Badges 118 × Eureka!
SuccessfulKoala55 Ok. Here is my code. Thanks.
` def plot_feature_scatter(df1, df2, features):
i = 0
fig, ax = plt.subplots(5, 4, figsize=(20, 20)) for feature in features: i += 1 plt.subplot(5, 4, i) plt.scatter(df1[feature], df2[feature], marker="+", color='#2B3A67', alpha=0.2) plt.xlabel(feature, fontsize=9) plt.show()
CostlyOstrich36 It's because the ports are used by other services.
I'm not sure how I can do it if I don't use the ClearML agent. In https://clear.ml/docs/latest/docs/references/sdk/scheduler/#class-automationtaskscheduler , I can't find how to stop it programmatically. Could I stop it by the UI if I don't use the ClearML agent. I see. In my understanding, the log would show all the message, but not so clear to me. Especially, if I have tens or hundreds of scheduled tasks. It's not convenient for me to check one by one.
agent.enable_task_env = false
agent.hide_docker_command_env_vars.enabled = true
agent.docker_internal_mounts.sdk_cache = /clearml_agent_cache
agent.docker_internal_mounts.apt_cache = /var/cache/apt/archives
agent.docker_internal_mounts.ssh_folder = /root/.ssh
agent.docker_internal_mounts.pip_cache = /root/.cache/pip
agent.docker_internal_mounts.poetry_cache = /root/.cache/pypoetry
agent.docker_internal_mounts.vcs_cache = /root/.clearml/vcs-cache
agent.docker_internal_mounts.venv_build = /root...
I installed ClearML-Agent to run it. However, I encounter another issue.
It shows the error message of
clearml_agent: ERROR: [Errno 2] No such file or directory: '/root/.clearml/venvs-builds/3.8/task_repository/PyTorch.git/ctbc/image_classification_CIFAR10.py'
I've executed https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.ipynb before executing https://github.com/allegroai/clearml/blo...
SuccessfulKoala55 I don't understand your meaning.
Yeah, there is no further explanation about the status of
closed so I'm wondering when it can become
closed . As for my second question, my intention is that no need to update the original task or create a new task for another training. I expect that I can do another training after
task.close() and I won't encounter any issues, but I'm wrong.
TimelyMouse69 Hello, could you help check my above questions? Thanks.
CostlyOstrich36 Ok. Thanks.
SweetBadger76 Thanks! Waiting for your example.
AbruptCow41 Hi, thanks.
I follow this tutorial - https://clear.ml/docs/latest/docs/guides/frameworks/pytorch/notebooks/image/hyperparameter_search/ , but I didn't see it told me to add any repository.
Also, what I execute as a base experiment is https://github.com/allegroai/clearml/blob/master/examples/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.ipynb , not image_classification_CIFAR10.py. Does the https://clear.ml/docs/latest/docs/references/sdk/hpo_optimization_hyp...
About question #2,
I don't want to reuse a task. I want to temporarily pause or permanently stop this ClearML task so the ClearML task won't record my following experiment (training job).
Hi SuccessfulKoala55 Do u mean give you the code to plot the image (but not including the data) or the image or the experiment I encountered this performance issue?
Is there any update?
SuccessfulKoala55 The image is something like this.
My questions are two
Is it possible to let ClearML not record this plot manually? Doesn't ClearML have performance issue for this kind of plot?
SuccessfulKoala55 No, I don't know how to turn off and turn on the auto-logging. Could you tell me? Thanks.
TimelyMouse69 Hello, could you help check the above messages ? Thanks.
For example, I want to compare accuracy (the metrics I'm interested) among different experiments. This metrics isn't automatically recorded by ClearML so I want to manually record it.
I've found a workaround to achieve it (as mentioned in the original message), but I'm still wondering if there is any suggestion except using
I see! Thanks AnxiousSeal95 and SweetBadger76 !
I have another related questions. Are the items in
+ metric I can select only the items in
Results -> Scalars .
Ok. It's strange. After executing
mark_completed() , the kernel of Jupyter is dead. You can see the following image. The three cells (3~5) run at once, then the kernel is dead. I use
task.close() but the status is still
completed , not
CostlyOstrich36 Thanks! I'll try it.
TimelyMouse69 About the
closed status, I'll wait for your response. Thanks!!