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52 lines
1.6 KiB
Markdown
52 lines
1.6 KiB
Markdown
---
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title: First Steps
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---
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## Install ClearML
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First, [sign up for free](https://app.community.clear.ml)
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Install the clearml python package:
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```bash
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pip install clearml
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```
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Connect your computer to the server by [creating credentials](https://app.community.clear.ml/profile), then run the below and follow the setup instructions:
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```bash
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clearml-init
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```
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## Auto-log experiment
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In ClearML, experiments are organized as [Tasks](../../fundamentals/task).
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ClearML will automatically log your experiment and code once you integrate the ClearML [SDK](../../clearml_sdk.md) with your code.
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At the begging of your code, import the clearml package
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```python
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From clearml import Task
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```
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:::note
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To ensure full automatic logging it is recommended to import the ClearML package at the top of your entry script.
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:::
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Then initialize the Task object in your `main()` function, or the beginning of the script.
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```python
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Task = Task.init(project_name=”great project”, task_name=”best experiment”)
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```
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Task name is not unique, it's possible to have multiple experiments with the same name.
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If the project does not already exist, a new one will be created automatically.
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**That’s it!** You are done integrating ClearML with your code :)
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Now, [command-line arguments](../../fundamentals/hyperparameters.md#argument-parser), [console output](../../fundamentals/logger#types-of-logged-results) as well as Tensorboard and Matplotlib will automatically be logged in the UI under the created Task.
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<br/>
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Sit back, relax, and watch your models converge :) or continue to see what else can be done with ClearML [here](ds_second_steps.md).
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