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pollfly
2024-03-12 11:24:42 +02:00
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28 changed files with 58 additions and 55 deletions
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docs/clearml_data/clearml_data_sdk.md
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@@ -56,7 +56,7 @@ For datasets created with earlier versions of `clearml`, or if using an earlier
:::
:::info Dataset Version
Input the dataset's version using the [semantic versioning](https://semver.org) scheme (e.g. `1.0.1`, `2.0`). If a version
Input the dataset's version using the [semantic versioning](https://semver.org) scheme (for example: `1.0.1`, `2.0`). If a version
is not input, the method tries finding the latest dataset version with the specified `dataset_name` and `dataset_project`
and auto-increments the version number.
:::
@@ -65,7 +65,7 @@ Use the `output_uri` parameter to specify a network storage target to upload the
(such as previews) to. For example:
* A shared folder: `/mnt/share/folder`
* S3: `s3://bucket/folder`
* Non-AWS S3-like services (e.g. MinIO): `s3://host_addr:port/bucket`
* Non-AWS S3-like services (such as MinIO): `s3://host_addr:port/bucket`
* Google Cloud Storage: `gs://bucket-name/folder`
* Azure Storage: `azure://<account name>.blob.core.windows.net/path/to/file`
@@ -209,12 +209,12 @@ dataset.add_external_files(
```
### remove_files()
To remove files from a current dataset, use the [`Dataset.remove_files`](../references/sdk/dataset.md#remove_files) method.
To remove files from a current dataset, use [`Dataset.remove_files()`](../references/sdk/dataset.md#remove_files).
Input the path to the folder or file to be removed in the `dataset_path` parameter. The path is relative to the dataset.
To remove links, specify their URL (e.g. `s3://bucket/file`).
To remove links, specify their URL (for example, `s3://bucket/file`).
You can also input a wildcard into `dataset_path` in order to remove a set of files matching the wildcard.
Set the `recursive` parameter to `True` in order to match all wildcard files recursively
You can also input a wildcard into `dataset_path` to remove a set of files matching the wildcard.
Set the `recursive` parameter to `True` to match all wildcard files recursively
For example:
@@ -257,7 +257,7 @@ To upload the dataset files to network storage, use the [`Dataset.upload`](../re
Use the `output_url` parameter to specify storage target, such as S3 / GS / Azure. For example:
* A shared folder: `/mnt/share/folder`
* S3: `s3://bucket/folder`
* Non-AWS S3-like services (e.g. MinIO): `s3://host_addr:port/bucket`
* Non-AWS S3-like services (such as MinIO): `s3://host_addr:port/bucket`
* Google Cloud Storage: `gs://bucket-name/folder`
* Azure Storage: `azure://<account name>.blob.core.windows.net/path/to/file`
@@ -369,7 +369,7 @@ ClearML Task: created new task id=offline-372657bb04444c25a31bc6af86552cc9
ClearML Task: Offline session stored in /home/user/.clearml/cache/offline/b786845decb14eecadf2be24affc7418.zip
```
Note that in offline mode, any methods that require communicating with the server have no effect (e.g. `squash()`,
Note that in offline mode, any methods that require communicating with the server have no effect (such as `squash()`,
`finalize()`, `get_local_copy()`, `get()`, `move_to_project()`, etc.).
Upload the offline dataset to the ClearML Server using [`Dataset.import_offline_session()`](../references/sdk/dataset.md#datasetimport_offline_session).