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Small edits (#796)
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@@ -106,7 +106,7 @@ and [example](https://github.com/allegroai/clearml/blob/master/examples/schedule
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### TriggerScheduler
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The `TriggerScheduler` class facilitates triggering task execution in the case that specific events occur in the system
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(e.g. model publication, dataset creation, task failure). See [code](https://github.com/allegroai/clearml/blob/master/clearml/automation/trigger.py#L148)
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(such as model publication, dataset creation, task failure). See [code](https://github.com/allegroai/clearml/blob/master/clearml/automation/trigger.py#L148)
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and [usage example](https://github.com/allegroai/clearml/blob/master/examples/scheduler/trigger_example.py).
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## Examples
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@@ -181,7 +181,7 @@ The default operator for a query is `or`, unless `and` is placed at the beginnin
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### Retrieving Models
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Retrieve a local copy of a ClearML model through a `Model`/`InputModel` object's [`get_local_copy()`](../references/sdk/model_model.md#get_local_copy).
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The method returns a path to a cached local copy of the model. In the case that the model is already cached, you can set
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`force_download` to `True` in order to download a fresh version.
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`force_download` to `True` to download a fresh version.
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## Logging Metrics and Plots
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@@ -19,7 +19,7 @@ To ensure every run will provide the same results, ClearML controls the determin
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:::
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:::note
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ClearML object (e.g. task, project) names are required to be at least 3 characters long
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ClearML object (such as task, project) names are required to be at least 3 characters long
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:::
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```python
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@@ -100,8 +100,8 @@ By default, when ClearML is integrated into your script, it automatically captur
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and parameters from supported argument parsers. But, you may want to have more control over what your experiment logs.
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#### Frameworks
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To control a task's framework logging, use the `auto_connect_frameworks` parameter of the [`Task.init`](../references/sdk/task.md#taskinit)
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method. Turn off all automatic logging by setting the parameter to `False`. For finer grained control of logged frameworks,
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To control a task's framework logging, use the `auto_connect_frameworks` parameter of [`Task.init()`](../references/sdk/task.md#taskinit).
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Turn off all automatic logging by setting the parameter to `False`. For finer grained control of logged frameworks,
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input a dictionary, with framework-boolean pairs.
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For example:
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@@ -165,7 +165,7 @@ auto_connect_arg_parser={}
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### Task Reuse
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Every `Task.init` call will create a new task for the current execution.
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In order to mitigate the clutter that a multitude of debugging tasks might create, a task will be reused if:
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To mitigate the clutter that a multitude of debugging tasks might create, a task will be reused if:
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* The last time it was executed (on this machine) was under 24 hours ago (configurable, see
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[`sdk.development.task_reuse_time_window_in_hours`](../configs/clearml_conf.md#task_reuse) in
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the ClearML configuration reference)
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@@ -183,7 +183,7 @@ The task will continue reporting its outputs based on the iteration in which it
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train/loss scalar reported was for iteration 100, when continued, the next report will be as iteration 101.
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:::note Reproducibility
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Continued tasks may not be reproducible. In order to guarantee task reproducibility, you must ensure that all steps are
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Continued tasks may not be reproducible. To guarantee task reproducibility, you must ensure that all steps are
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done in the same order (e.g. maintaining learning rate profile, ensuring data is fed in the same order).
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:::
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@@ -786,7 +786,7 @@ task = Task.init(
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Specify the model storage URI location using the relevant format:
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* A shared folder: `/mnt/share/folder`
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* S3: `s3://bucket/folder`
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* Non-AWS S3-like services (e.g. MinIO): `s3://host_addr:port/bucket`
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* Non-AWS S3-like services (such as MinIO): `s3://host_addr:port/bucket`
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* Google Cloud Storage: `gs://bucket-name/folder`
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* Azure Storage: `azure://<account name>.blob.core.windows.net/path/to/file`
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:::
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