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@@ -53,18 +53,21 @@ required python packages, and execute and monitor the process.
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(or even multiple queues), but only a single agent will pull a Task to be executed.
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:::tip Agent Deployment Modes
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ClearML Agents can be deployed in Virtual Environment Mode or Docker Mode. In [virtual environment mode](../../clearml_agent/clearml_agent_execution_env.md),
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the agent creates a new venv to execute an experiment. In [Docker mode](../../clearml_agent/clearml_agent_execution_env.md#docker-mode),
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the agent executes an experiment inside a Docker container. For more information, see [Running Modes](../../fundamentals/agents_and_queues.md#running-modes).
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ClearML Agents can be deployed in:
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* [Virtual environment mode](../../clearml_agent/clearml_agent_execution_env.md): Agent creates a new venv to execute an experiment.
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* [Docker mode](../../clearml_agent/clearml_agent_execution_env.md#docker-mode): Agent executes an experiment inside a
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Docker container.
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For more information, see [Running Modes](../../fundamentals/agents_and_queues.md#running-modes).
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:::
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## Clone an Experiment
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Experiments already in the system can be reproduced for validation, or used as a baseline for further experimentation.
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Experiments can be reproduced (cloned) for validation or as a baseline for further experimentation.
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Cloning a task duplicates the task's configuration, but not its outputs.
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**To clone an experiment in the ClearML WebApp:**
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1. Click on any project card to open its [experiments table](../../webapp/webapp_exp_table.md)
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1. Right-click one of the experiments on the table
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1. Click on any project card to open its [experiments table](../../webapp/webapp_exp_table.md).
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1. Right-click one of the experiments on the table .
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1. Click **Clone** in the context menu, which will open a **CLONE EXPERIMENT** window.
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1. Click **CLONE** in the window.
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@@ -169,7 +172,7 @@ Logging models into the model repository is the easiest way to integrate the dev
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Any model stored by a supported framework (Keras / TensorFlow / PyTorch / Joblib etc.) will be automatically logged into ClearML.
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ClearML also supports methods to explicitly log models. Models can be automatically stored on a preferred storage medium
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(s3 bucket, google storage, etc.).
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(S3 bucket, Google storage, etc.).
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#### Log Metrics
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Log as many metrics as you want from your processes using the [Logger](../../fundamentals/logger.md) module. This
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@@ -62,7 +62,7 @@ dataset.tags = []
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new_dataset.tags = ['latest']
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```
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The new dataset inherits the contents of the datasets specified in `Dataset.create`'s `parents` argument.
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The new dataset inherits the contents of the datasets specified in `Dataset.create`'s `parent_datasets` argument.
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This not only helps trace back dataset changes with full genealogy, but also makes the storage more efficient,
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since it only stores the changed and/or added files from the parent versions.
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When you access the Dataset, it automatically merges the files from all parent versions
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