?;
+
+                // `ndims` can be deduced statically from the inferred Tuple type.
+                tuple_element_types.len() as u64
+            }
+            TypeEnum::TObj { .. } => {
+                // Handle 3. An integer (generalized as [`TypeEnum::TObj`])
+
+                // Typecheck
+                self.unify(self.primitives.int32, shape_ty, &shape_location)?;
+
+                // Deduce `ndims`
+                1
+            }
+            _ => {
+                // The user wrote an ill-typed `shape_expr`,
+                // so throw an error.
+                let shape_ty_str = self.unifier.stringify(shape_ty);
+                return report_error(
+                    format!(
+                        "Expected List (must be a literal)/Tuple/integer for first argument of {id}, got {shape_expr_name} of type {shape_ty_str}",
+                    )
+                    .as_str(),
+                    shape_location,
+                );
+            }
+        };
+
+        Ok((ndims, shape))
+    }
+
     /// Tries to fold a special call. Returns [`Some`] if the call expression `func` is a special call, otherwise
     /// returns [`None`].
     fn try_fold_special_call(
@@ -1147,25 +1297,15 @@ impl<'a> Inferencer<'a> {
             }));
         }
 
-        // 1-argument ndarray n-dimensional creation functions
+        // 1-argument ndarray n-dimensional factory functions
         if ["np_ndarray".into(), "np_empty".into(), "np_zeros".into(), "np_ones".into()]
             .contains(id)
             && args.len() == 1
         {
-            let ExprKind::List { elts, .. } = &args[0].node else {
-                return report_error(
-                    format!(
-                        "Expected List literal for first argument of {id}, got {}",
-                        args[0].node.name()
-                    )
-                    .as_str(),
-                    args[0].location,
-                );
-            };
+            let shape_expr = args.remove(0);
+            let (ndims, shape) =
+                self.fold_numpy_function_call_shape_argument(*id, 0, shape_expr)?; // Special handling the `shape`
 
-            let ndims = elts.len() as u64;
-
-            let arg0 = self.fold_expr(args.remove(0))?;
             let ndims = self.unifier.get_fresh_literal(vec![SymbolValue::U64(ndims)], None);
             let ret = make_ndarray_ty(
                 self.unifier,
@@ -1176,7 +1316,7 @@ impl<'a> Inferencer<'a> {
             let custom = self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
                 args: vec![FuncArg {
                     name: "shape".into(),
-                    ty: arg0.custom.unwrap(),
+                    ty: shape.custom.unwrap(),
                     default_value: None,
                 }],
                 ret,
@@ -1192,7 +1332,7 @@ impl<'a> Inferencer<'a> {
                         location: func.location,
                         node: ExprKind::Name { id: *id, ctx: *ctx },
                     }),
-                    args: vec![arg0],
+                    args: vec![shape],
                     keywords: vec![],
                 },
             }));
@@ -1441,6 +1581,24 @@ impl<'a> Inferencer<'a> {
         Ok(self.unifier.add_ty(TypeEnum::TTuple { ty }))
     }
 
+    /// Checks for non-class attributes
+    fn infer_general_attribute(
+        &mut self,
+        value: &ast::Expr<Option<Type>>,
+        attr: StrRef,
+        ctx: ExprContext,
+    ) -> InferenceResult {
+        let attr_ty = self.unifier.get_dummy_var().ty;
+        let fields = once((
+            attr.into(),
+            RecordField::new(attr_ty, ctx == ExprContext::Store, Some(value.location)),
+        ))
+        .collect();
+        let record = self.unifier.add_record(fields);
+        self.constrain(value.custom.unwrap(), record, &value.location)?;
+        Ok(attr_ty)
+    }
+
     fn infer_attribute(
         &mut self,
         value: &ast::Expr<Option<Type>>,
@@ -1448,31 +1606,72 @@ impl<'a> Inferencer<'a> {
         ctx: ExprContext,
     ) -> InferenceResult {
         let ty = value.custom.unwrap();
-        if let TypeEnum::TObj { fields, .. } = &*self.unifier.get_ty(ty) {
+        if let TypeEnum::TObj { obj_id, fields, .. } = &*self.unifier.get_ty(ty) {
             // just a fast path
             match (fields.get(&attr), ctx == ExprContext::Store) {
                 (Some((ty, true)), _) | (Some((ty, false)), false) => Ok(*ty),
                 (Some((_, false)), true) => {
                     report_error(&format!("Field `{attr}` is immutable"), value.location)
                 }
-                (None, _) => {
-                    let t = self.unifier.stringify(ty);
-                    report_error(
-                        &format!("`{t}::{attr}` field/method does not exist"),
-                        value.location,
-                    )
+                (None, mutable) => {
+                    // Check whether it is a class attribute
+                    let defs = self.top_level.definitions.read();
+                    let result = {
+                        if let TopLevelDef::Class { attributes, .. } = &*defs[obj_id.0].read() {
+                            attributes.iter().find_map(|f| {
+                                if f.0 == attr {
+                                    return Some(f.1);
+                                }
+                                None
+                            })
+                        } else {
+                            None
+                        }
+                    };
+                    match result {
+                        Some(res) if !mutable => Ok(res),
+                        Some(_) => report_error(
+                            &format!("Class Attribute `{attr}` is immutable"),
+                            value.location,
+                        ),
+                        None => {
+                            let t = self.unifier.stringify(ty);
+                            report_error(
+                                &format!("`{t}::{attr}` field/method does not exist"),
+                                value.location,
+                            )
+                        }
+                    }
                 }
             }
+        } else if let TypeEnum::TFunc(sign) = &*self.unifier.get_ty(ty) {
+            // Access Class Attributes of classes with __init__ function using Class names e.g. Foo.ATTR1
+            let result = {
+                self.top_level.definitions.read().iter().find_map(|def| {
+                    if let Some(rear_guard) = def.try_read() {
+                        if let TopLevelDef::Class { name, attributes, .. } = &*rear_guard {
+                            if name.to_string() == self.unifier.stringify(sign.ret) {
+                                return attributes.iter().find_map(|f| {
+                                    if f.0 == attr {
+                                        return Some(f.clone().1);
+                                    }
+                                    None
+                                });
+                            }
+                        }
+                    }
+                    None
+                })
+            };
+            match result {
+                Some(f) if ctx != ExprContext::Store => Ok(f),
+                Some(_) => {
+                    report_error(&format!("Class Attribute `{attr}` is immutable"), value.location)
+                }
+                None => self.infer_general_attribute(value, attr, ctx),
+            }
         } else {
-            let attr_ty = self.unifier.get_dummy_var().ty;
-            let fields = once((
-                attr.into(),
-                RecordField::new(attr_ty, ctx == ExprContext::Store, Some(value.location)),
-            ))
-            .collect();
-            let record = self.unifier.add_record(fields);
-            self.constrain(value.custom.unwrap(), record, &value.location)?;
-            Ok(attr_ty)
+            self.infer_general_attribute(value, attr, ctx)
         }
     }
 

nac3core/src/typecheck/type_inferencer/test.rs

@@ -289,6 +289,7 @@ impl TestEnvironment {
                     object_id: DefinitionId(i),
                     type_vars: Vec::default(),
                     fields: Vec::default(),
+                    attributes: Vec::default(),
                     methods: Vec::default(),
                     ancestors: Vec::default(),
                     resolver: None,
@@ -331,6 +332,7 @@ impl TestEnvironment {
                 object_id: DefinitionId(defs + 1),
                 type_vars: vec![tvar.ty],
                 fields: [("a".into(), tvar.ty, true)].into(),
+                attributes: Vec::default(),
                 methods: Vec::default(),
                 ancestors: Vec::default(),
                 resolver: None,
@@ -365,6 +367,7 @@ impl TestEnvironment {
                 object_id: DefinitionId(defs + 2),
                 type_vars: Vec::default(),
                 fields: [("a".into(), int32, true), ("b".into(), fun, true)].into(),
+                attributes: Vec::default(),
                 methods: Vec::default(),
                 ancestors: Vec::default(),
                 resolver: None,
@@ -393,6 +396,7 @@ impl TestEnvironment {
                 object_id: DefinitionId(defs + 3),
                 type_vars: Vec::default(),
                 fields: [("a".into(), bool, true), ("b".into(), fun, false)].into(),
+                attributes: Vec::default(),
                 methods: Vec::default(),
                 ancestors: Vec::default(),
                 resolver: None,

nac3standalone/demo/src/ndarray.py

@@ -71,17 +71,44 @@ def output_ndarray_float_2(n: ndarray[float, Literal[2]]):
 def consume_ndarray_1(n: ndarray[float, Literal[1]]):
     pass
 
+def consume_ndarray_2(n: ndarray[float, Literal[2]]):
+    pass
+
 def test_ndarray_ctor():
     n: ndarray[float, Literal[1]] = np_ndarray([1])
     consume_ndarray_1(n)
 
 def test_ndarray_empty():
-    n: ndarray[float, 1] = np_empty([1])
-    consume_ndarray_1(n)
+    n1: ndarray[float, 1] = np_empty([1])
+    consume_ndarray_1(n1)
+
+    n2: ndarray[float, 1] = np_empty(10)
+    consume_ndarray_1(n2)
+
+    n3: ndarray[float, 1] = np_empty((2,))
+    consume_ndarray_1(n3)
+
+    n4: ndarray[float, 2] = np_empty((4, 4))
+    consume_ndarray_2(n4)
+
+    dim4 = (5, 2)
+    n5: ndarray[float, 2] = np_empty(dim4)
+    consume_ndarray_2(n5)
 
 def test_ndarray_zeros():
-    n: ndarray[float, 1] = np_zeros([1])
-    output_ndarray_float_1(n)
+    n1: ndarray[float, 1] = np_zeros([1])
+    output_ndarray_float_1(n1)
+
+    k = 3 + int32(n1[0]) # to test variable shape inputs
+    n2: ndarray[float, 1] = np_zeros(k * k)
+    output_ndarray_float_1(n2)
+
+    n3: ndarray[float, 1] = np_zeros((k * 2,))
+    output_ndarray_float_1(n3)
+
+    dim4 = (3, 2 * k)
+    n4: ndarray[float, 2] = np_zeros(dim4)
+    output_ndarray_float_2(n4)
 
 def test_ndarray_ones():
     n: ndarray[float, 1] = np_ones([1])