# ValueError in tuner.fit()

**URL:** <https://discuss.ray.io/t/valueerror-in-tuner-fit/10539>\
**Category:** Ray Tune\
**Created:** [May 5, 2023, 8:20pm UTC](https://discuss.ray.io/t/valueerror-in-tuner-fit/10539 "2023-05-05T20:20:59Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![fischi1611](https://avatars.discourse-cdn.com/v4/letter/f/96bed5/32.png) [@fischi1611](https://discuss.ray.io/u/fischi1611)\
**Post date:** [May 5, 2023, 8:21pm UTC](https://discuss.ray.io/t/valueerror-in-tuner-fit/10539/1 "2023-05-05T20:21:00Z")

</div>

Hello all together,

i’ve been working on an hyperparametertuning with Ray and i am running into following error:

Following is the last cell of my ipynb:

```auto
def main(num_samples=10, max_num_epochs=10, gpus_per_trial=2):

    config={
        "dropout_rate": tune.sample_from(lambda _: np.random.randint(1, 450)*0.001),
        "filter_size": tune.sample_from(lambda _: np.random.choice([3,5,7,9,11,15], (1,3))), 
        "nr_of_filters": tune.sample_from(lambda _: np.random.choice([2,4,6,8,12,16,32,48,64,96,128,132,148,196,224,256], (1,4))),
        "LR": tune.choice([1e-1, 1e-2, 1e-3, 1e-4, 1e-5, 5e-1, 5e-2, 5e-3, 5e-4, 5e-5]),
        'batch_size' : tune.choice([1,2,3,5,7])
    }

    scheduler = ASHAScheduler(
        max_t=max_num_epochs,
        grace_period=1,
        reduction_factor=2)
    
    tuner = tune.Tuner(
        tune.with_resources(
            tune.with_parameters(train),
            resources={"cpu": 8, "gpu": gpus_per_trial}
        ),
        tune_config=tune.TuneConfig(
            metric="loss",
            mode="min",
            scheduler=scheduler,
            num_samples=num_samples,
        ),
        param_space=config,
    )
    results = tuner.fit()
    
    best_result = results.get_best_result("loss", "min")

    print("Best trial config: {}".format(best_result.config))
    print("Best trial final validation loss: {}".format(
        best_result.metrics["loss"]))
    print("Best trial final validation accuracy: {}".format(
        best_result.metrics["accuracy"]))

    test_best_model(best_result)

main(num_samples=1, max_num_epochs=2, gpus_per_trial=0)

```

Error:

```auto
2023-05-05 22:06:55,519	ERROR trial_runner.py:1450 -- Trial train_5ccca_00000: Error happened when processing _ExecutorEventType.TRAINING_RESULT.
ray.exceptions.RayTaskError(ValueError): ray::ImplicitFunc.train() (pid=3964, ip=127.0.0.1, repr=train)
  File "python\ray\_raylet.pyx", line 877, in ray._raylet.execute_task
  File "python\ray\_raylet.pyx", line 881, in ray._raylet.execute_task
  File "python\ray\_raylet.pyx", line 821, in ray._raylet.execute_task.function_executor
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\_private\function_manager.py", line 670, in actor_method_executor
    return method(__ray_actor, *args, **kwargs)
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\util\tracing\tracing_helper.py", line 460, in _resume_span
    return method(self, *_args, **_kwargs)
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\tune\trainable\trainable.py", line 384, in train
    raise skipped from exception_cause(skipped)
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\tune\trainable\function_trainable.py", line 336, in entrypoint
    return self._trainable_func(
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\util\tracing\tracing_helper.py", line 460, in _resume_span
    return method(self, *_args, **_kwargs)
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\tune\trainable\function_trainable.py", line 653, in _trainable_func
    output = fn()
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\tune\trainable\util.py", line 421, in _inner
    return inner(config, checkpoint_dir=None)
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\ray\tune\trainable\util.py", line 413, in inner
    return trainable(config, **fn_kwargs)
  File "C:\Users\usr\AppData\Local\Temp\ipykernel_1896\1298047504.py", line 3, in train
  File "C:\Users\usr\AppData\Local\Temp\ipykernel_1896\4257726157.py", line 6, in __init__
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\torch\nn\modules\conv.py", line 450, in __init__
    super(). __init__ (
  File "c:\Users\usr\pyVenv\py38\lib\site-packages\torch\nn\modules\conv.py", line 91, in __init__
    if out_channels % groups != 0:
**ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()**

```

I wish someone can help me out.  
Let me know if more code is needed

---

<div class="post-metadata">

**Author:** ![arturn](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/arturn/32/2096_2.png) [@arturn](https://discuss.ray.io/u/arturn)\
**Post date:** [June 1, 2023, 5:35pm UTC](https://discuss.ray.io/t/valueerror-in-tuner-fit/10539/2 "2023-06-01T17:35:36Z")

</div>

Redirecting this to the AIR folks 🙂

---

<div class="post-metadata">

**Author:** ![justinvyu](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/justinvyu/32/4309_2.png) [@justinvyu](https://discuss.ray.io/u/justinvyu)\
**Post date:** [June 1, 2023, 9:24pm UTC](https://discuss.ray.io/t/valueerror-in-tuner-fit/10539/3 "2023-06-01T21:24:44Z")

</div>

Hi @fischi1611,

This is a bug that was fixed recently. Could you try updating to the nightly version of Ray and re-run your script? See here: [Installing Ray — Ray 2.4.0](https://docs.ray.io/en/latest/ray-overview/installation.html#daily-releases-nightlies)

This was the PR that fixed it: [[Tune] Fix param space placeholder injection for numpy/pandas objects by justinvyu · Pull Request #35763 · ray-project/ray · GitHub](https://github.com/ray-project/ray/pull/35763)