# Resources not being used

**URL:** <https://discuss.ray.io/t/resources-not-being-used/3495>\
**Category:** Ray Core\
**Created:** [September 10, 2021, 7:05am UTC](https://discuss.ray.io/t/resources-not-being-used/3495 "2021-09-10T07:05:51Z")\
**Posts on this page:** 5\
**Page:** 1

<div class="post-metadata">

**Author:** ![Kai\_Yun](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/kai_yun/32/167_2.png) [@Kai\_Yun](https://discuss.ray.io/u/Kai_Yun)\
**Post date:** [September 10, 2021, 7:05am UTC](https://discuss.ray.io/t/resources-not-being-used/3495/1 "2021-09-10T07:05:51Z")

</div>

Ray version: 1.0.1

I’m using Ray Tune to train a custom trainable function. I have 12 cpus and 1 gpu on my machine, but am initiating Ray with only 5 cpus as the following code shows:

```python
ray.init(ignore_reinit_error=True, num_cpus=5)

sbedqn_config = {
    ...

    # == Parallelism & Resources ==
    "num_workers": 4,
    "num_envs_per_worker": 1,
    "num_cpus_per_worker": 1,
    "num_gpus_per_worker": 0,
    "num_cpus_for_driver": 1,
    "num_gpus": 0,
    
    ...

tune.run(
    run_or_experiment=train_sbedqn,
    name=f"SBEDQN-{sbedqn_config['env']}_{now_date}-{now_time}",
    config=exp_config,
    num_samples=1,
    stop={"training_iteration": exp_config["max_iterations"]},
    local_dir=get_save_dir(),
    checkpoint_freq=exp_config["checkpoint_freq"],
    checkpoint_at_end=True
)

```

But the log shows that only one CPU is being used:

 ![image](https://us1.discourse-cdn.com/flex020/uploads/ray/original/2X/b/b10826fa0f0c73865d40ab3a32c0a640eafa1348.png)

Can someone figure out what the issue might be?

I initially tried using version 1.6.0, but that got stuck in PENDING forever with the following log.

```auto
Required resources for this actor or task: {CPU_group_c9c02268f9e7a6f6b2c2c91eeb57308d: 1.000000} 
Available resources on this node: {4.000000/5.000000 CPU, 2.365269 GiB/2.365269 GiB memory, 1.000000/1.000000 GPU, 1.182635 GiB/1.182635 GiB object_store_memory, 1000.000000/1000.000000 bundle_group_0_c9c02268f9e7a6f6b2c2c91eeb57308d, 0.000000/1.000000 CPU_group_c9c02268f9e7a6f6b2c2c91eeb57308d, 1.000000/1.000000 node:192.168.1.5, 0.000000/1.000000 CPU_group_0_c9c02268f9e7a6f6b2c2c91eeb57308d, 1000.000000/1000.000000 bundle_group_c9c02268f9e7a6f6b2c2c91eeb57308d} 
In total there are 0 pending tasks and 4 pending actors on this node.

```

Apparently some people were able to solve this issue by having `time.sleep()` between `ray.init(...)` and `tune.run(...)` in version 0.8.x. However, no matter how long I’ve set `time.sleep()` to, it never ran for me.

So I just downgraded to version 1.0.1. Now it’s at least running, but definitely not using the resources available/requested.

---

<div class="post-metadata">

**Author:** ![xwjiang2010](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/xwjiang2010/32/1476_2.png) [@xwjiang2010](https://discuss.ray.io/u/xwjiang2010)\
**Post date:** [September 10, 2021, 3:18pm UTC](https://discuss.ray.io/t/resources-not-being-used/3495/2 "2021-09-10T15:18:38Z")

</div>

Hi @Kai_Yun,  
Thanks for reporting the issue.  
Can you provide me with a repro script for the pending issue? I would like to try it out on 1.6.0.  
BTW, have you tried specifying `resources per trial` through `tune.run`?  
By default, only 1 CPU and 0 GPU is allocated per trial.  
If you want to run multiple trials, you can specify `num_samples` \> 1.

Hope this helps!

---

<div class="post-metadata">

**Author:** ![Kai\_Yun](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/kai_yun/32/167_2.png) [@Kai\_Yun](https://discuss.ray.io/u/Kai_Yun)\
**Post date:** [September 17, 2021, 5:46am UTC](https://discuss.ray.io/t/resources-not-being-used/3495/3 "2021-09-17T05:46:39Z")

</div>

Sorry for replying so late. Apparently all the requested CPUs were actually used, but it seems like Tune just didn’t log it properly. I was able to tell that it utilizes 1 CPU for trainer and 4 CPUs for 4 workers from the warning log shown below:

```auto
(pid=22040) WARNING:tensorflow:From C:\Users\kaiyu\anaconda3\envs\ray_env\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
(pid=22040) Instructions for updating:
(pid=22040) non-resource variables are not supported in the long term
(pid=22040) 2021-09-16 21:56:03,499	ERROR syncer.py:63 -- Log sync requires rsync to be installed.
(pid=22040) 2021-09-16 21:56:03,517	INFO trainer.py:592 -- Tip: set framework=tfe or the --eager flag to enable TensorFlow eager execution
(pid=22040) 2021-09-16 21:56:03,517	INFO trainer.py:617 -- Current log_level is WARN. For more information, set 'log_level': 'INFO' / 'DEBUG' or use the -v and -vv flags.
(pid=31888) WARNING:tensorflow:From C:\Users\kaiyu\anaconda3\envs\ray_env\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
(pid=31888) Instructions for updating:
(pid=31888) non-resource variables are not supported in the long term
(pid=31260) WARNING:tensorflow:From C:\Users\kaiyu\anaconda3\envs\ray_env\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
(pid=31260) Instructions for updating:
(pid=31260) non-resource variables are not supported in the long term
(pid=15172) WARNING:tensorflow:From C:\Users\kaiyu\anaconda3\envs\ray_env\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
(pid=15172) Instructions for updating:
(pid=15172) non-resource variables are not supported in the long term
(pid=11776) WARNING:tensorflow:From C:\Users\kaiyu\anaconda3\envs\ray_env\lib\site-packages\tensorflow\python\compat\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.
(pid=11776) Instructions for updating:
(pid=11776) non-resource variables are not supported in the long term

```

From my personal experience, each warning represents each instantiation. From the looks of it, PID=22040 is the trainer and the others are workers. Thus, I think Ray actually does use all 5 CPUs as requested, but did not log it properly

* * *

I did what you recommended and set the `resources_per_trial` and commented out the resource assignment in the config dictionary:

```python
tune.run(
    run_or_experiment=train_sbedqn,
    name=f"SBEDQN-{sbedqn_config['env']}_{date}-{time}",
    config=exp_config,
    num_samples=1,
    resources_per_trial={
        "cpu": 1,
        "extra_cpu": 4
    },
    stop={"training_iteration": exp_config["max_iterations"]},
    local_dir=get_save_dir(),
    checkpoint_freq=exp_config["checkpoint_freq"],
    checkpoint_at_end=True
)

```

And it worked like a charm (or at least I think it did)! The following log showed up:

 ![image](https://us1.discourse-cdn.com/flex020/uploads/ray/original/2X/b/b117399390b38394eade6978f9347cc31549e334.png)

I just have two questions:

- Does “cpu” mean CPU for trainer and “extra\_cpu” is CPU for workers? So by setting the resources as shown above, I’d have four workers each with one CPU or one worker with four CPUs?
- Can I both specify `num_workers` in config dictionary and resources in `resources_per_trial`?

Thanks a lot!

---

<div class="post-metadata">

**Author:** ![xwjiang2010](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/xwjiang2010/32/1476_2.png) [@xwjiang2010](https://discuss.ray.io/u/xwjiang2010)\
**Post date:** [September 21, 2021, 4:57pm UTC](https://discuss.ray.io/t/resources-not-being-used/3495/4 "2021-09-21T16:57:20Z")

</div>

Hi Kai,  
Glad that it works out.  
Try specifying both `resources_per_trial` and `num_workers`.  
I believe `extra_cpu` is the overall amount of CPUs divide up among the `num_workers` that you specify.

---

<div class="post-metadata">

**Author:** ![xwjiang2010](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/xwjiang2010/32/1476_2.png) [@xwjiang2010](https://discuss.ray.io/u/xwjiang2010)\
**Post date:** [September 21, 2021, 4:58pm UTC](https://discuss.ray.io/t/resources-not-being-used/3495/5 "2021-09-21T16:58:33Z")

</div>

One more comment, if you are using the training function supplied by RLlib itself, you wouldn’t need to specify `resources_per_trial`, as RLlib as some default resources spec for each algorithm that it provides. But in this case, since you are using your own, so you have to specify that.