core: Implement elementwise comparison operators

nac3core/src/codegen/expr.rs

@@ -1390,12 +1390,92 @@ pub fn gen_unaryop_expr<'ctx, G: CodeGenerator>(
 /// Generates LLVM IR for a comparison operator expression using the [`Type`] and
 /// [LLVM value][`BasicValueEnum`] of the operands.
 pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
-    _generator: &mut G,
+    generator: &mut G,
     ctx: &mut CodeGenContext<'ctx, '_>,
     left: (Option<Type>, BasicValueEnum<'ctx>),
     ops: &[ast::Cmpop],
     comparators: &[(Option<Type>, BasicValueEnum<'ctx>)],
 ) -> Result<Option<ValueEnum<'ctx>>, String> {
+    debug_assert_eq!(comparators.len(), ops.len());
+
+    if comparators.len() == 1 {
+        let left_ty = ctx.unifier.get_representative(left.0.unwrap());
+        let right_ty = ctx.unifier.get_representative(comparators[0].0.unwrap());
+
+        if left_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray) || right_ty.obj_id(&ctx.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray) {
+            let llvm_usize = generator.get_size_type(ctx.ctx);
+
+            let (Some(left_ty), lhs) = left else { unreachable!() };
+            let (Some(right_ty), rhs) = comparators[0] else { unreachable!() };
+            let op = ops[0].clone();
+
+            let is_ndarray1 = left_ty.obj_id(&ctx.unifier)
+                .is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray);
+            let is_ndarray2 = right_ty.obj_id(&ctx.unifier)
+                .is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray);
+
+            return if is_ndarray1 && is_ndarray2 {
+                let (ndarray_dtype1, _) = unpack_ndarray_var_tys(&mut ctx.unifier, left_ty);
+                let (ndarray_dtype2, _) = unpack_ndarray_var_tys(&mut ctx.unifier, right_ty);
+            
+                assert!(ctx.unifier.unioned(ndarray_dtype1, ndarray_dtype2));
+            
+                let left_val = NDArrayValue::from_ptr_val(
+                    lhs.into_pointer_value(),
+                    llvm_usize,
+                    None
+                );
+                let res = numpy::ndarray_elementwise_binop_impl(
+                    generator,
+                    ctx,
+                    ctx.primitives.bool,
+                    None,
+                    (left_val.as_ptr_value().into(), false),
+                    (rhs, false),
+                    |generator, ctx, (lhs, rhs)| {
+                        let val = gen_cmpop_expr_with_values(
+                            generator,
+                            ctx,
+                            (Some(ndarray_dtype1), lhs),
+                            &[op.clone()],
+                            &[(Some(ndarray_dtype2), rhs)],
+                        )?.unwrap().to_basic_value_enum(ctx, generator, ctx.primitives.bool)?;
+
+                        Ok(generator.bool_to_i8(ctx, val.into_int_value()).into())
+                    },
+                )?;
+            
+                Ok(Some(res.as_ptr_value().into()))
+            } else {
+                let (ndarray_dtype, _) = unpack_ndarray_var_tys(
+                    &mut ctx.unifier,
+                    if is_ndarray1 { left_ty } else { right_ty },
+                );
+                let res = numpy::ndarray_elementwise_binop_impl(
+                    generator,
+                    ctx,
+                    ctx.primitives.bool,
+                    None,
+                    (lhs, !is_ndarray1),
+                    (rhs, !is_ndarray2),
+                    |generator, ctx, (lhs, rhs)| {
+                        let val = gen_cmpop_expr_with_values(
+                            generator,
+                            ctx,
+                            (Some(ndarray_dtype), lhs),
+                            &[op.clone()],
+                            &[(Some(ndarray_dtype), rhs)],
+                        )?.unwrap().to_basic_value_enum(ctx, generator, ctx.primitives.bool)?;
+
+                        Ok(generator.bool_to_i8(ctx, val.into_int_value()).into())
+                    },
+                )?;
+            
+                Ok(Some(res.as_ptr_value().into()))
+            }
+        }
+    }
+
     let cmp_val = izip!(chain(once(&left), comparators.iter()), comparators.iter(), ops.iter(),)
         .fold(Ok(None), |prev: Result<Option<_>, String>, (lhs, rhs, op)| {
             let (left_ty, lhs) = lhs;
@@ -1465,6 +1545,7 @@ pub fn gen_cmpop_expr_with_values<'ctx, G: CodeGenerator>(
                 } else {
                     unimplemented!()
                 };
+
             Ok(prev?.map(|v| ctx.builder.build_and(v, current, "cmp").unwrap()).or(Some(current)))
         })?;
     

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: [127]\n}\n",
+    "Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [156]\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[typevar116]\", \"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: [\"typevar116\"]\n}\n",
+    "Class {\nname: \"B\",\nancestors: [\"B[typevar145]\", \"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: [\"typevar145\"]\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: [129]\n}\n",
+    "Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [158]\n}\n",
-    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [134]\n}\n",
+    "Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [163]\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[typevar115, typevar116]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar115\", \"typevar116\"]\n}\n",
+    "Class {\nname: \"A\",\nancestors: [\"A[typevar144, typevar145]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar144\", \"typevar145\"]\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: [135]\n}\n",
+    "Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [164]\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: [143]\n}\n",
+    "Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [172]\n}\n",
 ]

nac3core/src/typecheck/magic_methods.rs

@@ -483,6 +483,33 @@ pub fn typeof_unaryop(
     })
 }
 
+/// Returns the return type given a comparison operator and its primitive operands.
+pub fn typeof_cmpop(
+    unifier: &mut Unifier,
+    primitives: &PrimitiveStore,
+    _op: &Cmpop,
+    lhs: Type,
+    rhs: Type,
+) -> Result<Option<Type>, String> {
+    let is_left_ndarray = lhs
+        .obj_id(unifier)
+        .is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray);
+    let is_right_ndarray = rhs
+        .obj_id(unifier)
+        .is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray);
+
+    Ok(Some(if is_left_ndarray || is_right_ndarray {
+        let brd = typeof_ndarray_broadcast(unifier, primitives, lhs, rhs)?;
+        let (_, ndims) = unpack_ndarray_var_tys(unifier, brd);
+
+        make_ndarray_ty(unifier, primitives, Some(primitives.bool), Some(ndims))
+    } else if unifier.unioned(lhs, rhs) {
+        primitives.bool
+    } else {
+        return Ok(None)
+    }))
+}
+
 pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifier) {
     let PrimitiveStore {
         int32: int32_t,
@@ -508,8 +535,8 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
         impl_mod(unifier, store, t, &[t, ndarray_int_t], None);
         impl_invert(unifier, store, t, Some(t));
         impl_not(unifier, store, t, Some(bool_t));
-        impl_comparison(unifier, store, t, &[t], Some(bool_t));
+        impl_comparison(unifier, store, t, &[t, ndarray_int_t], None);
-        impl_eq(unifier, store, t, &[t], Some(bool_t));
+        impl_eq(unifier, store, t, &[t, ndarray_int_t], None);
     }
     for t in [int32_t, int64_t] {
         impl_sign(unifier, store, t, Some(t));
@@ -525,12 +552,13 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
     impl_mod(unifier, store, float_t, &[float_t, ndarray_float_t], None);
     impl_sign(unifier, store, float_t, Some(float_t));
     impl_not(unifier, store, float_t, Some(bool_t));
-    impl_comparison(unifier, store, float_t, &[float_t], Some(bool_t));
+    impl_comparison(unifier, store, float_t, &[float_t, ndarray_float_t], None);
-    impl_eq(unifier, store, float_t, &[float_t], Some(bool_t));
+    impl_eq(unifier, store, float_t, &[float_t, ndarray_float_t], None);
 
     /* bool ======== */
+    let ndarray_bool_t = make_ndarray_ty(unifier, store, Some(bool_t), None);
     impl_not(unifier, store, bool_t, Some(bool_t));
-    impl_eq(unifier, store, bool_t, &[bool_t], Some(bool_t));
+    impl_eq(unifier, store, bool_t, &[bool_t, ndarray_bool_t], None);
 
     /* ndarray ===== */
     let ndarray_usized_ndims_tvar = unifier.get_fresh_const_generic_var(size_t, Some("ndarray_ndims".into()), None);
@@ -544,4 +572,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
     impl_mod(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
     impl_sign(unifier, store, ndarray_t, Some(ndarray_t));
     impl_invert(unifier, store, ndarray_t, Some(ndarray_t));
+    impl_eq(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
+    impl_comparison(unifier, store, ndarray_t, &[ndarray_unsized_t, ndarray_unsized_dtype_t], None);
 }

nac3core/src/typecheck/type_inferencer/mod.rs

@@ -1271,22 +1271,45 @@ impl<'a> Inferencer<'a> {
         ops: &[ast::Cmpop],
         comparators: &[ast::Expr<Option<Type>>],
     ) -> InferenceResult {
-        let boolean = self.primitives.bool;
+        if ops.len() > 1 && once(left).chain(comparators).any(|expr| expr.custom.unwrap().obj_id(self.unifier).is_some_and(|id| id == PRIMITIVE_DEF_IDS.ndarray)) {
+            return Err(HashSet::from([String::from("Comparator chaining with ndarray types not supported")]))
+        }
+
         for (a, b, c) in izip!(once(left).chain(comparators), comparators, ops) {
             let method = comparison_name(c)
                 .ok_or_else(|| HashSet::from([
                     "unsupported comparator".to_string()
                 ]))?
                 .into();
+
+            let ret = typeof_cmpop(
+                self.unifier,
+                self.primitives,
+                c,
+                a.custom.unwrap(),
+                b.custom.unwrap(),
+            ).map_err(|e| HashSet::from([format!("{e} (at {})", b.location)]))?;
+            
             self.build_method_call(
                 a.location,
                 method,
                 a.custom.unwrap(),
                 vec![b.custom.unwrap()],
-                Some(boolean),
+                ret,
             )?;
         }
-        Ok(boolean)
+
+        let res_lhs = comparators.iter().rev().nth(1).unwrap_or(left);
+        let res_rhs = comparators.iter().rev().nth(0).unwrap();
+        let res_op = ops.iter().rev().nth(0).unwrap();
+
+        Ok(typeof_cmpop(
+            self.unifier,
+            self.primitives,
+            res_op,
+            res_lhs.custom.unwrap(),
+            res_rhs.custom.unwrap(),
+        ).unwrap().unwrap())
     }
 
     /// Infers the type of a subscript expression on an `ndarray`.

nac3standalone/demo/src/ndarray.py

@@ -455,6 +455,174 @@ def test_ndarray_inv():
     output_ndarray_int32_2(x_int32)
     output_ndarray_int32_2(y_int32)
 
+def test_ndarray_eq():
+    x = np_identity(2)
+    y = x == np_full([2, 2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_eq_broadcast():
+    x = np_identity(2)
+    y = x == np_full([2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_eq_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 0.0 == x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_eq_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x == 0.0
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ne():
+    x = np_identity(2)
+    y = x != np_full([2, 2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ne_broadcast():
+    x = np_identity(2)
+    y = x != np_full([2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ne_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 0.0 != x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ne_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x != 0.0
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_lt():
+    x = np_identity(2)
+    y = x < np_full([2, 2], 1.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_lt_broadcast():
+    x = np_identity(2)
+    y = x < np_full([2], 1.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_lt_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 1.0 < x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_lt_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x < 1.0
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_le():
+    x = np_identity(2)
+    y = x <= np_full([2, 2], 0.5)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_le_broadcast():
+    x = np_identity(2)
+    y = x <= np_full([2], 0.5)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_le_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 0.5 <= x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_le_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x <= 0.5
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_gt():
+    x = np_identity(2)
+    y = x > np_full([2, 2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_gt_broadcast():
+    x = np_identity(2)
+    y = x > np_full([2], 0.0)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_gt_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 0.0 > x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_gt_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x > 0.0
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ge():
+    x = np_identity(2)
+    y = x >= np_full([2, 2], 0.5)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ge_broadcast():
+    x = np_identity(2)
+    y = x >= np_full([2], 0.5)
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ge_broadcast_lhs_scalar():
+    x = np_identity(2)
+    y = 0.5 >= x
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
+def test_ndarray_ge_broadcast_rhs_scalar():
+    x = np_identity(2)
+    y = x >= 0.5
+
+    output_ndarray_float_2(x)
+    output_ndarray_bool_2(y)
+
 def run() -> int32:
     test_ndarray_ctor()
     test_ndarray_empty()
@@ -517,5 +685,29 @@ def run() -> int32:
     test_ndarray_pos()
     test_ndarray_neg()
     test_ndarray_inv()
+    test_ndarray_eq()
+    test_ndarray_eq_broadcast()
+    test_ndarray_eq_broadcast_lhs_scalar()
+    test_ndarray_eq_broadcast_rhs_scalar()
+    test_ndarray_ne()
+    test_ndarray_ne_broadcast()
+    test_ndarray_ne_broadcast_lhs_scalar()
+    test_ndarray_ne_broadcast_rhs_scalar()
+    test_ndarray_lt()
+    test_ndarray_lt_broadcast()
+    test_ndarray_lt_broadcast_lhs_scalar()
+    test_ndarray_lt_broadcast_rhs_scalar()
+    test_ndarray_lt()
+    test_ndarray_le_broadcast()
+    test_ndarray_le_broadcast_lhs_scalar()
+    test_ndarray_le_broadcast_rhs_scalar()
+    test_ndarray_gt()
+    test_ndarray_gt_broadcast()
+    test_ndarray_gt_broadcast_lhs_scalar()
+    test_ndarray_gt_broadcast_rhs_scalar()
+    test_ndarray_gt()
+    test_ndarray_ge_broadcast()
+    test_ndarray_ge_broadcast_lhs_scalar()
+    test_ndarray_ge_broadcast_rhs_scalar()
 
     return 0