How to override /root/.cache/pip path?

Can you help me?

@<1523701435869433856:profile|SmugDolphin23> hi! it works! thanks!

@<1523701070390366208:profile|CostlyOstrich36> Above, I provided the code for this pipeline, I specify cache_executed_step=True for each pipeline step , but it doesn't work.

I create a pipeline via PipelineController with adding a step as a function

pipe = PipelineController(
        name=cfg.clearml.pipeline_name,
        project=cfg.clearml.project_name,
        target_project=True,
        version=cfg.clearml.version,
        add_pipeline_tags=True,
        docker=cfg.clearml.dockerfile,
        docker_args=DefaultMLPLATparam().docker_arg,
        packages=packages,
        retry_on_failure=3
    )

for parameter in cfg.clearml.params:
        pipe.add_...

Hi @<1523701205467926528:profile|AgitatedDove14>
I define a pipeline through functions. I have a lot of parameters, about 40. It is inconvenient to overwrite them all from the window that is on the screen.

@<1523701087100473344:profile|SuccessfulKoala55>

The /root/clearml.conf file no longer contains anything.

Hi @<1523701087100473344:profile|SuccessfulKoala55> No, I am using self-hosted ClearML enterprise server

thank you!

No, I get start pipelines through cloning as tasks, it's less visual, but this way I can change all my hyperparameters

@<1523701205467926528:profile|AgitatedDove14> thanks for your reply! Do I also need to change the path for docker_pip_cache ?

None

in the clearml section in values.yaml:

clearml:
  ...
  clearmlConfig: |-
   agent.docker_pip_cache="/mnt/pip_cache"

Hi @<1523701435869433856:profile|SmugDolphin23> Thank you for your reply!
I use 2 machines.
I set these parameters, but unfortunately, the training has not started.

torch.distributed.DistStoreError: Timed out after 1801 seconds waiting for clients. 2/4 clients joined.

However, nothing is saved along this path

@<1523701070390366208:profile|CostlyOstrich36> If I run the pipeline with the same input parameters, all the steps will also be re-run, nothing will be taken from the cache

@<1523701070390366208:profile|CostlyOstrich36> Any ideas?

@<1523701070390366208:profile|CostlyOstrich36> can you help me?

I store my data in s3 and clearml tracks this data. I want to migrate this data from one ClearML instance to another, that is, transfer it to another s3 and have a new ClearML instance track it

I had a similar behavior: the parameters for starting the pipeline are not selected in a detailes view, only in the table view

@<1523701435869433856:profile|SmugDolphin23> It is possible to request up to 5 workers in the toy example with Feed Forward and MNIST, BUT it is not possible to request more than 2 workers on a real large model

@<1523701435869433856:profile|SmugDolphin23> This error occurs when a secondary task is created with launch_multi_node. And this error disappears when I add the reuse_last_task_id=False flag when initializing the task. But now I have a new problem. I can't request more than 2 nodes. The training logs freezes after several iterations of first epoch with three workers. And if i request four workers i get this error:

DEBUG Epoch 0:   8%|▊         | 200/2484 [04:43<53:55,  0.71it/s, v_num=...

@<1523701435869433856:profile|SmugDolphin23> Everything worked after setting the variables: --env NCCL_IB_DISABLE=1 --env NCCL_SOCKET_IFNAME=ens192 --env NCCL_P2P_DISABLE=1. But previously, these variables were not required for a successful launch. When I run ddp training with two nodes , everything works for me now. But as soon as I increase their number ( nodes > 2 ), I get the following error.

Traceback (most recent call last):
  File "/root/.clearml/venvs-builds/3.11/code/light...

@<1523701435869433856:profile|SmugDolphin23> if task.aunch_multi_node(4) , then all 4 tasks are failed

@<1523701435869433856:profile|SmugDolphin23> Each task shows that process allocates only 1 gpu out of 2 (all task have the same scalar as below)

Hi @<1523701087100473344:profile|SuccessfulKoala55> where can I get examples of REST API requests for creating reports?

@<1523701070390366208:profile|CostlyOstrich36> i have 2 clearm-serving instances with endpoints

@<1523701070390366208:profile|CostlyOstrich36> yes

Hi @<1523701205467926528:profile|AgitatedDove14>
I started an experiment with gpus=2 and node=2 and I have the following logs

do I understand correctly that it is impossible to disable the installation of system packages without CLEARML_AGENT_SKIP_PIP_VENV_INSTALL and CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL?