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Fix links (#165)
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@@ -56,11 +56,11 @@ This adds the downloaded files to the current dataset.
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dataset.upload()
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```
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This uploads the dataset to the ClearML Server by default. The dataset's destination can be changed by specifying the
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target storage with the `output_url` parameter of the [`upload`](../../references/sdk/dataset#upload) method.
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target storage with the `output_url` parameter of the [`upload`](../../references/sdk/dataset.md#upload) method.
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### Finalizing the Dataset
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Run the [`finalize`](../../references/sdk/dataset#finzalize) command to close the dataset and set that dataset's tasks
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Run the [`finalize`](../../references/sdk/dataset.md#finalize) command to close the dataset and set that dataset's tasks
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status to *completed*. The dataset can only be finalized if it doesn't have any pending uploads.
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```python
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@@ -14,7 +14,7 @@ dataset), and reports (uploads) the following to the main Task:
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* Scalars - Loss reported as a scalar during training in each Task in a subprocess.
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* Hyperparameters - Hyperparameters created in each Task are added to the hyperparameters in the main Task.
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Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task#taskcurrent_task), which always returns
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Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task.md#taskcurrent_task), which always returns
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the main Task.
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When the script runs, it creates an experiment named `test torch distributed`, which is associated with the `examples` project.
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@@ -38,7 +38,7 @@ All of these artifacts appear in the main Task under **ARTIFACTS** **>** **OTHER
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## Scalars
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Loss is reported to the main Task by calling the [Logger.report_scalar](../../references/sdk/logger#report_scalar)
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Loss is reported to the main Task by calling the [Logger.report_scalar](../../references/sdk/logger.md#report_scalar)
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method on `Task.current_task().get_logger`, which is the logger for the main Task. Since `Logger.report_scalar` is called
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with the same title (`loss`), but a different series name (containing the subprocess' `rank`), all loss scalar series are
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logged together.
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@@ -58,7 +58,7 @@ The single scalar plot for loss appears in **RESULTS** **>** **SCALARS**.
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## Hyperparameters
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**ClearML** automatically logs the argparse command line options. Since the [`Task.connect`](../../references/sdk/task#connect)
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**ClearML** automatically logs the argparse command line options. Since the [`Task.connect`](../../references/sdk/task.md#connect)
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method is called on [`Task.current_task`](../../references/sdk/task.md#taskcurrent_task), they are logged in the main Task. A different hyperparameter key is used in each
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subprocess, so they do not overwrite each other in the main Task.
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@@ -5,7 +5,7 @@ title: Subprocess
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The [subprocess_example.py](https://github.com/allegroai/clearml/blob/master/examples/distributed/subprocess_example.py)
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script demonstrates multiple subprocesses interacting and reporting to a main Task. The following happens in the script:
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* This script initializes a main Task and spawns subprocesses, each for an instances of that Task.
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* Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task#taskcurrent_task),
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* Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task.md#taskcurrent_task),
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which always returns the main Task.
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* The Task in each subprocess reports the following to the main Task:
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* Hyperparameters - Additional, different hyperparameters.
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@@ -15,7 +15,7 @@ which always returns the main Task.
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## Hyperparameters
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ClearML automatically logs the command line options defined with `argparse`. A parameter dictionary is logged by
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connecting it to the Task using a call to the [Task.connect](../../references/sdk/task#connect) method.
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connecting it to the Task using a call to the [Task.connect](../../references/sdk/task.md#connect) method.
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```python
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additional_parameters = {
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@@ -6,7 +6,7 @@ The [html_reporting.py](https://github.com/allegroai/clearml/blob/master/example
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demonstrates reporting local HTML files and HTML by URL, using the [Logger.report_media](../../references/sdk/logger.md#report_media)
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method.
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**ClearML** reports these HTML debug samples in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>**
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ClearML reports these HTML debug samples in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>**
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**DEBUG SAMPLES** sub-tab.
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When the script runs, it creates an experiment named `html samples reporting`, which is associated with the `examples` project.
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@@ -18,7 +18,7 @@ When the script runs, it creates an experiment named `html samples reporting`, w
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Report HTML by URL, using the [Logger.report_media](../../references/sdk/logger.md#report_media) method's `url` parameter.
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See the example script's [report_html_url](https://github.com/allegroai/clearml/blob/master/examples/reporting/html_reporting.py#L16)
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function, which reports the **ClearML** documentation's home page.
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function, which reports the ClearML documentation's home page.
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```python
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Logger.current_logger().report_media("html", "url_html", iteration=iteration, url="https://clear.ml/docs")
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@@ -10,7 +10,7 @@ method to upload from:
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* URL of media already uploaded to some storage
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**ClearML** uploads media to the bucket specified in the **ClearML** configuration file or **ClearML** can be configured for image storage, see [Logger.set_default_upload_destination](../../references/sdk/logger.md#set_default_upload_destination)
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(storage for [artifacts](../../fundamentals/artifacts#setting-upload-destination) is different). Set credentials for storage in the **ClearML**
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(storage for [artifacts](../../fundamentals/artifacts.md#setting-upload-destination) is different). Set credentials for storage in the **ClearML**
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[configuration file](../../configs/clearml_conf.md).
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**ClearML** reports media in the **ClearML Web UI** **>** experiment details **>** **RESULTS** tab **>** **DEBUG SAMPLES**
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