Small edits (#594)

docs/clearml_data/clearml_data_sdk.md

@@ -9,7 +9,7 @@ See [Hyper-Datasets](../hyperdatasets/overview.md) for ClearML's advanced querya
 
 Datasets can be created, modified, and managed with ClearML Data's python interface. You can upload your dataset to any 
 storage service of your choice (S3 / GS / Azure / Network Storage) by setting the dataset’s upload destination (see 
-[`output_url`](#uploading-files) parameter of `Dataset.upload` method). Once you have uploaded your dataset, you can access 
+[`output_url`](#uploading-files) parameter of `Dataset.upload()`). Once you have uploaded your dataset, you can access 
 it from any machine.  
 
 The following page provides an overview for using the most basic methods of the `Dataset` class. See the [Dataset reference page](../references/sdk/dataset.md) 

docs/clearml_sdk/task_sdk.md

@@ -520,8 +520,8 @@ the `offline_mode` argument to `True`
 * Before running a task, set `CLEARML_OFFLINE_MODE=1`
 
 :::caution 
-Offline mode only works with tasks created using `Task.init` and not with those created 
+Offline mode only works with tasks created using [`Task.init()`](../references/sdk/task.md#taskinit) and not with those created 
-using the `Task.create` method. 
+using [`Task.create()`](../references/sdk/task.md#taskcreate). 
 :::
 
 All the information captured by the Task is saved locally. Once the task script finishes execution, it's zipped. 

docs/configs/clearml_conf.md

@@ -933,7 +933,7 @@ and limitations on bucket naming.
 **`sdk.development.default_output_uri`** (*string*) <a class="tr_top_negative" id="config_default_output_uri"></a> 
     
 * The default output destination for model checkpoints (snapshots) and artifacts. If the `output_uri` parameter is not provided 
-  when calling the `Task.init` method, then use the destination in `default_output_uri`.
+  when calling [`Task.init()`](../references/sdk/task.md#taskinit), then use the destination in `default_output_uri`.
     
 
 ---

docs/deploying_clearml/clearml_server_config.md

@@ -55,7 +55,7 @@ For example, a domain is called `mydomain.com`, and a subdomain named `clearml.m
 * `api.clearml.mydomain.com` (API server)
 * `files.clearml.mydomain.com` (file server)
 
-Accessing the **ClearML Web UI** with `app.clearml.mydomain.com` will automatically send API requests to `api.clearml.mydomain.com`.
+Accessing the [ClearML Web UI](../webapp/webapp_overview.md) with `app.clearml.mydomain.com` will automatically send API requests to `api.clearml.mydomain.com`.
 
 ## ClearML Server Feature Configurations
 

docs/faq.md

@@ -509,8 +509,8 @@ the `offline_mode` argument to `True`
 * Before running a task, set `CLEARML_OFFLINE_MODE=1`
 
 :::caution 
-Offline mode only works with tasks created using `Task.init` and not with those created 
+Offline mode only works with tasks created using [`Task.init()`](references/sdk/task.md#taskinit) and not with those created 
-using the `Task.create` method. 
+using [`Task.create()`](references/sdk/task.md#taskcreate). 
 :::
 
 The task's console output displays the task ID and a path to the folder with the session's captured information:

docs/getting_started/mlops/mlops_best_practices.md

@@ -18,7 +18,7 @@ If you are afraid of clutter, use the archive option, and set up your own [clean
 
 ## Clone Tasks
 Define a ClearML Task with one of the following options:
-- Run the actual code with `Task.init` call. This will create and auto-populate the Task in CleaML (including Git Repo / Python Packages / Command line etc.).
+- Run the actual code with the `Task.init()` call. This will create and auto-populate the Task in CleaML (including Git Repo / Python Packages / Command line etc.).
 - Register local / remote code repository with `clearml-task`. See [details](../../apps/clearml_task.md).
 
 Once you have a Task in ClearML, you can clone and edit its definitions in the UI, then launch it on one of your nodes with [ClearML Agent](../../clearml_agent.md).

docs/guides/set_offline.md

@@ -23,8 +23,8 @@ the `offline_mode` argument to `True`
 * Before running a task, set `CLEARML_OFFLINE_MODE=1`
 
 :::caution 
-Offline mode only works with tasks created using `Task.init` and not with those created 
+Offline mode only works with tasks created using [`Task.init()`](../references/sdk/task.md#taskinit) and not with those created 
-using the `Task.create` method. 
+using [`Task.create()`](../references/sdk/task.md#taskcreate). 
 :::
 
 

docs/guides/ui/building_leader_board.md

@@ -24,7 +24,7 @@ For this tutorial, use one of the following as a project:
 
 The leaderboard will track experiments in one or all projects. 
 
-Begin by opening the **ClearML Web UI** and selecting a project, by doing one of the following:
+Begin by opening the [ClearML Web UI](../../webapp/webapp_overview.md) and selecting a project, by doing one of the following:
 * On the Dashboard, click a project card or **VIEW ALL**.
 * On the Projects page, click a project card or the **All projects** card.
 

docs/hyperdatasets/dataviews.md

@@ -310,7 +310,7 @@ list_of_frames = myDataView.to_list()
 
 ### Controlling Query Iteration
 
-Use [`DataView.set_iteration_parameters`](../references/hyperdataset/dataview.md#set_iteration_parameters) to manage the 
+Use [`DataView.set_iteration_parameters()`](../references/hyperdataset/dataview.md#set_iteration_parameters) to manage the 
 order, number, timing, and reproducibility of frames for training.
 
 

old-sidebars.js

@@ -1,95 +0,0 @@
-/**
- * Copyright (c) Facebook, Inc. and its affiliates.
- *
- * This source code is licensed under the MIT license found in the
- * LICENSE file in the root directory of this source tree.
- *
- * @format
- */
-
-module.exports = {
-  someSidebar: {
-    'Getting Started': ['main','starting', 'architecture'],
-    'Experiment Management': [
-        {'Getting Started':['expman/main', 'expman/best practices']},
-        {'Task':['expman/task/task','expman/task/task_details']},
-        'expman/hyperparameters',
-        'expman/artifacts',
-        'expman/logger',
-        'expman/integrations/libraries',
-        'expman/clearml_task',
-        {'Functionality':['expman/ui/leaderboard', 'expman/ui/task comparison']},
-        {'Remote Development':['expman/remote/remote_jupyter','expman/remote/remote pycharm']},
-        {'Advanced Topics':['expman/advanced/multiple tasks','expman/advanced/hpo']},
-    ],
-    'Automation': [
-        {
-            'Getting Started': [
-                'mlops/main',
-                'mlops/setup/getting_started',
-                'mlops/setup/agent',
-                'mlops/setup/services',
-                'mlops/best practices',
-
-            ],
-        },
-        {'ClearML Agent': [
-            'mlops/concepts/agents_and_queues','mlops/concepts/clearml_agent_usage','mlops/concepts/services']
-        },
-        'mlops/orchestration/pipeline/create pipeline',
-
-    ],
-    'Data Management': ['expman/data/data','expman/data/api'],
-    'WebApp': ['webapp/webapp_overview','webapp/webapp_home',
-              {'Projects Page':[
-                  {'Experiments':['webapp/webapp_exp_table','webapp/webapp_exp_track_visual','webapp/webapp_exp_reproducing','webapp/webapp_exp_tuning',
-                                  'webapp/webapp_exp_comparing','webapp/webapp_exp_sharing']},
-                  {'Models': ['webapp/webapp_model_table','webapp/webapp_model_viewing','webapp/webapp_model_modifying']},
-                  'webapp/webapp_archiving']},
-              'webapp/webapp_profile','webapp/webapp_workers_queues'],
-     //'References': ['references/clearml_ref','references/clearml_agent_ref'],
-     'DevOps': ['devops/main','expman/integrations/storage'],
-     'Comments': ['Notes'],
-
-
-  },
-    refSidebar: {
-        'References':['references/refmain','references/clearml_ref','references/clearml_agent_ref'
-        ],
-      },
-    guidesSidebar:{
-      'Guides': [
-                'guides/guidemain',
-                {'Frameworks':[
-                {'Autokeras':['guides/frameworks/autokeras/integration_autokeras','guides/frameworks/autokeras/autokeras_imdb_example']},
-                {'FastAI':['guides/frameworks/fastai/fastai_with_tensorboard']},
-                {'Keras': ['guides/frameworks/keras/allegro_clearml_keras_tb_example','guides/frameworks/keras/jupyter','guides/frameworks/keras/keras_tensorboard',
-                           'guides/frameworks/keras/manual_model_upload']},
-                {'Matplotlib': ['guides/frameworks/matplotlib/allegro_clearml_matplotlib_example','guides/frameworks/matplotlib/matplotlib_example']},
-                {'Pytorch':['guides/frameworks/pytorch/manual_model_upload','guides/frameworks/pytorch/pytorch_distributed_example','guides/frameworks/pytorch/pytorch_matplotlib',
-                            'guides/frameworks/pytorch/pytorch_mnist','guides/frameworks/pytorch/pytorch_tensorboard','guides/frameworks/pytorch/pytorch_tensorboardx',
-                            'guides/frameworks/pytorch/tensorboard_toy_pytorch']},
-                {'Scikit-Learn':['guides/frameworks/scikit-learn/sklearn_joblib_example','guides/frameworks/scikit-learn/sklearn_matplotlib_example']},
-                {'TensorboardX':['guides/frameworks/tensorboardx/tensorboardx']},
-                {'Tensorflow':['guides/frameworks/tensorflow/manual_model_upload','guides/frameworks/tensorflow/tensorboard_pr_curve','guides/frameworks/tensorflow/tensorboard_toy',
-                               'guides/frameworks/tensorflow/tensorflow_mnist','guides/frameworks/tensorflow/integration_keras_tuner']},
-                {'XGboost':['guides/frameworks/xgboost/xgboost_sample']},
-                {'Pytorch Ignite':['guides/frameworks/pytorch_ignite/integration_pytorch_ignite']}
-                ]},
-                {'Automation':['guides/automation/manual_random_param_search_example','guides/automation/task_piping']},
-                {'Data Management':['guides/data management/data_man_simple','guides/data management/data_man_folder_sync','guides/data management/data_man_cifar_classification']},
-                {'Clearml-task':['guides/clearml-task/clearml_task_tutorial']},
-                {'Distributed':['guides/distributed/distributed_pytorch_example','guides/distributed/subprocess_example']},
-                {'Optimization':['guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt']},
-                {'Pipelines':['guides/pipeline/pipeline_controller']},
-                {'Reporting':['guides/reporting/3d_plots_reporting','guides/reporting/artifacts','guides/reporting/clearml_logging_example','guides/reporting/html_reporting',
-                              'guides/reporting/hyper_parameters','guides/reporting/image_reporting','guides/reporting/manual_matplotlib_reporting','guides/reporting/media_reporting',
-                              'guides/reporting/model_config','guides/reporting/pandas_reporting','guides/reporting/plotly_reporting',
-                              'guides/reporting/scalar_reporting','guides/reporting/scatter_hist_confusion_mat_reporting','guides/reporting/text_reporting']},
-                {'Services':['guides/services/aws_autoscaler','guides/services/cleanup_service','guides/services/execute_jupyter_notebook_server','guides/services/slack_alerts']},
-                {'IDEs':['guides/ide/integration_jupyter','guides/ide/integration_pycharm', 'guides/ide/remote_jupyter_tutorial']},
-                {'ClearML':['guides/clearml/building_leader_board', 'guides/clearml/explicit_reporting', 'guides/clearml/tuning_exp']},
-                {'Storage':['guides/examples_storagehelper']}
-               ]
-    }
-};