An error occurred while running the metagrating case

[xungu1]

Hello, I made a mistake when I ran the metagrating case of invrs _ gym for the first time. This problem also appeared in other cases. Is there a problem with where I set it ?
Will it be a problem with the python version ? My version of python is 3.8

Here 's my misinformation：
Traceback (most recent call last):
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev\pydevconsole.py", line 364, in runcode
coro = func()
File "", line 1, in
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_umd.py", line 198, in runfile
pydev_imports.execfile(filename, global_vars, local_vars) # execute the script
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_imps_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "E:\Object\simulation_up\compare\gym-main\gym-main\src\demo_1.py", line 26, in
from invrs_gym import challenges
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self.system_import(name, *args, **kwargs)
File "E:\Object\simulation_up\compare\gym-main\gym-main\src\invrs_gym_init.py", line 9, in
from invrs_gym import challenges as challenges
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self.system_import(name, *args, **kwargs)
File "E:\Object\simulation_up\compare\gym-main\gym-main\src\invrs_gym\challenges_init.py", line 1, in
from invrs_gym.challenges.bayer.challenge import bayer_sorter as bayer_sorter
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self._system_import(name, *args, **kwargs)
File "E:\Object\simulation_up\compare\gym-main\gym-main\src\invrs_gym\challenges\bayer\challenge.py", line 10, in
from fmmax import basis, fmm # type: ignore[import-untyped]
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self.system_import(name, *args, **kwargs)
File "D:\test_code\virtuallab\test_file\lib\site-packages\fmmax_init.py", line 5, in
from . import (
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self._system_import(name, *args, **kwargs)
File "D:\test_code\virtuallab\test_file\lib\site-packages\fmmax\fields.py", line 11, in
from fmmax import basis, fft, fmm, scattering, utils
File "D:\BaiduNetdiskDownload\Pycharm Pro 2023\PyCharm 2023.1\plugins\python\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 21, in do_import
module = self._system_import(name, *args, **kwargs)
File "D:\test_code\virtuallab\test_file\lib\site-packages\fmmax\fmm.py", line 47, in
formulation: Formulation | VectorFn,
TypeError: unsupported operand type(s) for |: 'EnumMeta' and '_CallableGenericAlias'

[mfschubert]

Thanks for reporting this. It seems the Python version specified in the pyproject.toml is incorrect, since I am using some python 3.10 language features. I’ll make an update.

Will it be possible for you to use python 3.10 or newer?

[xungu1]

Thank you for your answer. After replacing the python version with 3.10, the program can run normally. In addition, I have tried the given program for optimizing metagrating. I would like to ask whether it can be used to optimize the diffractive splitter ? If yes, how can I modify the program ?
import numpy as np
from invrs_gym import challenges

challenge = challenges.metagrating()

import jax

params = challenge.component.init(jax.random.PRNGKey(0))

def loss_fn(params):
response, aux = challenge.component.response(params)
loss = challenge.loss(response)
metrics = challenge.metrics(response, params=params, aux=aux)
efficiency = metrics["average_efficiency"]
return loss, (response, efficiency)

import invrs_opt

opt = invrs_opt.density_lbfgsb(beta=4)
state = opt.init(params) # Initialize optimizer state using the initial parameters.

@jax.jit
def step_fn(state):
params = opt.params(state)
(value, (_, efficiency)), grad = jax.value_and_grad(loss_fn, has_aux=True)(params)
state = opt.update(grad=grad, value=value, params=params, state=state)
return state, (params, efficiency)

Call step_fn repeatedly to optimize, and store the results of each evaluation.

efficiencies = []
for _ in range(65):
state, (params, efficiency) = step_fn(state)
efficiencies.append(efficiency)

import matplotlib.pyplot as plt
import numpy as onp
from skimage import measure

ax = plt.subplot(121)
ax.plot(onp.asarray(efficiencies) * 100)
ax.set_xlabel("Step")
ax.set_ylabel("Diffraction efficiency into +1 order (%)")

ax = plt.subplot(122)
im = ax.imshow(1 - params.array, cmap="gray")
im.set_clim([-2, 1])

contours = measure.find_contours(onp.asarray(params.array))
for c in contours:
ax.plot(c[:, 1], c[:, 0], "k", lw=1)

ax.set_xticks([])
ax.set_yticks([])
plt.show()

print(f"Final efficiency: {efficiencies[-1] * 100:.1f}%")

[mfschubert]

You should be able to design a diffractive supplier by replacing challenges.metagrating() with challenges.diffractive_splitter(). Check the challenges/__init__.py for a consolidated view of all the challenge constructors (https://github.com/invrs-io/gym/blob/main/src/invrs_gym/challenges/__init__.py).

FYI if you surround your code with triple backticks it will format nicely: https://docs.github.com/en/get-started/writing-on-github/getting-started-with-writing-and-formatting-on-github/basic-writing-and-formatting-syntax#quoting-code