[Lang] Move real function out of the experimental module (#8399)

Issue: #

### Brief Summary

<!--
copilot:summary
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### <samp>🤖 Generated by Copilot at 8c46960</samp>

This pull request updates the `real_func` examples and tests to use the
stable `ti.real_func` decorator and the new vector, matrix, and field
APIs. It also refactors some code for readability, performance, and
consistency, and removes the deprecated `experimental` module.

### Walkthrough

<!--
copilot:walkthrough
-->
### <samp>🤖 Generated by Copilot at 8c46960</samp>

* Remove `experimental` module and move `real_func` decorator to
top-level `taichi` module
([link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-e0e39c57bc92c0e1da4c831f8820a4082a3cc26a9b88962bee72964dfa26a74aL13-R13),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-a157043b38542c8145447ff342fda65fe4d54fb777fe514daa70007e83e20dc1L1235-R1235))
* Update all examples and tests that use `real_func` decorator to import
it from `taichi` module instead of `experimental` module
([link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-9cbae292e39bc9b37e4cfab4bfef6f363788d06ecb7757753ee5c0ba7ad0afcdL51-R51),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-9cbae292e39bc9b37e4cfab4bfef6f363788d06ecb7757753ee5c0ba7ad0afcdL58-R58),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-9cbae292e39bc9b37e4cfab4bfef6f363788d06ecb7757753ee5c0ba7ad0afcdL72-R82),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-9cbae292e39bc9b37e4cfab4bfef6f363788d06ecb7757753ee5c0ba7ad0afcdL136-R136),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f6098eab3d43899f2146cafc8454b2d9bae86064709eb2eeb43e0edbf459f22fL33-R33),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f6098eab3d43899f2146cafc8454b2d9bae86064709eb2eeb43e0edbf459f22fL55-R55),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f6098eab3d43899f2146cafc8454b2d9bae86064709eb2eeb43e0edbf459f22fL93-R98),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-86667a5be06e5995f4b15199aa3d4b655e64cceed6d108185d5cc71e03f0bb1fL43-R53),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-86667a5be06e5995f4b15199aa3d4b655e64cceed6d108185d5cc71e03f0bb1fL89-R94),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-86667a5be06e5995f4b15199aa3d4b655e64cceed6d108185d5cc71e03f0bb1fL108-R108),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL51-R51),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL61-R61),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL68-R68),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL78-R78),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL89-R89),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL116-R116),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f9f9a26653afb587b73d90d08c099a8236820fc72b4d247e001954d620073ebcL124-R124),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL66-R71),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL80-R80),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL86-R86),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL95-R95),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL105-R105),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL119-R119),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL125-R125),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL132-R132),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-52ca6a00561cb88b076a00d2ae2a30dca3d46713e52f0f5ca6b52ecfd95545daL344-R344),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-f2d9c4a8c504d2073549cde99b31a733a2f39bba4ce9f062cbaa09e1be17aa87L243-R243),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L11-R11),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L29-R29),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L49-R49),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L153-R153),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L185-R185),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L194-R194),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L207-R207),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L221-R221),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L242-R242),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L259-R259),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L281-R281),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L295-R295),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L310-R310),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L329-R329),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L352-R352),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L451-R451),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L469-R469),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L484-R484),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L501-R501),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L515-R515),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-d6f5c74e17462c8ff96d5bba06ebf81d16c015ca667fa945513a80be17bef017L533-R533),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-ca3c8d1edb25b6a7f4affbb79b2e3e74f73b3757e5d465258ce42ea9eb09fbc0L1035-R1035),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-ca3c8d1edb25b6a7f4affbb79b2e3e74f73b3757e5d465258ce42ea9eb09fbc0L1052-R1052),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-ca3c8d1edb25b6a7f4affbb79b2e3e74f73b3757e5d465258ce42ea9eb09fbc0L1134-R1134),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-ca3c8d1edb25b6a7f4affbb79b2e3e74f73b3757e5d465258ce42ea9eb09fbc0L1149-R1149),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-85fb062b09589d588166180e3c7954753018dc39474d3846346f2a8bb3faac32L480-R480),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-85fb062b09589d588166180e3c7954753018dc39474d3846346f2a8bb3faac32L494-R494),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-8641463ffef94529453efd945e02d056e4339417cc65aad074d4e6b3ef093244L49-R53),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-e206c19691b4678b401a5e2787000e93ab0b0060cbf4ac2625b51f87599d98d8L218-R218),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-e206c19691b4678b401a5e2787000e93ab0b0060cbf4ac2625b51f87599d98d8L238-R238),
[link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-e206c19691b4678b401a5e2787000e93ab0b0060cbf4ac2625b51f87599d98d8L258-R258))
* Delete `python/taichi/experimental.py` file as it is no longer needed
([link](https://github.com/taichi-dev/taichi/pull/8399/files?diff=unified&w=0#diff-60267f25c1e1dfada9487235a4a793b63a49aa3d33c93b8449e24ac821a33174))

python/taichi/__init__.py

@@ -10,7 +10,7 @@
 from taichi.types.primitive_types import *
 
 
-from taichi import ad, algorithms, experimental, graph, linalg, math, sparse, tools, types
+from taichi import ad, algorithms, graph, linalg, math, sparse, tools, types
 from taichi.ui import GUI, hex_to_rgb, rgb_to_hex, ui
 
 # Issue#2223: Do not reorder, or we're busted with partially initialized module

python/taichi/examples/real_func/algorithm/marching_squares.py

@@ -48,14 +48,14 @@
 iTime = ti.field(float, shape=())
 
 
-@ti.experimental.real_func
+@ti.real_func
 def hash22(p_: tm.vec2) -> tm.vec2:
     n = tm.sin(tm.dot(p_, tm.vec2(41, 289)))
     p = tm.fract(tm.vec2(262144, 32768) * n)
     return tm.sin(p * 6.28 + iTime[None])
 
 
-@ti.experimental.real_func
+@ti.real_func
 def noise(p_: tm.vec2) -> float:
     ip = tm.floor(p_)
     p = p_ - ip
@@ -69,17 +69,17 @@ def noise(p_: tm.vec2) -> float:
     return tm.mix(tm.mix(v.x, v.y, p.x), tm.mix(v.z, v.w, p.x), p.y)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def isofunc(p: tm.vec2) -> float:
     return noise(p / 4 + 1)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def interp(p1: tm.vec2, p2: tm.vec2, v1: float, v2: float, isovalue: float) -> tm.vec2:
     return tm.mix(p1, p2, (isovalue - v1) / (v2 - v1))
 
 
-@ti.experimental.real_func
+@ti.real_func
 def get_vertex(vertex_id: int, values: tm.vec4, isovalue: float) -> tm.vec2:
     v = tm.vec2(0)
     square = [tm.vec2(0), tm.vec2(1, 0), tm.vec2(1, 1), tm.vec2(0, 1)]
@@ -133,7 +133,7 @@ def march_squares() -> int:
     return edges.length()
 
 
-@ti.experimental.real_func
+@ti.real_func
 def dseg(p_: tm.vec2, a: tm.vec2, b_: tm.vec2) -> ti.f32:
     p = p_ - a
     b = b_ - a

python/taichi/examples/real_func/algorithm/poisson_disk_sampling.py

@@ -30,7 +30,7 @@
 sample_count = ti.field(int, shape=())
 
 
-@ti.experimental.real_func
+@ti.real_func
 def coord_to_index(p: tm.vec2) -> tm.ivec2:
     return (p * tm.vec2(grid_n)).cast(int)
 
@@ -52,7 +52,7 @@ def refresh_scene():
         img[i, j] = tm.vec3(1)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def find_nearest_point(p: tm.vec2) -> typing.Tuple[float, tm.vec2]:
     x, y = coord_to_index(p)
     dmin = 1e5
@@ -90,12 +90,12 @@ def poisson_disk_sample(num_samples: int) -> int:
     return tail[None]
 
 
-@ti.experimental.real_func
+@ti.real_func
 def hash21(p: tm.vec2) -> float:
     return tm.fract(tm.sin(tm.dot(p, tm.vec2(127.619, 157.583))) * 43758.5453)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def sample_dist(uv_: tm.vec2) -> tm.vec4:
     uv = uv_ * iResolution
     x, y = tm.clamp(0, iResolution - 1, uv).cast(int)

python/taichi/examples/real_func/graph/stable_fluid_graph.py

@@ -40,17 +40,17 @@ def sample_impl(qf: ti.template(), u: int, v: int):
     return qf[I]
 
 
-@ti.experimental.real_func
+@ti.real_func
 def sample2(qf: ti.types.ndarray(ndim=2), u: int, v: int) -> vec2:
     return sample_impl(qf, u, v)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def sample3(qf: ti.types.ndarray(ndim=2), u: int, v: int) -> vec3:
     return sample_impl(qf, u, v)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def sample0(qf: ti.types.ndarray(ndim=2), u: int, v: int) -> float:
     return sample_impl(qf, u, v)
 
@@ -86,12 +86,12 @@ def bilerp_impl(vf: ti.template(), p):
     return lerp(lerp(a, b, fu), lerp(c, d, fu), fv)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def bilerp2(vf: ti.types.ndarray(ndim=2), p: vec2) -> vec2:
     return bilerp_impl(vf, p)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def bilerp3(vf: ti.types.ndarray(ndim=2), p: vec2) -> vec3:
     return bilerp_impl(vf, p)
 
@@ -105,7 +105,7 @@ def bilerp(vf: ti.template(), p):
 
 
 # 3rd order Runge-Kutta
-@ti.experimental.real_func
+@ti.real_func
 def backtrace(vf: ti.types.ndarray(ndim=2), p: vec2, dt_: float) -> vec2:
     v1 = bilerp(vf, p)
     p1 = p - 0.5 * dt_ * v1

python/taichi/examples/real_func/rendering/cornell_box.py

@@ -48,7 +48,7 @@
 )
 
 
-@ti.experimental.real_func
+@ti.real_func
 def rotate(a: vec3) -> mat3:
     s, c = sin(a), cos(a)
     return (
@@ -58,14 +58,14 @@ def rotate(a: vec3) -> mat3:
     )
 
 
-@ti.experimental.real_func
+@ti.real_func
 def signed_distance(obj: SDFObject, pos: vec3) -> float:
     p = obj.transform.matrix @ (pos - obj.transform.position)
     q = abs(p) - obj.transform.scale
     return length(max(q, 0)) + min(max(q.x, max(q.y, q.z)), 0)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def nearest_object(p: vec3) -> (int, float):
     index, min_dis = 0, 1e32
     for i in ti.static(range(8)):
@@ -75,7 +75,7 @@ def nearest_object(p: vec3) -> (int, float):
     return index, min_dis
 
 
-@ti.experimental.real_func
+@ti.real_func
 def calc_normal(obj: SDFObject, p: vec3) -> vec3:
     e = vec2(1, -1) * 0.5773 * 0.005
     return normalize(
@@ -86,7 +86,7 @@ def calc_normal(obj: SDFObject, p: vec3) -> vec3:
     )
 
 
-@ti.experimental.real_func
+@ti.real_func
 def raycast(ray: Ray) -> (SDFObject, vec3, bool):
     w, s, d, cerr = 1.6, 0.0, 0.0, 1e32
     index, t, position, hit = 0, 0.005, vec3(0), False
@@ -113,15 +113,15 @@ def raycast(ray: Ray) -> (SDFObject, vec3, bool):
     return objects[index], position, hit
 
 
-@ti.experimental.real_func
+@ti.real_func
 def hemispheric_sampling(normal: vec3) -> vec3:
     z = 2.0 * ti.random() - 1.0
     a = ti.random() * 2.0 * pi
     xy = sqrt(1.0 - z * z) * vec2(sin(a), cos(a))
     return normalize(normal + vec3(xy, z))
 
 
-@ti.experimental.real_func
+@ti.real_func
 def raytrace(ray: Ray) -> Ray:
     for _ in range(3):
         object, position, hit = raycast(ray)

python/taichi/examples/real_func/rendering/taichi_ngp.py

@@ -63,12 +63,12 @@ def depth2img(depth):
 
 
 # <----------------- hash table util code ----------------->
-@ti.experimental.real_func
+@ti.real_func
 def calc_dt(t: data_type, exp_step_factor: data_type, grid_size: int, scale: data_type) -> data_type:
     return ti.math.clamp(t * exp_step_factor, SQRT3_MAX_SAMPLES, SQRT3_2 * scale / grid_size)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def __expand_bits(v_: uvec3) -> uvec3:
     v = (v_ * ti.uint32(0x00010001)) & ti.uint32(0xFF0000FF)
     v = (v * ti.uint32(0x00000101)) & ti.uint32(0x0F00F00F)
@@ -77,13 +77,13 @@ def __expand_bits(v_: uvec3) -> uvec3:
     return v
 
 
-@ti.experimental.real_func
+@ti.real_func
 def __morton3D(xyz_: uvec3) -> ti.u32:
     xyz = __expand_bits(xyz_)
     return xyz[0] | (xyz[1] << 1) | (xyz[2] << 2)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def fast_hash(pos_grid_local: uvec3) -> ti.u32:
     result = ti.uint32(0)
     primes = uvec3(ti.uint32(1), ti.uint32(2654435761), ti.uint32(805459861))
@@ -92,7 +92,7 @@ def fast_hash(pos_grid_local: uvec3) -> ti.u32:
     return result
 
 
-@ti.experimental.real_func
+@ti.real_func
 def under_hash(pos_grid_local: uvec3, resolution: ti.u32) -> ti.u32:
     result = ti.uint32(0)
     stride = ti.uint32(1)
@@ -102,7 +102,7 @@ def under_hash(pos_grid_local: uvec3, resolution: ti.u32) -> ti.u32:
     return result
 
 
-@ti.experimental.real_func
+@ti.real_func
 def grid_pos2hash_index(indicator: ti.i32, pos_grid_local: uvec3, resolution: ti.u32, map_size: ti.u32) -> ti.u32:
     hash_result = ti.uint32(0)
     if indicator == 1:
@@ -116,20 +116,20 @@ def grid_pos2hash_index(indicator: ti.i32, pos_grid_local: uvec3, resolution: ti
 # <----------------- hash table util code ----------------->
 
 
-@ti.experimental.real_func
+@ti.real_func
 def random_in_unit_disk() -> tf_vec2:
     theta = 2.0 * np.pi * ti.random()
     return ti.Vector([ti.sin(theta), ti.cos(theta)])
 
 
-@ti.experimental.real_func
+@ti.real_func
 def random_normal() -> tf_vec2:
     x = ti.random() * 2.0 - 1.0
     y = ti.random() * 2.0 - 1.0
     return tf_vec2(x, y)
 
 
-@ti.experimental.real_func
+@ti.real_func
 def dir_encode_func(dir_: tf_vec3) -> tf_vec32:
     out_feat = tf_vec32(0.0)
     dir_n = dir_ / dir_.norm()
@@ -341,7 +341,7 @@ def reset(self):
         for i, j in ti.ndrange(self.N_rays, 2):
             self.alive_indices[i * 2 + j] = i
 
-    @ti.experimental.real_func
+    @ti.real_func
     def _ray_aabb_intersec(self, ray_o: tf_vec3, ray_d: tf_vec3) -> tf_vec2:
         inv_d = 1.0 / ray_d
 

python/taichi/lang/kernel_impl.py

@@ -1232,4 +1232,4 @@ def _getattr(self, item):
     return cls
 
 
-__all__ = ["data_oriented", "func", "kernel", "pyfunc"]
+__all__ = ["data_oriented", "func", "kernel", "pyfunc", "real_func"]

tests/python/test_api.py

@@ -129,7 +129,6 @@ def _get_expected_matrix_apis():
     "dx12",
     "eig",
     "exp",
-    "experimental",
     "extension",
     "f16",
     "f32",
@@ -199,6 +198,7 @@ def _get_expected_matrix_apis():
     "random",
     "raw_div",
     "raw_mod",
+    "real_func",
     "ref",
     "rescale_index",
     "reset",

tests/python/test_argument.py

@@ -240,7 +240,7 @@ def test_struct_arg_with_matrix_real_func():
     s0 = ti.types.struct(a=mat, b=ti.f32)
     s1 = ti.types.struct(a=ti.i32, b=s0)
 
-    @ti.experimental.real_func
+    @ti.real_func
     def foo(a: s1) -> ti.i32:
         ret = a.a + a.b.b
         for i in range(3):