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Fix links (#165)

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pollfly
2022-01-19 14:26:14 +02:00
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parent b48dfe1d50
commit 70595e4f84
22 changed files with 48 additions and 46 deletions
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6
docs/guides/distributed/distributed_pytorch_example.md
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@@ -14,7 +14,7 @@ dataset), and reports (uploads) the following to the main Task:
* Scalars - Loss reported as a scalar during training in each Task in a subprocess.
* Hyperparameters - Hyperparameters created in each Task are added to the hyperparameters in the main Task.
Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task#taskcurrent_task), which always returns
Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task.md#taskcurrent_task), which always returns
the main Task.
When the script runs, it creates an experiment named `test torch distributed`, which is associated with the `examples` project.
@@ -38,7 +38,7 @@ All of these artifacts appear in the main Task under **ARTIFACTS** **>** **OTHER
## Scalars
Loss is reported to the main Task by calling the [Logger.report_scalar](../../references/sdk/logger#report_scalar)
Loss is reported to the main Task by calling the [Logger.report_scalar](../../references/sdk/logger.md#report_scalar)
method on `Task.current_task().get_logger`, which is the logger for the main Task. Since `Logger.report_scalar` is called
with the same title (`loss`), but a different series name (containing the subprocess' `rank`), all loss scalar series are
logged together.
@@ -58,7 +58,7 @@ The single scalar plot for loss appears in **RESULTS** **>** **SCALARS**.
## Hyperparameters
**ClearML** automatically logs the argparse command line options. Since the [`Task.connect`](../../references/sdk/task#connect)
**ClearML** automatically logs the argparse command line options. Since the [`Task.connect`](../../references/sdk/task.md#connect)
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
subprocess, so they do not overwrite each other in the main Task.

4
docs/guides/distributed/subprocess_example.md
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@@ -5,7 +5,7 @@ title: Subprocess
The [subprocess_example.py](https://github.com/allegroai/clearml/blob/master/examples/distributed/subprocess_example.py)
script demonstrates multiple subprocesses interacting and reporting to a main Task. The following happens in the script:
* This script initializes a main Task and spawns subprocesses, each for an instances of that Task.
* Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task#taskcurrent_task),
* Each Task in a subprocess references the main Task by calling [Task.current_task](../../references/sdk/task.md#taskcurrent_task),
which always returns the main Task.
* The Task in each subprocess reports the following to the main Task:
* Hyperparameters - Additional, different hyperparameters.
@@ -15,7 +15,7 @@ which always returns the main Task.
## Hyperparameters
ClearML automatically logs the command line options defined with `argparse`. A parameter dictionary is logged by
connecting it to the Task using a call to the [Task.connect](../../references/sdk/task#connect) method.
connecting it to the Task using a call to the [Task.connect](../../references/sdk/task.md#connect) method.
```python
additional_parameters = {