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# Get Started with CML on Bitbucket | ||
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Here, we'll walk through a tutorial to start using CML. For simplicity, we'll | ||
show the demo in Bitbucket Pipelines, but instructions are pretty similar for | ||
all the supported CI systems. | ||
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1. Fork our | ||
[example project repository](https://bitbucket.org/iterative-ai/example-cml). | ||
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![](/img/bitbucket_fork_cml_project.png) | ||
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The following steps can all be done in the Bitbucket browser interface. | ||
However, to follow along the commands, we recommend cloning your fork to your | ||
local workstation: | ||
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```bash | ||
git clone https://bitbucket.org/<your-username>/example-cml | ||
``` | ||
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2. To create a CML workflow, copy the following into a new file, | ||
`bitbucket-pipelines.yml`: | ||
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```yaml | ||
image: iterativeai/cml:0-dvc2-base1 | ||
pipelines: | ||
default: | ||
- step: | ||
name: Train model | ||
script: | ||
- pip install -r requirements.txt | ||
- python train.py | ||
- cat metrics.txt > report.md | ||
- cml-publish confusion_matrix.png --md >> report.md | ||
- cml-send-comment report.md | ||
``` | ||
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3. In your text editor of choice, edit line 16 of `train.py` to `depth = 12`. | ||
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4. Commit and push the changes: | ||
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```bash | ||
git checkout -b experiment | ||
git add . && git commit -m "modify forest depth" | ||
git push origin experiment | ||
``` | ||
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5. In Bitbucket, create a Pull Request to compare the `experiment` branch to | ||
`master`. | ||
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![](/img/bitbucket_make_pr.png) | ||
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Shortly, you should see a comment from your user appear in the Pull Request | ||
with your CML report. This is a result of the `cml send-comment` command in | ||
your workflow. | ||
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![](/img/bitbucket_cml_first_report.png) | ||
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This is the gist of the CML workflow: when you push changes to your Bitbucket | ||
repository, the workflow in your `bitbucket-pipelines.yml` file gets run and a | ||
report generated. | ||
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CML commands let you display relevant results from the workflow, like model | ||
performance metrics and vizualizations, in Bitbucket checks and comments. What | ||
kind of workflow you want to run, and want to put in your CML report, is up to | ||
you. | ||
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## Final Solution | ||
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An example of what your repository should look like now can be found at | ||
[`iterative-ai/cml_base_case`](https://bitbucket.org/iterative-ai/cml-base-case). |
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