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@ -9,7 +9,7 @@ See [Hyper-Datasets](../hyperdatasets/overview.md) for ClearML's advanced querya
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Datasets can be created, modified, and managed with ClearML Data's python interface. You can upload your dataset to any
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storage service of your choice (S3 / GS / Azure / Network Storage) by setting the dataset’s upload destination (see
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[`output_url`](#uploading-files) parameter of `Dataset.upload` method). Once you have uploaded your dataset, you can access
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[`output_url`](#uploading-files) parameter of `Dataset.upload()`). Once you have uploaded your dataset, you can access
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it from any machine.
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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)
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@ -520,8 +520,8 @@ the `offline_mode` argument to `True`
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* Before running a task, set `CLEARML_OFFLINE_MODE=1`
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:::caution
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Offline mode only works with tasks created using `Task.init` and not with those created
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using the `Task.create` method.
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Offline mode only works with tasks created using [`Task.init()`](../references/sdk/task.md#taskinit) and not with those created
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using [`Task.create()`](../references/sdk/task.md#taskcreate).
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:::
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All the information captured by the Task is saved locally. Once the task script finishes execution, it's zipped.
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@ -933,7 +933,7 @@ and limitations on bucket naming.
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**`sdk.development.default_output_uri`** (*string*) <a class="tr_top_negative" id="config_default_output_uri"></a>
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* The default output destination for model checkpoints (snapshots) and artifacts. If the `output_uri` parameter is not provided
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when calling the `Task.init` method, then use the destination in `default_output_uri`.
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when calling [`Task.init()`](../references/sdk/task.md#taskinit), then use the destination in `default_output_uri`.
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---
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@ -55,7 +55,7 @@ For example, a domain is called `mydomain.com`, and a subdomain named `clearml.m
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* `api.clearml.mydomain.com` (API server)
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* `files.clearml.mydomain.com` (file server)
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Accessing the **ClearML Web UI** with `app.clearml.mydomain.com` will automatically send API requests to `api.clearml.mydomain.com`.
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Accessing the [ClearML Web UI](../webapp/webapp_overview.md) with `app.clearml.mydomain.com` will automatically send API requests to `api.clearml.mydomain.com`.
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## ClearML Server Feature Configurations
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@ -509,8 +509,8 @@ the `offline_mode` argument to `True`
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* Before running a task, set `CLEARML_OFFLINE_MODE=1`
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:::caution
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Offline mode only works with tasks created using `Task.init` and not with those created
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using the `Task.create` method.
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Offline mode only works with tasks created using [`Task.init()`](references/sdk/task.md#taskinit) and not with those created
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using [`Task.create()`](references/sdk/task.md#taskcreate).
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:::
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The task's console output displays the task ID and a path to the folder with the session's captured information:
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@ -18,7 +18,7 @@ If you are afraid of clutter, use the archive option, and set up your own [clean
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## Clone Tasks
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Define a ClearML Task with one of the following options:
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- 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.).
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- 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.).
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- Register local / remote code repository with `clearml-task`. See [details](../../apps/clearml_task.md).
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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).
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@ -23,8 +23,8 @@ the `offline_mode` argument to `True`
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* Before running a task, set `CLEARML_OFFLINE_MODE=1`
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:::caution
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Offline mode only works with tasks created using `Task.init` and not with those created
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using the `Task.create` method.
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Offline mode only works with tasks created using [`Task.init()`](../references/sdk/task.md#taskinit) and not with those created
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using [`Task.create()`](../references/sdk/task.md#taskcreate).
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:::
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@ -24,7 +24,7 @@ For this tutorial, use one of the following as a project:
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The leaderboard will track experiments in one or all projects.
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Begin by opening the **ClearML Web UI** and selecting a project, by doing one of the following:
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Begin by opening the [ClearML Web UI](../../webapp/webapp_overview.md) and selecting a project, by doing one of the following:
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* On the Dashboard, click a project card or **VIEW ALL**.
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* On the Projects page, click a project card or the **All projects** card.
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@ -310,7 +310,7 @@ list_of_frames = myDataView.to_list()
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### Controlling Query Iteration
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Use [`DataView.set_iteration_parameters`](../references/hyperdataset/dataview.md#set_iteration_parameters) to manage the
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Use [`DataView.set_iteration_parameters()`](../references/hyperdataset/dataview.md#set_iteration_parameters) to manage the
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order, number, timing, and reproducibility of frames for training.
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@ -51,7 +51,7 @@ The app monitors your workspace for trigger events and will launch copies of the
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## Dashboard
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The Trigger Manager app instance's dashboard displays its console log. The log shows the instance’s activity: periodic
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The Trigger Manager app instance's dashboard displays its console log. The log shows the instance’s activity: periodic
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polling, and events triggered
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@ -1,95 +0,0 @@
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/**
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* Copyright (c) Facebook, Inc. and its affiliates.
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*
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* This source code is licensed under the MIT license found in the
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* LICENSE file in the root directory of this source tree.
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*
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* @format
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*/
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module.exports = {
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someSidebar: {
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'Getting Started': ['main','starting', 'architecture'],
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'Experiment Management': [
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{'Getting Started':['expman/main', 'expman/best practices']},
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{'Task':['expman/task/task','expman/task/task_details']},
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'expman/hyperparameters',
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'expman/artifacts',
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'expman/logger',
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'expman/integrations/libraries',
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'expman/clearml_task',
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{'Functionality':['expman/ui/leaderboard', 'expman/ui/task comparison']},
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{'Remote Development':['expman/remote/remote_jupyter','expman/remote/remote pycharm']},
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{'Advanced Topics':['expman/advanced/multiple tasks','expman/advanced/hpo']},
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],
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'Automation': [
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{
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'Getting Started': [
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'mlops/main',
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'mlops/setup/getting_started',
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'mlops/setup/agent',
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'mlops/setup/services',
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'mlops/best practices',
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],
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},
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{'ClearML Agent': [
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'mlops/concepts/agents_and_queues','mlops/concepts/clearml_agent_usage','mlops/concepts/services']
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},
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'mlops/orchestration/pipeline/create pipeline',
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],
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'Data Management': ['expman/data/data','expman/data/api'],
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'WebApp': ['webapp/webapp_overview','webapp/webapp_home',
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{'Projects Page':[
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{'Experiments':['webapp/webapp_exp_table','webapp/webapp_exp_track_visual','webapp/webapp_exp_reproducing','webapp/webapp_exp_tuning',
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'webapp/webapp_exp_comparing','webapp/webapp_exp_sharing']},
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{'Models': ['webapp/webapp_model_table','webapp/webapp_model_viewing','webapp/webapp_model_modifying']},
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'webapp/webapp_archiving']},
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'webapp/webapp_profile','webapp/webapp_workers_queues'],
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//'References': ['references/clearml_ref','references/clearml_agent_ref'],
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'DevOps': ['devops/main','expman/integrations/storage'],
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'Comments': ['Notes'],
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},
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refSidebar: {
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'References':['references/refmain','references/clearml_ref','references/clearml_agent_ref'
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],
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},
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guidesSidebar:{
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'Guides': [
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'guides/guidemain',
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{'Frameworks':[
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{'Autokeras':['guides/frameworks/autokeras/integration_autokeras','guides/frameworks/autokeras/autokeras_imdb_example']},
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{'FastAI':['guides/frameworks/fastai/fastai_with_tensorboard']},
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{'Keras': ['guides/frameworks/keras/allegro_clearml_keras_tb_example','guides/frameworks/keras/jupyter','guides/frameworks/keras/keras_tensorboard',
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'guides/frameworks/keras/manual_model_upload']},
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{'Matplotlib': ['guides/frameworks/matplotlib/allegro_clearml_matplotlib_example','guides/frameworks/matplotlib/matplotlib_example']},
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{'Pytorch':['guides/frameworks/pytorch/manual_model_upload','guides/frameworks/pytorch/pytorch_distributed_example','guides/frameworks/pytorch/pytorch_matplotlib',
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'guides/frameworks/pytorch/pytorch_mnist','guides/frameworks/pytorch/pytorch_tensorboard','guides/frameworks/pytorch/pytorch_tensorboardx',
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'guides/frameworks/pytorch/tensorboard_toy_pytorch']},
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{'Scikit-Learn':['guides/frameworks/scikit-learn/sklearn_joblib_example','guides/frameworks/scikit-learn/sklearn_matplotlib_example']},
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{'TensorboardX':['guides/frameworks/tensorboardx/tensorboardx']},
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{'Tensorflow':['guides/frameworks/tensorflow/manual_model_upload','guides/frameworks/tensorflow/tensorboard_pr_curve','guides/frameworks/tensorflow/tensorboard_toy',
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'guides/frameworks/tensorflow/tensorflow_mnist','guides/frameworks/tensorflow/integration_keras_tuner']},
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{'XGboost':['guides/frameworks/xgboost/xgboost_sample']},
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{'Pytorch Ignite':['guides/frameworks/pytorch_ignite/integration_pytorch_ignite']}
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]},
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{'Automation':['guides/automation/manual_random_param_search_example','guides/automation/task_piping']},
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{'Data Management':['guides/data management/data_man_simple','guides/data management/data_man_folder_sync','guides/data management/data_man_cifar_classification']},
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{'Clearml-task':['guides/clearml-task/clearml_task_tutorial']},
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{'Distributed':['guides/distributed/distributed_pytorch_example','guides/distributed/subprocess_example']},
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{'Optimization':['guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt']},
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{'Pipelines':['guides/pipeline/pipeline_controller']},
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{'Reporting':['guides/reporting/3d_plots_reporting','guides/reporting/artifacts','guides/reporting/clearml_logging_example','guides/reporting/html_reporting',
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'guides/reporting/hyper_parameters','guides/reporting/image_reporting','guides/reporting/manual_matplotlib_reporting','guides/reporting/media_reporting',
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'guides/reporting/model_config','guides/reporting/pandas_reporting','guides/reporting/plotly_reporting',
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'guides/reporting/scalar_reporting','guides/reporting/scatter_hist_confusion_mat_reporting','guides/reporting/text_reporting']},
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{'Services':['guides/services/aws_autoscaler','guides/services/cleanup_service','guides/services/execute_jupyter_notebook_server','guides/services/slack_alerts']},
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{'IDEs':['guides/ide/integration_jupyter','guides/ide/integration_pycharm', 'guides/ide/remote_jupyter_tutorial']},
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{'ClearML':['guides/clearml/building_leader_board', 'guides/clearml/explicit_reporting', 'guides/clearml/tuning_exp']},
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{'Storage':['guides/examples_storagehelper']}
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]
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}
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};
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