From a79447bba6823067da0cc55c2f2cf1c76868ff8c Mon Sep 17 00:00:00 2001 From: pollfly <75068813+pollfly@users.noreply.github.com> Date: Tue, 29 Jun 2021 11:22:12 +0300 Subject: [PATCH] Link to clear.ml docs and fix links (#389) * switch allegro.ai links to clear.ml * fix colab links * add newline --- docs/clearml-task.md | 10 +++++----- .../keras/jupyter_keras_TB_example.ipynb | 6 +++--- .../jupyter_matplotlib_example.ipynb | 6 +++--- .../reporting/jupyter_logging_example.ipynb | 18 +++++++++--------- 4 files changed, 20 insertions(+), 20 deletions(-) diff --git a/docs/clearml-task.md b/docs/clearml-task.md index b769a212..1e8418e2 100644 --- a/docs/clearml-task.md +++ b/docs/clearml-task.md @@ -1,7 +1,7 @@ # `clearml-task` - Execute ANY python code on a remote machine Using only your command line and __zero__ additional lines of code, you can easily integrate the ClearML platform -into your experiment. With the `clearml-task` command, you can create a [Task](https://allegro.ai/clearml/docs/docs/concepts_fundamentals/concepts_fundamentals_tasks.html) +into your experiment. With the `clearml-task` command, you can create a [Task](https://clear.ml/docs/latest/docs/fundamentals/task) using any script from **any python code or repository and launch it on a remote machine**. The remote execution is fully monitored. All outputs - including console / tensorboard / matplotlib - @@ -12,7 +12,7 @@ are logged in real-time into the ClearML UI. With the `clearml-task` command, you specify the details of your experiment including: * Project and task name * Repository / commit / branch -* [Queue](https://allegro.ai/clearml/docs/docs/concepts_fundamentals/concepts_fundamentals_workers_and_queues.html) +* [Queue](https://clear.ml/docs/latest/docs/fundamentals/agents_and_queues#what-is-a-queue) name * Optional: the base docker image to be used as underlying environment * Optional: alternative python requirements, in case `requirements.txt` is not found inside the repository. @@ -34,7 +34,7 @@ track and visualize the results in the ClearML Web UI. ### Prerequisites - A single python script, or an up-to-date repository containing the codebase. -- `clearml` installed. `clearml` also has a [Task](https://allegro.ai/clearml/docs/rst/getting_started/index.html) +- `clearml` installed. `clearml` also has a [Task](https://clear.ml/docs/latest/docs/fundamentals/task) feature but it requires two lines of code in order to integrate the platform. - `clearml-agent` running on at least one machine (to execute the experiment) @@ -56,7 +56,7 @@ By default, the execution working directory will be the root of the repository. The names of the arguments should match the argparse arguments, but without the '--' prefix. Instead of --key=value -> use `--args key=value`, for example `--args batch_size=64 epochs=1` 5. Select the queue for your Task's execution, for example: `--queue default`. If a queue isn't chosen, the Task - will not be executed, it will be left in [draft mode](https://allegro.ai/clearml/docs/docs/concepts_fundamentals/concepts_fundamentals_tasks.html?highlight=draft#task-states-and-state-transitions), + will not be executed, it will be left in [draft mode](https://clear.ml/docs/latest/docs/fundamentals/task#task-states), and you can enqueue and execute the Task at a later point. 6. Add required packages. If your repo has a requirements.txt file, you don't need to do anything; `clearml-task` will automatically find the file and put it in your Task. If your repo does __not__ have a requirements file and @@ -83,7 +83,7 @@ You will be launching a single local script file (no git repo needed) on a remot 5. If you have a docker container with an entire environment in which you want your script to run inside, add e.g. `--docker nvcr.io/nvidia/pytorch:20.11-py3` 6. Select the queue for your Task's execution, for example: `--queue dual_gpu`. If a queue isn't chosen, the Task - will not be executed, it will be left in [draft mode](https://allegro.ai/clearml/docs/docs/concepts_fundamentals/concepts_fundamentals_tasks.html?highlight=draft#task-states-and-state-transitions), + will not be executed, it will be left in [draft mode](https://clear.ml/docs/latest/docs/fundamentals/task#task-states), and you can enqueue and execute it at a later point. ``` bash diff --git a/examples/frameworks/keras/jupyter_keras_TB_example.ipynb b/examples/frameworks/keras/jupyter_keras_TB_example.ipynb index 4b6e3af3..e270c42e 100644 --- a/examples/frameworks/keras/jupyter_keras_TB_example.ipynb +++ b/examples/frameworks/keras/jupyter_keras_TB_example.ipynb @@ -9,7 +9,7 @@ "source": [ "# Allegro ClearML Keras with TensorBoard example\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/frameworks/keras/Allegro_Trains_keras_TB_example.ipynb)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/frameworks/keras/jupyter_keras_TB_example.ipynb)\n", "\n", "This example introduces ClearML with Keras and TensorBoard functionality, including automatic logging, models, and TensorBoard outputs. You can find more frameworks examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks).\n", "\n", @@ -40,7 +40,7 @@ "### Create a new task.\n", "To create a new Task object, call the `Task.init` method providing it with `project_name` (the project name for the experiment) and `task_name` (the name of the experiment). When `Task.init` executes, a link to the Web UI Results page for the newly generated Task will be printed, and the Task will be updated in real time in the ClearML demo server.\n", "\n", - "You can read about the `Task` class in the docs [here](https://allegro.ai/docs/task.html)." + "You can read about the `Task` class in the docs [here](https://clear.ml/docs/latest/docs/fundamentals/task)." ] }, { @@ -228,4 +228,4 @@ }, "nbformat": 4, "nbformat_minor": 1 -} +} \ No newline at end of file diff --git a/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb b/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb index b5bb496a..b2736ac7 100644 --- a/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb +++ b/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb @@ -9,7 +9,7 @@ "source": [ "# Allegro ClearML matplotlib example\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/frameworks/matplotlib/Allegro_Trains_matplotlib_example.ipynb)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/frameworks/matplotlib/jupyter_matplotlib_example.ipynb)\n", "\n", "This example introduces ClearML with matplotlib functionality. It also shows seaborn functionality. You can find more frameworks examples [here](https://github.com/allegroai/clearml/tree/master/examples/frameworks).\n", "\n", @@ -42,7 +42,7 @@ "\n", "To create a new Task object, call the `Task.init` method providing it with `project_name` (the project name for the experiment) and `task_name` (the name of the experiment). When `Task.init` executes, a link to the Web UI Results page for the newly generated Task will be printed, and the Task will be updated in real time in the ClearML demo server.\n", "\n", - "You can read about the `Task` class in the docs [here](https://allegro.ai/docs/task.html)." + "You can read about the `Task` class in the docs [here](https://clear.ml/docs/latest/docs/fundamentals/task)." ] }, { @@ -235,4 +235,4 @@ }, "nbformat": 4, "nbformat_minor": 1 -} +} \ No newline at end of file diff --git a/examples/reporting/jupyter_logging_example.ipynb b/examples/reporting/jupyter_logging_example.ipynb index 068a1222..871525e8 100644 --- a/examples/reporting/jupyter_logging_example.ipynb +++ b/examples/reporting/jupyter_logging_example.ipynb @@ -9,9 +9,9 @@ "source": [ "# Allegro ClearML logging example\n", "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/reporting/Allegro_Trains_logging_example.ipynb)\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/allegroai/clearml/blob/master/examples/reporting/jupyter_logging_example.ipynb)\n", "\n", - "This example introduces ClearML [Logger](https://allegro.ai/docs/logger.html) functionality. Logger is the ClearML console log and metric interface.\n", + "This example introduces ClearML [Logger](https://clear.ml/docs/latest/docs/fundamentals/logger) functionality. Logger is the ClearML console log and metric interface.\n", "\n", "You can find more reporting examples [here](https://github.com/allegroai/clearml/tree/master/examples/reporting)." ] @@ -42,7 +42,7 @@ "\n", "To create a new Task object, call the `Task.init` method providing it with `project_name` (the project name for the experiment) and `task_name` (the name of the experiment). When `Task.init` executes, a link to the Web UI Results page for the newly generated Task will be printed, and the Task will be updated in real time in the ClearML demo server.\n", "\n", - "You can read about the `Task` class in the docs [here](https://allegro.ai/docs/task.html).\n", + "You can read about the `Task` class in the docs [here](https://clear.ml/docs/latest/docs/fundamentals/task).\n", "\n", "After the Task is created, get a Logger for it." ] @@ -77,7 +77,7 @@ }, "source": [ "### Explicit scalar logging\n", - "Use the [Logger.report_scalar](https://allegro.ai/docs/logger.html#clearml.logger.Logger.report_scalar) method to explicitly log scalars. Scalar plots appear in the Web UI, Results > Scalars tab." + "Use the [Logger.report_scalar](https://clear.ml/docs/latest/docs/references/sdk/logger#report_scalar) method to explicitly log scalars. Scalar plots appear in the Web UI, Results > Scalars tab." ] }, { @@ -112,7 +112,7 @@ "\n", "You can log other data and report the data in a variety of plot types, including histograms, confusion matrices, 2D and 3D scatter diagrams, and surface diagrams. They appear in the Results > Plots tab.\n", "\n", - "For information about the methods to report each type of plot, see the [Logger](https://allegro.ai/docs/logger.html) module.\n" + "For information about the methods to report each type of plot, see the [Logger](https://clear.ml/docs/latest/docs/references/sdk/logger) module.\n" ] }, { @@ -228,7 +228,7 @@ "\n", "We use StorageManager to download a local copy of the files. You can use it immediately. Just provide the URL. Cache is enabled by default for all downloaded remote URLs/files.\n", "\n", - "For more information, you can read about the storage manager [here](https://allegro.ai/docs/storage_manager_storagemanager.html)." + "For more information, you can read about the storage manager [here](https://clear.ml/docs/latest/docs/references/sdk/storage)." ] }, { @@ -273,7 +273,7 @@ "source": [ "#### Report images and media\n", "\n", - "Use [Logger.report_image](https://allegro.ai/docs/logger.html?highlight=report_image#clearml.logger.Logger.report_image) and [Logger.report_media](https://allegro.ai/docs/logger.html?highlight=report_media#clearml.logger.Logger.report_media) to report the downloaded samples. The debug samples appear in the Results > Debug Samples tab." + "Use [Logger.report_image](https://clear.ml/docs/latest/docs/references/sdk/logger#report_image) and [Logger.report_media](https://clear.ml/docs/latest/docs/references/sdk/logger#report_media) to report the downloaded samples. The debug samples appear in the Results > Debug Samples tab." ] }, { @@ -316,7 +316,7 @@ }, "source": [ "### Explicit text logging\n", - "Use [Logger.report_text](https://allegro.ai/docs/logger.html?highlight=report_text#clearml.logger.Logger.report_text) to log text message. They appear in Results > Log." + "Use [Logger.report_text](https://clear.ml/docs/latest/docs/references/sdk/logger#report_text) to log text message. They appear in Results > Log." ] }, { @@ -344,7 +344,7 @@ "\n", "Reports are flushed in the background every couple of seconds, and at the end of the process execution.\n", "\n", - "Or, flush the Logger by calling [Logger.flush](https://allegro.ai/docs/logger.html?highlight=report_text#clearml.logger.Logger.flush)." + "Or, flush the Logger by calling [Logger.flush](https://clear.ml/docs/latest/docs/references/sdk/logger#flush)." ] }, {