From b171d597fc62b392236e1a013c92e506e540e624 Mon Sep 17 00:00:00 2001
From: pollfly <75068813+pollfly@users.noreply.github.com>
Date: Mon, 18 Sep 2023 10:49:13 +0300
Subject: [PATCH] Small edits (#671)
---
docs/apps/clearml_param_search.md | 4 ++--
docs/clearml_agent.md | 2 +-
docs/clearml_agent/clearml_agent_ref.md | 4 ++--
docs/clearml_sdk/clearml_sdk.md | 2 +-
docs/faq.md | 2 +-
.../notebooks/image/image_classification_CIFAR10.md | 7 +++++--
.../notebooks/table/download_and_preprocessing.md | 2 +-
.../pytorch/pytorch_distributed_example.md | 12 ++++++++----
docs/guides/reporting/image_reporting.md | 2 +-
9 files changed, 22 insertions(+), 15 deletions(-)
diff --git a/docs/apps/clearml_param_search.md b/docs/apps/clearml_param_search.md
index 38ed9ae0..777b67f6 100644
--- a/docs/apps/clearml_param_search.md
+++ b/docs/apps/clearml_param_search.md
@@ -29,8 +29,8 @@ of the optimization results in table and graph forms.
|`--task-id`|ID of a ClearML task whose hyperparameters will be optimized. Required unless `--script` is specified.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--script`|Script to run the parameter search on. Required unless `--task-id` is specified.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--queue`|Queue to enqueue the experiments on.|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
-|`--params-search`|Parameters space for optimization. See more information [here](#specifying-the-parameter-space). |<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
-|`--params-override`|Additional parameters of the base task to override for this parameter search. Use the following JSON format for each parameter: `{"name": "param_name", "value": <new_value>}`. Windows users, see JSON format note [here](#json_note).|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
+|`--params-search`|Parameters space for optimization. See more information in [Specifying the Parameter Space](#specifying-the-parameter-space). |<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
+|`--params-override`|Additional parameters of the base task to override for this parameter search. Use the following JSON format for each parameter: `{"name": "param_name", "value": <new_value>}`. Windows users, see [JSON format note](#json_note).|<img src="/docs/latest/icons/ico-optional-yes.svg" alt="Yes" className="icon size-md center-md" />|
|`--objective-metric-title`| Objective metric title to maximize/minimize (e.g. 'validation').|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--objective-metric-series`| Objective metric series to maximize/minimize (e.g. 'loss').|<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
|`--objective-metric-sign`| Optimization target, whether to maximize or minimize the value of the objective metric specified. Possible values: "min", "max", "min_global", "max_global". See more information [here](#optimization-objective). |<img src="/docs/latest/icons/ico-optional-no.svg" alt="No" className="icon size-md center-md" />|
diff --git a/docs/clearml_agent.md b/docs/clearml_agent.md
index ada04c44..186aaa4d 100644
--- a/docs/clearml_agent.md
+++ b/docs/clearml_agent.md
@@ -349,7 +349,7 @@ ClearML Agent supports executing tasks in multiple environments.
### PIP Mode
By default, ClearML Agent works in PIP Mode, in which it uses [pip](https://en.wikipedia.org/wiki/Pip_(package_manager))
as the package manager. When ClearML runs, it will create a virtual environment
-(or reuse an existing one, see [here](clearml_agent.md#virtual-environment-reuse)).
+(or [reuse an existing one](clearml_agent.md#virtual-environment-reuse)).
Task dependencies (Python packages) will be installed in the virtual environment.
### Conda Mode
diff --git a/docs/clearml_agent/clearml_agent_ref.md b/docs/clearml_agent/clearml_agent_ref.md
index 46960c71..7571be77 100644
--- a/docs/clearml_agent/clearml_agent_ref.md
+++ b/docs/clearml_agent/clearml_agent_ref.md
@@ -15,9 +15,9 @@ The following page provides a reference to `clearml-agent`'s CLI commands:
Use the `build` command to create worker environments without executing tasks.
You can build Docker containers according to the execution environments of specific tasks, which an agent can later
-use to execute other tasks. See tutorial [here](../guides/clearml_agent/exp_environment_containers.md).
+use to execute other tasks. See [tutorial](../guides/clearml_agent/exp_environment_containers.md).
-You can also create a Docker container that executes a specific task when launched. See tutorial [here](../guides/clearml_agent/executable_exp_containers.md).
+You can also create a Docker container that executes a specific task when launched. See [tutorial](../guides/clearml_agent/executable_exp_containers.md).
```bash
clearml-agent build [-h] --id TASK_ID [--target TARGET]
diff --git a/docs/clearml_sdk/clearml_sdk.md b/docs/clearml_sdk/clearml_sdk.md
index 3638833e..9050eee9 100644
--- a/docs/clearml_sdk/clearml_sdk.md
+++ b/docs/clearml_sdk/clearml_sdk.md
@@ -93,7 +93,7 @@ See an [overview](apiclient_sdk.md) for APIClient usage.
Use the ClearmlJob to create and manage jobs based on existing tasks. The class supports changing a job's parameters,
configurations, and other execution details.
-See reference page [here](../references/sdk/automation_job_clearmljob.md).
+See [reference page](../references/sdk/automation_job_clearmljob.md).
### AutoScaler
The `AutoScaler` class facilitates implementing resource budgeting. See class methods [here](https://github.com/allegroai/clearml/blob/master/clearml/automation/auto_scaler.py).
diff --git a/docs/faq.md b/docs/faq.md
index f4d5877b..0e81d341 100644
--- a/docs/faq.md
+++ b/docs/faq.md
@@ -1,4 +1,4 @@
---
+---
title: FAQ
---
diff --git a/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md b/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
index f6329aac..8d667a5b 100644
--- a/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
+++ b/docs/guides/frameworks/pytorch/notebooks/image/image_classification_CIFAR10.md
@@ -32,8 +32,11 @@ By doubling clicking a thumbnail, you can view a spectrogram plot in the image v
ClearML automatically logs TensorFlow Definitions. A parameter dictionary is logged by connecting it to the Task using
[`Task.connect()`](../../../../../references/sdk/task.md#connect).
- configuration_dict = {'number_of_epochs': 3, 'batch_size': 4, 'dropout': 0.25, 'base_lr': 0.001}
- configuration_dict = task.connect(configuration_dict) # enabling configuration override by clearml
+```python
+configuration_dict = {'number_of_epochs': 3, 'batch_size': 4, 'dropout': 0.25, 'base_lr': 0.001}
+# enabling configuration override by clearml
+configuration_dict = task.connect(configuration_dict)
+```
Parameter dictionaries appear in **CONFIGURATION** **>** **HYPERPARAMETERS** **>** **General**.
diff --git a/docs/guides/frameworks/pytorch/notebooks/table/download_and_preprocessing.md b/docs/guides/frameworks/pytorch/notebooks/table/download_and_preprocessing.md
index 272047a9..3ecd1b51 100644
--- a/docs/guides/frameworks/pytorch/notebooks/table/download_and_preprocessing.md
+++ b/docs/guides/frameworks/pytorch/notebooks/table/download_and_preprocessing.md
@@ -28,7 +28,7 @@ For example, the raw data is read into a Pandas DataFrame named `train_set`, and
```python
train_set = pd.read_csv(Path(path_to_ShelterAnimal) / 'train.csv')
Logger.current_logger().report_table(
- title='ClearMLet - raw',series='pandas DataFrame',iteration=0, table_plot=train_set.head()
+ title='ClearMLet - raw', series='pandas DataFrame', iteration=0, table_plot=train_set.head()
)
```
diff --git a/docs/guides/frameworks/pytorch/pytorch_distributed_example.md b/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
index 5233c209..459a4d3c 100644
--- a/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
+++ b/docs/guides/frameworks/pytorch/pytorch_distributed_example.md
@@ -26,8 +26,10 @@ The script does the following:
The example uploads a dictionary as an artifact in the main Task by calling [`Task.upload_artifact()`](../../../references/sdk/task.md#upload_artifact)
on `Task.current_task` (the main Task). The dictionary contains the `dist.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, **ARTIFACTS** **>** **OTHER**.
@@ -39,8 +41,10 @@ Report loss to the main Task by calling [`Logger.report_scalar()`](../../../refe
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.
- 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 **SCALARS**.
diff --git a/docs/guides/reporting/image_reporting.md b/docs/guides/reporting/image_reporting.md
index 46645457..f9a89b0e 100644
--- a/docs/guides/reporting/image_reporting.md
+++ b/docs/guides/reporting/image_reporting.md
@@ -1,5 +1,5 @@
---
-title: Images Reporting
+title: Image Reporting
---
The [image_reporting.py](https://github.com/allegroai/clearml/blob/master/examples/reporting/image_reporting.py) example