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Small fixes (#131)

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This commit is contained in:
pollfly
2021-12-14 15:12:30 +02:00
committed by GitHub
parent 6ae75beaa2
commit ec304690b6
25 changed files with 622 additions and 432 deletions
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28
docs/guides/distributed/distributed_pytorch_example.md
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@@ -26,8 +26,12 @@ The example uploads a dictionary as an artifact in the main Task by calling the
method on [`Task.current_task`](../../references/sdk/task.md#taskcurrent_task) (the main Task). The dictionary contains the [`dist.rank`](https://pytorch.org/docs/stable/distributed.html#torch.distributed.get_rank)
of the subprocess, making each unique.
Task.current_task().upload_artifact(
'temp {:02d}'.format(dist.get_rank()), artifact_object={'worker_rank': dist.get_rank()})
```python
Task.current_task().upload_artifact(
'temp {:02d}'.format(dist.get_rank()),
artifact_object={'worker_rank': dist.get_rank()}
)
```
All of these artifacts appear in the main Task under **ARTIFACTS** **>** **OTHER**.
@@ -40,8 +44,14 @@ method on `Task.current_task().get_logger`, which is the logger for the main Tas
with the same title (`loss`), but a different series name (containing the subprocess' `rank`), all loss scalar series are
logged together.
Task.current_task().get_logger().report_scalar(
'loss', 'worker {:02d}'.format(dist.get_rank()), value=loss.item(), iteration=i)
```python
Task.current_task().get_logger().report_scalar(
'loss',
'worker {:02d}'.format(dist.get_rank()),
value=loss.item(),
iteration=i
)
```
The single scalar plot for loss appears in **RESULTS** **>** **SCALARS**.
@@ -49,12 +59,14 @@ 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)
method is called on `Task.current_task`, they are logged in the main Task. A different hyperparameter key is used in each
**ClearML** automatically logs the argparse command line options. Since the [`Task.connect`](../../references/sdk/task#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.
param = {'worker_{}_stuff'.format(dist.get_rank()): 'some stuff ' + str(randint(0, 100))}
Task.current_task().connect(param)
```python
param = {'worker_{}_stuff'.format(dist.get_rank()): 'some stuff ' + str(randint(0, 100))}
Task.current_task().connect(param)
```
All the hyperparameters appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS**.

10
docs/guides/distributed/subprocess_example.md
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@@ -14,11 +14,15 @@ which always returns the main Task.
## Hyperparameters
**ClearML** automatically logs the command line options defined with `argparse`. A parameter dictionary is logged by
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.
additional_parameters = {'stuff_' + str(randint(0, 100)): 'some stuff ' + str(randint(0, 100))}
Task.current_task().connect(additional_parameters)
```python
additional_parameters = {
'stuff_' + str(randint(0, 100)): 'some stuff ' + str(randint(0, 100))
}
Task.current_task().connect(additional_parameters)
```
Command line options appear in **CONFIGURATIONS** **>** **HYPER PARAMETERS** **>** **Args**.