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Add artifact upload format options (#249)

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docs/fundamentals/artifacts.md
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@ -13,7 +13,8 @@ A few examples of artifacts are:
## Artifacts ## Artifacts
### Logging Artifacts ### Logging Artifacts
To log any type of artifact to a Task, use the `upload_artifact()` method. For example: To log any type of artifact to a Task, use the [`upload_artifact`](../references/sdk/task.md#upload_artifact) method.
For example:
* Upload a local file containing the preprocessing results of the data. * Upload a local file containing the preprocessing results of the data.
```python ```python
@ -24,12 +25,27 @@ task.upload_artifact(name='data', artifact_object='/path/to/preprocess_data.csv'
```python ```python
task.upload_artifact(name='folder', artifact_object='/path/to/folder/') task.upload_artifact(name='folder', artifact_object='/path/to/folder/')
``` ```
* Upload an instance of an object, Numpy / Pandas / PIL (converted to npz / csv.gz / jpg formats accordingly). If the * Serialize and upload a Python object. ClearML automatically chooses the file format based on the object’s type, or you
object type is unknown, it is pickled and uploaded. can explicitly specify the format as follows:
```python * dict - `.json` (default), `.yaml`
person_dict = {'name': 'Erik', 'age': 30} * pandas.DataFrame - `.csv.gz` (default), `.parquet`, `.feather`, `.pickle`
task.upload_artifact(name='person dictionary', artifact_object=person_dict) * numpy.ndarray - `.npz` (default), `.csv.gz`
``` * PIL.Image - Any PIL-supported extensions (default `.png`)
For example:
```python
person_dict = {'name': 'Erik', 'age': 30}
# upload as JSON artifact
task.upload_artifact(name='person dictionary json', artifact_object=person_dict)
# upload as YAML artifact
task.upload_artifact(
name='person dictionary yaml',
artifact_object=person_dict,
extension_name="yaml"
)
```
See more details in the artifacts [example](../guides/reporting/artifacts.md). See more details in the artifacts [example](../guides/reporting/artifacts.md).