Fix links (#528)

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pollfly 2023-04-09 15:01:26 +03:00 committed by GitHub
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@ -179,7 +179,7 @@ The default operator for a query is `or`, unless `and` is placed at the beginnin
``` ```
### Retrieving Models ### Retrieving Models
Retrieve a local copy of a ClearML model through a `Model`/`InputModel` object's [`get_local_copy()`](../references/sdk/model_outputmodel.md#get_local_copy). Retrieve a local copy of a ClearML model through a `Model`/`InputModel` object's [`get_local_copy()`](../references/sdk/model_model.md#get_local_copy).
The method returns a path to a cached local copy of the model. In the case that the model is already cached, you can set The method returns a path to a cached local copy of the model. In the case that the model is already cached, you can set
`force_download` to `True` in order to download a fresh version. `force_download` to `True` in order to download a fresh version.
@ -192,7 +192,7 @@ These methods can be used on `Model`, `InputModel`, and/or `OutputModel` objects
* Single metric values - [`report_single_value`](../references/sdk/model_outputmodel.md#report_single_value) * Single metric values - [`report_single_value`](../references/sdk/model_outputmodel.md#report_single_value)
* Plots * Plots
* 2d plots * 2d plots
* Histogram - [`report_histogram`](../references/sdk/model_outputmodel.md#report_historgram) * Histogram - [`report_histogram`](../references/sdk/model_outputmodel.md#report_histogram)
* Vector as histogram plot - [`report_vector`](../references/sdk/model_outputmodel.md#report_vector) * Vector as histogram plot - [`report_vector`](../references/sdk/model_outputmodel.md#report_vector)
* Table - [`report_table`](../references/sdk/model_outputmodel.md#report_table) * Table - [`report_table`](../references/sdk/model_outputmodel.md#report_table)
* Line plot - [`report_line_plot`](../references/sdk/model_outputmodel.md#report_line_plot) * Line plot - [`report_line_plot`](../references/sdk/model_outputmodel.md#report_line_plot)

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@ -64,7 +64,7 @@ After invoking `Task.init` in a script, ClearML starts its automagical logging,
* [click](https://click.palletsprojects.com) (see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/click/click_multi_cmd.py)). * [click](https://click.palletsprojects.com) (see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/click/click_multi_cmd.py)).
* argparse (see argparse logging example [here](../guides/reporting/hyper_parameters.md).) * argparse (see argparse logging example [here](../guides/reporting/hyper_parameters.md).)
* [Python Fire](https://github.com/google/python-fire) - see code examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks/fire). * [Python Fire](https://github.com/google/python-fire) - see code examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks/fire).
* [LightningCLI](https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.cli.LightningCLI.html) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/jsonargparse/pytorch_lightning_cli.py). * [LightningCLI](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html#lightning-cli) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/jsonargparse/pytorch_lightning_cli.py).
* TensorFlow Definitions (`absl-py`) * TensorFlow Definitions (`absl-py`)
* [Hydra](https://github.com/facebookresearch/hydra) - the OmegaConf which holds all the configuration files, as well as overridden values. * [Hydra](https://github.com/facebookresearch/hydra) - the OmegaConf which holds all the configuration files, as well as overridden values.
* **Models** - ClearML automatically logs and updates the models and all snapshot paths saved with the following frameworks: * **Models** - ClearML automatically logs and updates the models and all snapshot paths saved with the following frameworks:

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@ -16,7 +16,7 @@ but can be overridden by command-line arguments.
|Name| Description | |Name| Description |
|---|--------------------------------------------------------------------------------| |---|--------------------------------------------------------------------------------|
|**CLEARML_LOG_ENVIRONMENT** | List of Environment variable names. These environment variables will be logged in the ClearML tasks configuration hyperparameters `Environment` section. When executed by a ClearML agent, these values will be set in the tasks execution environment. | |**CLEARML_LOG_ENVIRONMENT** | List of Environment variable names. These environment variables will be logged in the ClearML tasks configuration hyperparameters `Environment` section. When executed by a ClearML agent, these values will be set in the tasks execution environment. |
|**CLEARML_TASK_NO_REUSE** | Boolean. <br/> When set to `true`, a new task is created for every execution (see Task [reuse](../clearml_sdk/task_sdk#task-reuse)). | |**CLEARML_TASK_NO_REUSE** | Boolean. <br/> When set to `true`, a new task is created for every execution (see Task [reuse](../clearml_sdk/task_sdk.md#task-reuse)). |
|**CLEARML_CACHE_DIR** | Set the path for the ClearML cache directory, where ClearML stores all downloaded content. | |**CLEARML_CACHE_DIR** | Set the path for the ClearML cache directory, where ClearML stores all downloaded content. |
|**CLEARML_DOCKER_IMAGE** | Sets the default docker image to use when running an agent in [Docker mode](../clearml_agent.md#docker-mode). | |**CLEARML_DOCKER_IMAGE** | Sets the default docker image to use when running an agent in [Docker mode](../clearml_agent.md#docker-mode). |
|**CLEARML_LOG_LEVEL** | Sets the ClearML package's log verbosity. Log levels adhere to [Python log levels](https://docs.python.org/3/library/logging.config.html#configuration-file-format): CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET | |**CLEARML_LOG_LEVEL** | Sets the ClearML package's log verbosity. Log levels adhere to [Python log levels](https://docs.python.org/3/library/logging.config.html#configuration-file-format): CRITICAL, ERROR, WARNING, INFO, DEBUG, NOTSET |

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@ -286,7 +286,7 @@ to reproduce. You can see uncommitted changes in the ClearML Web UI, in the EXEC
Yes! ClearML provides multiple ways to configure your task and track your parameters! Yes! ClearML provides multiple ways to configure your task and track your parameters!
In addition to argparse, ClearML also automatically captures and tracks command line parameters created using [click](https://click.palletsprojects.com/), In addition to argparse, ClearML also automatically captures and tracks command line parameters created using [click](https://click.palletsprojects.com/),
[Python Fire](https://github.com/google/python-fire), and/or [LightningCLI](https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.cli.LightningCLI.html). [Python Fire](https://github.com/google/python-fire), and/or [LightningCLI](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html#lightning-cli).
ClearML also supports tracking code-level configuration dictionaries using the [Task.connect](references/sdk/task.md#connect) method. ClearML also supports tracking code-level configuration dictionaries using the [Task.connect](references/sdk/task.md#connect) method.

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@ -25,7 +25,7 @@ the following types of parameters:
* [click](https://click.palletsprojects.com) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/click/click_multi_cmd.py). * [click](https://click.palletsprojects.com) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/click/click_multi_cmd.py).
* [argparse](https://docs.python.org/3/library/argparse.html) - see code example [here](../guides/frameworks/pytorch/pytorch_tensorboardx.md). * [argparse](https://docs.python.org/3/library/argparse.html) - see code example [here](../guides/frameworks/pytorch/pytorch_tensorboardx.md).
* [Python Fire](https://github.com/google/python-fire) - see code examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks/fire). * [Python Fire](https://github.com/google/python-fire) - see code examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks/fire).
* [LightningCLI](https://pytorch-lightning.readthedocs.io/en/latest/api/pytorch_lightning.cli.LightningCLI.html) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/jsonargparse/pytorch_lightning_cli.py). * [LightningCLI](https://lightning.ai/docs/pytorch/stable/cli/lightning_cli.html#lightning-cli) - see code example [here](https://github.com/allegroai/clearml/blob/master/examples/frameworks/jsonargparse/pytorch_lightning_cli.py).
* TensorFlow Definitions (`absl-py`). See examples of ClearML's automatic logging of TF Defines: * TensorFlow Definitions (`absl-py`). See examples of ClearML's automatic logging of TF Defines:
* [TensorFlow MNIST](../guides/frameworks/tensorflow/tensorflow_mnist.md) * [TensorFlow MNIST](../guides/frameworks/tensorflow/tensorflow_mnist.md)
* [TensorBoard PR Curve](../guides/frameworks/tensorflow/tensorboard_pr_curve.md) * [TensorBoard PR Curve](../guides/frameworks/tensorflow/tensorboard_pr_curve.md)

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@ -69,7 +69,7 @@ understanding model behavior.
Hyperparameters can be added from anywhere in your code, and ClearML provides multiple ways to log them. If you specify Hyperparameters can be added from anywhere in your code, and ClearML provides multiple ways to log them. If you specify
your parameters using popular python packages, such as [argparse](https://docs.python.org/3/library/argparse.html) and your parameters using popular python packages, such as [argparse](https://docs.python.org/3/library/argparse.html) and
[click](https://click.palletsprojects.com/), all you need to do is [initialize](../references/sdk/task#taskinit) a task, and [click](https://click.palletsprojects.com/), all you need to do is [initialize](../references/sdk/task.md#taskinit) a task, and
ClearML will automatically log the parameters. ClearML also provides methods to explicitly report parameters. ClearML will automatically log the parameters. ClearML also provides methods to explicitly report parameters.
When executing a task through a ClearML agent, the ClearML instrumentation of your code allows for using the ClearML UI When executing a task through a ClearML agent, the ClearML instrumentation of your code allows for using the ClearML UI

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@ -80,7 +80,7 @@ in target local path [ClearML GitHub issue #709](https://github.com/allegroai/cl
**New Features and Improvements** **New Features and Improvements**
* Additional model information * Additional model information
* Add Lineage tab to UI model page, which displays experiment that created model and lists experiments that use the model [ClearML GitHub issue #810](https://github.com/allegroai/clearml/issues/810https://github.com/allegroai/clearml/issues/810) * Add Lineage tab to UI model page, which displays experiment that created model and lists experiments that use the model [ClearML GitHub issue #810](https://github.com/allegroai/clearml/issues/810)
* Add Plots and Scalars tabs to UI Model page * Add Plots and Scalars tabs to UI Model page
* Add project hierarchy view for ClearML resources (pipelines, datasets, hyper-datasets, reports) [ClearML GitHub issue #724](https://github.com/allegroai/clearml/issues/724): * Add project hierarchy view for ClearML resources (pipelines, datasets, hyper-datasets, reports) [ClearML GitHub issue #724](https://github.com/allegroai/clearml/issues/724):
* Flat view - all objects displayed side-by-side * Flat view - all objects displayed side-by-side